Conversational Commerce Platforms and Solutions

Conversational Commerce Platforms and Solutions

Conversational commerce has evolved into a multifaceted landscape with numerous channels and platforms available for direct business-to-customer communication.

From chatbots and virtual assistants to voice-enabled interfaces, each type of conversational platform brings its unique strengths to the table. These multi-featured platforms are called conversational experience solutions.

Let’s explore how you can leverage these platforms to make your shopping experience as convenient as possible for your customers.

Heard about conversational commerce, but not sure how to get started?

Don’t worry— we’ve got you covered.

This new trend, often called chat commerce, is reshaping the way businesses connect with their customers, and those who get a jump-start, will be poised to gain a competitive advantage.

For a comprehensive understanding of conversational commerce, check out our previous articles covering its fundamentals, use cases, and implementation strategies.

Leveraging any of the wider known messenger apps (e.g. Facebook Messenger, WhatsApp Business, Viber, etc.) starts by choosing a conversational commerce platform that helps you with this kind of implementation. Oftentimes, they are quite versatile and offer other features for E-commerce businesses, besides the opportunity to be in contact with their customers directly. 

Why to Use a Conversational Commerce Platform?

Let’s take a quick peek at the most important features of said platforms:

  • automated conversations through chatbots

Powered by artificial intelligence, they can engage in real-time conversations with customers, answer their queries, and provide support.

  • personalized experiences and recommendations

This is a standout feature of conversational commerce platforms, thanks to their ability to access customer data, such as purchase history and preferences. It enhances customer satisfaction, customer loyalty, and ultimately increase conversion rate. 

  • omni-channel communication

When choosing a platform, you first need to make sure it’s compatible with the messaging channel you plan to use. To choose the best channel for your business, make sure you consider factors such as your target audience and geographical location, and the specific features offered by each to align with your business objectives.

omnichannel communication illutration

An omni-channel communication platform is a great choice if you’d like to engage with your customers across multiple messaging channels, be it social media platforms, messaging apps, and ecommerce websites. Ensuring that your customers can interact with you in the way they prefer enhances their convenience and satisfaction.

NLP enables the platform to understand and interpret user queries in a more human-like manner. By comprehending the context and intent behind customer messages, you can deliver more accurate and relevant responses to them. 

  • advanced analytics and reporting capabilities

Thanks to this feature, you gain insights into customer interactions, track key metrics, and measure the effectiveness of your conversational marketing strategy. This can help you refine strategies, optimize customer journeys, and drive better outcomes.

Choosing Your Ideal Platform: A Strategic Decision

When selecting the ideal platform for your business, opt for one that suits your business requirements and objectives, plus, integrates seamlessly with your current systems.

Evaluate aspects such as scalability, customization options tailored to your unique requirements, and compatibility with your E-commerce platform to make an informed decision.

Conversational Commerce Platforms illustration - implementation

There are two major use cases of conversational commerce platforms that stand out from the rest: 

  1. Support

Through the integration of chatbots and AI-driven systems, businesses can provide instant assistance to customers, offer 24/7 support, and address their concerns in real-time.

Intercom’s has long been a popular support platform and is now integrating AI chat capabilities to support conversational scenarios. Their chatbot, called Fin, is powered by GPT-4 and is available 24/7 and chats with your customers to resolve queries based on your support content. 

You can see a demo of Fin in action here.

  1. Sales 

Conversational commerce tools can take the offline shopping experience, online by replicating the experience of sales assistants who engage potential customers in personalized conversations. They can recommend products, answer customer inquiries, and guide users through the purchasing process seamlessly. 

Chatfuel is a chat commerce platform that has ready-to-use templates that you can use to engage your customers on other channels. This can help you build workflows to automate cart abandonment reminders, track orders, and more. 

Types of Conversational Experience Platforms (and How Can You Benefit from Using Each)?

Each conversational commerce platform can provide your business with unique features and benefits, however, in order to choose one you need to clarify what your objectives are and what purposes you would use it for.

Let’s see the most common solutions that conversational platforms support:

Build-your-own AI Chatbot platform solutions

These messaging platforms enable you to build your own chatbot to leverage the power of AI in customer support and engagement. The communication channels are up to your (and your customers’) preferences.

Instant chatbot support is quite an attractive feature for online shoppers when it comes to getting help with a service.

💡Pro tip: to maintain a balance between automation and human touch, provide the option for users to connect with human agents when they feel their case requires it.

The next level of automated E-commerce messaging is when the entirety of the shopping journey is carried out with the help of chatbots.

AI Customer Engagement solutions (Marketing Automation)

The purpose of these solutions is to assist your business in creating different campaigns for increased customer engagement. They help you find the most relevant content for your target audience, alongside the best communication channels and the recommended time of publication. 

Furthermore, automation promotes speedier communication between customers and businesses, allowing for faster problem-resolution times at cheaper costs than human processes.

Cloud Contact Center solutions

As a 2021 study shows, 77% of contact centers that already used AI for multiple purposes back then, reduced their overall costs as a result. 

In the context of contact centers, AI-powered bots are able to handle first line of customer interactions and free up some time in your customer service team’s already busy phone line. 

Cloud contact center illustration

Chat commerce solutions can help you connect different digital channels to ensure the same level of service, regardless of the way your online shoppers decided to get in touch. Usually, you can access all relevant channels from one interface, alongside the information related to your customer’s profile.

AI Customer Data platforms

These platforms let you gather, store, and analyze data about users to create customer profiles and enable you to personalize every interaction with them for enhanced user experience. With the help of AI, you can recommend your products and services to the right audience, based on individual profile data. 

As we mentioned at the beginning of this article, there are platforms that offer numerous different features for businesses instead of focusing on one of the developmental areas. These are called conversational experience solutions.

Case Study: Infobip

Infobip is a great example of an omnichannel conversational experience solution. They are a CPaaS (communication platform as a service) company that now also empowers businesses to integrate chat commerce seamlessly into their operations.

Infobip’s multifunctional services include all of the above-mentioned features and solutions. 

They enable you to communicate with your customers over their favorite channels. By expanding your communication solutions and channel portfolio, you can create new revenue streams and win new business.  

Infobip allows you to craft end-to-end customer journeys powered by AI and build your own Gen AI-based chatbot by your own rules. They also have a solution that lets you create customer profiles as well, for maximum personalization. 

Creating connected customer experiences is at the heart of what we do

To enable your shoppers to reach out directly to your business with inquiries, be it about general product recommendations, needing support with choosing the right product, or having trouble with payment, you can choose Infobip’s chatbot platform, and imitate the feel of a human conversation with many times fewer effort. 

Wrap up

In conclusion, conversational commerce platforms represent a transformative force in the E-commerce landscape. 

From instant AI-backed support to personalized sales assistance, these platforms redefine the dynamics of business-consumer relationships. In order to select the platform best for your business, start by identifying your goals and what you want to achieve.

As customer expectations continue to shift towards seamless and personalized interactions, leveraging these platforms becomes not just an option but a valuable addition to any E-commerce strategy.

Paige TyrrellHead of Marketing – Prefixbox

Paige is the Head of Marketing at Prefixbox, a leading eCommerce site search solution. She’s an American who’s been living in Budapest since 2017 and loves giving #alwayslearning sessions to help people optimize their online stores.

Unveiling How Vector Search Works

Unveiling How Vector Search Works

Vector Search is a game-changer for retailers striving to enhance their online user experience, boost conversion rates, and increase their online revenue. 

In this article we are going to delve deeper into how this transformative technology actually works

We’ve recently covered the basics and the main benefits of vector search, an emerging technology that’s redefining how we search and shop online.

Check our mini video series on the topic too! Now let’s see the technical aspects of vector search.

Mathematical representation of information

The key difference between vector and keyword search lies in the way data is represented and compared.

Traditional search methods treat data as a collection of words, focusing on the presence or absence of specific terms. Vector search, on the other hand, uses vector embeddings to represent data points.

Vectors are essentially mathematical representations of objects, whether they be words, products, or images.

Each product in an E-commerce catalog is translated into a vector in a high-dimensional space. These dimensions can represent various product attributes. For example, movies might be represented as vectors where each dimension represents a movie feature (e.g., genre, director, actors, etc.).

By operating in high-dimensional spaces, the search algorithm can capture intricate relationships and similarities between products. For example, products with similar attributes will have vectors that are closer in this multi-dimensional space.

Vectorization methods

E-commerce site search relevancy

To create vector representations, you can use various techniques, such as Word2Vec, Doc2Vec or deep learning models like convolutional neural networks (CNNs) or recurrent neural networks (RNNs). The choice of machine learning method depends on the data and the problem you are trying to solve.

In the E-commerce setup, methods like word embeddings (for textual product descriptions), product embeddings (based on their attributes), session data embeddings (that adds up to a user profile), and hybrid models that combine multiple vectorization methods might be the most beneficial, providing the best search accuracy.


Once you have vector representations for all your items, you need to index them for efficient retrieval.

This is often done using data structures like search trees or more advanced techniques like locality-sensitive hashing (LSH) or approximate nearest neighbor (ANN) indexes. These data structures enable fast nearest-neighbor searches.

Search Query Vector

When a user or system submits a query, it is also vectorized in the same manner as the items. The query vector represents the features or characteristics of the query, which then will be used as a base of similarity to find the relevant products in stock.

Vector Search vector embeddings illustration with a bonsai tree

Similarity Metrics

To find similar items in vector databases, you need a way to measure the similarity between the search query vector and the vectors of items in the dataset. Common similarity metrics include cosine similarity, Euclidean distance, L2 distance and Jaccard similarity, among others.

Closeness in space means more vector similarity, whereas more distance means fewer common characteristics. Businesses using a vector search engine could perform nearest-neighbor searches to determine distance metrics to the closest query-related vectors in a space. 

Utilizing the joint power of keyword and vector search

When vector search and keyword search results are blended, it’s called a hybrid search solution.

A hybrid search engine that combines keyword-based and vector-based approaches offers a more robust and versatile solution, providing highly relevant search results across a wide range of scenarios.

But how exactly are keyword and vector search results blended?

There are multiple different ways, but here’s how we do it at Prefixbox:

In a vector-based search result, you can still have traditional keyword-based search scores, like

  • the matching score, which shows how relevant the result is for a specific search query, and
  • the popularity score, which shows how popular a specific search result is.

In addition to these scores, the vector-based search results have similarity scores, which are based on the mathematical representation of the keyword, and its distance from the result in the vector space.

Blending is the method of merging the result lists. This can be achieved by scaling and normalizing these scores by applying weights in order to get the best ranking. 


Vector search is a technique used to find similar items in a large dataset based on their vector representations. Applications span from content recommendation to image retrieval and E-commerce product recommendations.

It’s the critical element that empowers recommendation systems to deliver more insightful suggestions and fine-tunes search engines for superior performance. 


Vector Search: The Future of E-commerce Search

Vector Search: The Future of E-commerce Search

What if there was a revolutionary way to help shoppers navigate the vast E-commerce universe? One where search results are not just based on keywords, but on the essence of the products themselves?

In this article, we discuss:

  • What Vector Search is
  • 7 Main Advantages of Vector Search over traditional Keyword Search technology

Importance of E-commerce Search

In the ever-evolving landscape of E-commerce, where countless products are just a click away, the power of search cannot be overstated.

The search bar is the key to directing shoppers to the products they want to buy.

People who search spend 2.6 times more money compared to non-searchers, and on for B2B sites, 92% of purchases start with search!   

Issues with traditional keyword search

More often than not, search solutions are currently powered by traditional keyword-based search, which are usually called semantic search engines (when they have advanced capabilities like query understanding). This traditional search method that, as the name suggests, relies on keywords, has its limitations.

Solutions that only leverage keyword matches often require a lot of manual optimization efforts (think: relevance optimization, matching and tuning weight editing, and synonym management), otherwise they lead to irrelevant results, frustrating experiences, and missed revenue opportunities.

Online E-commerce store illustration

This is where vector search enters the scene, a transformative technology that has the potential to redefine the E-commerce search experience.

Vector and keyword-based search can be combined to give you the most powerful search on the market.

But first let’s get started with an overview of vector search.

What is Vector Search?

Vector search is a search methodology that provides even more relevant results by taking into account information like: product descriptions and user behavior to return better quality search results.

Unlike traditional keyword search , vector search seeks to understand the inherent qualities and relationships between items in a dataset. To put it even more simply, it’s like transitioning from looking up words in a dictionary to understanding concepts and their connections.

Vector Search goes beyond mere keywords, diving deep into the very nature of products, understanding their features and nuances. This means more relevant search results, better product recommendations, and an altogether more satisfying shopping journey.

Benefits of Vector Search for E-commerce businesses

One of the primary challenges with traditional E-commerce search methods (keyword-based search) is the heavy reliance on keyword matching.

Until the emergence of vector search, this has been a challenge for shoppers because, in order to receive relevant results, a retailer must have a highly optimized search solution or the shopper must meticulously craft their search queries in order to see relevant results.

E-commerce vector search illustration

However, with a solution solely leveraging keyword-matching search, even the best search queries can still return irrelevant results.

For example, searching for “black leather boots” might return brown boots or other unrelated products simply because they’re black OR leather. 

This is where vector search can make a big difference, offering numerous benefits for both customers and E-commerce businesses.

Here are the 7 main  benefits you can get from using a search solution that leverages vector search.

Result Relevance Improvement

Vector search enables shoppers to search more generally, while prioritizing relevancy, which means even if they cannot exactly explain what product they need, they can search for the concept and receive matching results.

Take the following queries for example:

  1. home decor items for a minimalist living room
  2. engagement rings with sapphire stones
  3. skincare products for sensitive skin
  4. hiking boots for all-terrain trekking
  5. recommend pet toys for large dogs

A search engine powered by vector search would understand these broadly described concepts, and provide the user with the following results:

  1. furniture, lighting and accessories that align with the minimalist aesthetic
  2. a list of rings specifically designed for engagement, featuring sapphire gemstones
  3. all kinds of skincare products known to be gentle and beneficial for sensitive skin (moisturizers, cleansers, serums)
  4. hiking boots known for their durability and performance on various terrains
  5. a selection of pet toys specifically designed for larger breeds, taking into account durability and safety

By leveraging a technology that can understand such queries, you can boost your search coverage, which will lead to Zero Result Search Rate reduction, and Search Success Rate, Conversion Rate, and Revenue increases.

If you want to dive deeper into measuring your E-commerce store, check our comprehensive guide on the 25 most essential E-commerce KPIs.

Enhanced User Experience

Vector search enhances the overall shopping experience.

Besides returning more relevant results and enabling shoppers to search using natural language (no need for exact keyword matches), it supports real-time updates, so shoppers always see in-stock products and the most up-to-date product information. Of course, it also helps reduce the appearance of irrelevant products.

All this together can lead to longer sessions, a higher retention rate, and a greater sense of user satisfaction.

Faster Shopping Journey

Vector search streamlines the search process, ensuring a quicker shopping journey for the user. Its ability to understand and interpret intent means that customers spend less time thinking about how to phrase, then rephrase their search queries, sometimes several times in a row. 

By using vector representations, the search engine narrows down the search space to focus on items that are semantically similar to the user’s query. This reduces the number of items that need to be considered during the search process, and as a consequence, it can provide results more quickly since it doesn’t need to sift through a vast number of irrelevant items.

Less Manual Synonym Editing Work

Synonym management is an important, but extremely time-consuming, way to optimize your online store’s search results. Most often, tagging products and keywords with relevant synonymous keywords is a manual process.

There are solutions for automatically mining and recommending synonyms for search keywords in order to improve synonym management productivity, but these recommendations still need to be manually reviewed for accuracy.

Vector Search synonym management illustration

Vector search can handle synonyms automatically based on the language model it leverages by machine learning techniques.
By freeing up your team from this time-intensive process, imagine how much more time they’ll have for other conversion rate- and UX optimizations.

Improved Personalization and Recommendations

By deeply understanding product relationships, vector search powers advanced personalization and recommendation systems. This not only helps customers discover new items they might love but also increases cross-selling and upselling opportunities for E-commerce businesses, and can even be used for digital marketing purposes as well.

Besides creating vector embeddings of the search queries sent and the products in your stock, you can make a vector space of user profiles and offer an even more personalized shopping experience for your customers based on their journey on your site and their behavior in general (categories of interest, previous purchases, etc.) 

Learn more about AI-drive product recommendation from our all-inclusive guide.

Adaptation to Evolving Language

This is a significant challenge for search engines, as language is constantly evolving with the introduction of new words, phrases, and shifts in terminology. 

Traditional keyword-based search relies on predefined lists of keywords, which results in less adaptiveness to linguistic changes. This limitation might lead to a less satisfactory shopper experience. 


Thanks to Natural Language Processing (NLP), vector-based search models can adapt more quickly to changes in language usage and stay current with evolving language through machine learning.

Smart Ranking

Besides the traditional keyword-based search scores, like the matching and the popularity score, vector-based search results have a so-called similarity score. This is computed based on the item’s vector distance from the query’s vector.

A search solution powered by vector databases ranks the search results based on their similarity to the query. The most similar items are retrieved and presented to the user.

Hybrid Search – Blending Vector and Keyword Search 

The emergence of vector technology does not mean that it will replace keyword search altogether. Instead, they complement each other, so that more, and more relevant results appear.

When vector search and keyword search results are blended, it’s called a Hybrid search solution.

A Hybrid Setup that combines keyword-based and vector-based approaches offers a more robust and versatile solution, thanks to the benefits mentioned above, providing highly relevant search results across a wide range of scenarios. 

But let’s cut the story here for now, we have another blog post exploring this topic.

Wrap Up

Vector search is transforming the search and online shopping experience. 

As the E-commerce landscape continues to evolve, businesses that embrace vector search are poised to lead the way. 

By adopting this transformative technology, you can revolutionize how customers discover and shop for products while optimizing your operations for the future. 

How to Implement Conversational Commerce? 5 Steps to Success [2023]

How to Implement Conversational Commerce? 5 Steps to Success [2023]

Are you ready to take your E-commerce business to the next level by opening a new revenue stream and improving your customer experience?

In this article, we discuss:

  • the 4 most essential ways how conversational commerce can contribute to your business goals
  • 5 steps to successfully implement conversational commerce
Conversational Commerce Implementation blogpost illustration

Conversational Commerce Basics

Chat commerce (or conversational commerce) is a new avenue of shopping where people can interact with their brands directly to ask questions, find products, and make purchases all via a messaging platform. It combines the convenience of messaging platforms with the personalized experience of a real conversation.

It is changing the way both retailers and shoppers think about online shopping and those businesses that can move fast will get a competitive advantage.

If you’ve already heard about this topic, but aren’t sure how to get started, you’re in the right place!

We’ll explain the benefits of conversational commerce (both for retailers and shoppers) and have gathered 5 steps below to help you get started in your conversational commerce journey today.

How can conversational commerce contribute to your E-Commerce brand and increase your revenue?

Conversational commerce has become increasingly important for E-commerce retailers, as it offers numerous benefits for both the brand and the customers.

By integrating messaging platforms and artificial intelligence, conversational commerce provides a personalized and interactive experience for shoppers, revolutionizing the way E-commerce businesses engage with their audience.

This avenue of shopping opens a dialogue between retailers and their potential customers.

Customers may interact with one of the company’s human representatives, a chatbot, or a mix of both.

From guiding shoppers through their entire buying journey to nurturing post-purchase customer relationships, chat commerce enables brands to enhance customer satisfaction, increase conversion rates, drive sales, and foster customer loyalty and retention. According to a Hubspot study, 47% of shoppers are already open to buying items via a chatbot.

The most essential benefits in more detail are the following:

Engage shoppers with seamless experience

Conversational commerce tools can be integrated into various platforms, including live chat on websites and social messaging apps (like Facebook Messenger) allowing businesses to meet customers where they already are.

It saves shoppers time by providing instant responses and eliminating the need to browse through search engine results or navigate complex E-commerce websites. This immediacy not only increases customer satisfaction but also increases conversion rates and reduces shopping cart abandonment.

Personalize the buying journey

There are many ways in which chat commerce brings customers closer to businesses. By leveraging messaging platforms and AI-powered chatbots, e-tailers can create a personalized experience that meets the unique needs and preferences of each individual shopper.

Every interaction with your customers via chat commerce allows your E-commerce business to gain further insight into their preferences, interests, and concerns. 

By building this consumer profile, you’re able to create a much more personalized shopping experience.

Over time, chatbots can help you engage even more in natural conversations, providing relevant information and guidance in real time. They can remember previous interactions and preferences, ensuring a seamless and consistent experience across multiple customer touchpoints. For example, Sa Sa Hong Kong beauty retailer decreased waiting times by 57% with automated chat commerce solutions according to Facebook.

Improve conversion rates and order value

Chat commerce has the potential to significantly boost conversion rate and increase order value, particularly when automated by AI chatbots.

Thanks to chatbots tailoring their recommendations based on data that the shopper continuously provides, customers find products that they are more likely to purchase.

What’s more, this feature also increases the likelihood of upselling and cross-selling for businesses, thus driving up the order value.

Sometimes, consumers abandon their shopping carts due to distractions or indecisiveness. On the topic of order values, conversational messaging platforms can be leveraged to send shopping cart reminders as well.

By sending these reminders through chat apps (like Facebook Messenger or Viber), businesses can prompt customers to complete their purchases, contributing to a growth in conversion rates and average order value.

Improve the post-purchase experience

Leveraging conversational AI does not have to end upon purchase. AI chatbots can contribute to enhancing customer loyalty by providing customer service and support after shopping, like offering post-purchase recommendations and alternative products upon a return.

By automating this part of the shopping journey, companies can free up human agents to focus on more complex challenges, such as addressing specific consumer queries or handling escalations.

This allows them to provide faster and more efficient support to a larger number of shoppers, enhancing overall customer satisfaction.

How to implement conversational commerce? TL;DR

There are 5 main steps that businesses can take to successfully integrate conversational commerce into their operations.

  1. Get to planning and goal-setting
  2. Choose the right messaging platform
  3. Create a structure for conversations
  4. Implement and train your own AI-powered chatbot
  5. Monitor and adjust relevant KPIs

1. Get to planning and goal-setting

Formulating your plans and objectives for implementing chat commerce in your store might be just as important as the practical implementation itself.

Understanding your business’ needs and goals is essential as it will help you determine how conversational AI can resolve your challenges effectively.

Pro tip: start small and build upon your successes. As for the first few weeks of your plan, set goals like decreasing the customer service queries by 8-10%, or increase online orders by 5-7%, etc.

Moreover, knowing where your customers are is fundamental. Different chat apps attract different demographics. Knowing the target audience’s preferred communication channels helps you with choosing which platforms to be present on.

Customer’s behavioral patterns and interests are also key factors. Analyze data from your existing customer base and identify common characteristics to create  personas.

These personas will guide your conversational commerce strategy, allowing you to tailor your messaging and personalized experiences to specific customer segments.

2. Choose the right messaging platform

When it comes to conversational commerce, choosing the right messaging platform is crucial for a successful customer journey. Popular mobile messaging apps like Facebook Messenger and WhatsApp are leading the way in consumer communication and online shopping. As of 2023, mobile commerce or M-commerce already takes up more than 60% of all E-commerce sales worldwide, based on Statista’s numbers.

These platforms offer a range of features that make them effective, such as direct and convenient means of engaging with potential and existing customers.

When choosing a messaging platform, it’s important to note which functionalities are supported and what limitations exist.

Each messaging platform is different, so based on the one you decide to use, you will need to adapt your strategy accordingly. 

3. Create a structure for conversation

Creating a structured and effective conversation between a seller and a client involves careful planning and design.

It’s important to maintain a conversational and friendly tone throughout the interaction, and the chatbot or seller should be adaptable to handle unexpected questions or issues that may arise.

Identify the scenarios you want to support via chat commerce and design an ideal conversation flow as the baseline to get started. 

Regularly analyze and refine the conversation structure based on customer feedback and evolving business needs to continually improve the chat commerce experience.

A possible guide for your seller-shopper conversation:

Greeting and introduction

Identification and verification

  • if necessary, verify the shopper’s identity to ensure security
  • asking for the customer’s name helps with personalizing the conversation

Customer inquiry

  • use open-ended questions to gather information on what your customer is looking to buy

Product recommendations

Questions and clarifications

  • let the consumer ask clarifying questions about the products, and give informative and timely responses

Order assistance

  • guide the customers through the order process, when they are ready to make a purchase

Customization or personalization

  • if possible, offer shoppers the option to customize and personalize their order

Payment and billing information

  • ensure transparency regarding pricing, taxes, and shipping costs, then assist the shopper in providing payment and billing details securely

Confirmation and order summary

  • recap the client’s order, and request them to confirm that all the information is valid

Additional services or upselling

  • offer related services, accessories, opportunities to upsell

Post-purchase chitchat – delivery and shipping information, support and assistance

  • provide information on shipping options, delivery times, and tracking details, and offer post-purchase support (returns, exchanges, contact information for customer support)
woman chatting with ai

4. Implement and train your AI-powered chatbot

For this to work, you’ll need to choose a conversational commerce platform that offers chatbot capabilities. These platforms often provide easy-to-use tools and integrations to build and deploy your chatbot.

Once you have selected a platform, you can start training your chatbot using natural language processing (NLP) and machine learning (ML) techniques. NLP allows the chatbot to understand and interpret user messages, while ML helps the chatbot learn from past interactions to improve its responses over time.

Additionally, sentiment analysis can be incorporated into the chatbot to understand the emotional tone of customer messages. This allows the chatbot to provide more empathetic and personalized responses, ultimately leading to better customer service.


These AI chatbots act as virtual shopping assistants and with sufficient training, they can replicate the feel of interacting with a store associate, being available 24/7 to answer questions, suggest choices, and guide customers to decisions based on their personal wants and needs.

5. Monitor and adjust relevant KPIs

Businesses that implement any form of chat commerce, require a thorough understanding of the key performance indicators (KPIs). By tracking specific metrics, businesses can gain valuable insights into customer engagement, conversion rate, order value, customer satisfaction, and abandoned cart rate.

Customer engagement measures the level of interaction and involvement customers have with chatbots or customer service representatives. Monitoring the number of conversations initiated, response times, and the overall duration of customer conversations can provide insights into the quality of the customer experience.

Conversion rate plays a significant role in determining the success of conversational commerce. Tracking the percentage of customer interactions that result in a purchase can help identify any bottlenecks or issues in the buying process. By analyzing conversion rates, businesses can optimize their strategies to drive more conversions and increase revenue.

Order value is another important KPI to monitor. It measures the average value of orders made through conversational commerce channels. By analyzing order values, businesses can identify opportunities for upselling and cross-selling to increase average order sizes.

Overall customer satisfaction is a crucial metric for assessing the effectiveness of conversational commerce. Monitoring customer feedback, ratings, or surveys after interactions can provide insights into the quality of customer service and identify areas for improvement.

Finally, tracking the abandoned cart rate is essential in understanding customer behavior and optimizing the shopping experience. By monitoring the percentage of customers who abandon their shopping carts, businesses can identify any pain points or barriers in the purchasing process and take action to improve it.

Wrap Up

Conversational or chat commerce has emerged as a powerful tool for customer engagement in the digital era. It’s a growing trend offering a more interactive and efficient way for businesses to engage with shoppers and drive sales.

Besides granting convenience to shoppers, the data-based personalized product recommendations and the 24/7 availability coming hand-in-hand with chat commerce are amongst the most attractive features for shoppers.

While automation can streamline processes and scale customer service, it is crucial to not lose the personal touch that human agents provide. Striking the right balance ensures that businesses can provide assistance while efficiently handling customer queries.

The effectiveness of chat commerce largely depends on how well businesses address the pros and cons to create a seamless and secure user experience.

Paige TyrrellHead of Marketing – Prefixbox

Paige is the Head of Marketing at Prefixbox, a leading eCommerce site search solution. She’s an American who’s been living in Budapest since 2017 and loves giving #alwayslearning sessions to help people optimize their online stores.

Conversational Commerce Use Cases

Conversational Commerce Use Cases

Generative AI and chatbot technologies are revolutionizing the way businesses and shoppers communicate and are shaping the future of retail before our eyes.

In this article, we discuss:

  • Use cases for conversational commerce
  • Benefits
  • Real-world examples

Brief Introduction to Conversational Commerce

Before exploring the benefits of conversational commerce, we must understand what it is and it’s importance in Ecommerce.

Defining Conversational Commerce

Conversational Commerce enables online shoppers to communicate with their favorite brands through their platform of choice. By opening a messaging app and starting a conversation with a chatbot, shoppers can easily purchase items, receive immediate customer support, and view recommendations tailored to them.

Conversational commerce meets shoppers wherever they are and provides them with what they need. When done effectively, conversational commerce enhances the user experience, builds brand trust, and increases revenue.

In short, it’s essential to an online business’s success. Statista expects global spending on conversational commerce channels to reach almost 300 billion USD by 2025.

Advantages of Conversational Commerce in Retail

Conversational commerce empowers businesses to foster meaningful connections with customers. Integrating AI-powered chatbots into online platforms enables stores to interact with shoppers in real-time. Thus, shoppers can easily access information and quickly make purchases with confidence.

By implementing conversational commerce, retailers can improve customer satisfaction, build trust, generate more sales, and stand out from competitors.

Enhancing the Customer Experience

By AI, retailers can use conversational commerce to provide an offline shopping journey online by mimicking the retail assistant’s behavior.

Chatbots and Virtual Shopping Assistants

First, let’s review what chatbots and virtual shopping assistants do. Chatbots and virtual shopping assistants offer support designed to mimic human interaction. They leverage NLP to understand user requests and return intuitive responses that go beyond the scope of pre-programmed replies.

Image by storyset on Freepik

By understanding context and subtle language nuances to provide tailored recommendations, virtual shopping assistants act like knowledgeable human salespeople.

They can answer questions, suggest additional products, and provide real-time product information, pricing, and availability instantly.

There are countless ways conversational commerce enhances the online shopping experience, all of which revolve around real-time interactions that lead to satisfied customers who feel understood and valued.

According to an eMarketer study in 2022, it was found that 53% of the people surveyed in the United States had interacted with an AI chatbot within the previous year.

Product Discovery

AI powered chatbots can help shoppers find the products they’re looking for by understanding natural language and context of shopper queries.

They can make relevant recommendations to help shoppers complete their order and can leverage advanced filtering options to guide shoppers through product catalogs.


Personalized Product Recommendations

By analyzing user behavior, preferences, and needs, chatbots can deepen customer understanding beyond Autocomplete searches, and provide personalized replies and tailored recommendations.

Personalized product recommendations help shoppers quickly find what they’re looking to buy, round out their purchases with complementary items, and inspire product discovery in areas of your catalog relevant to them. They make shoppers feel understood and help them navigate the shopping journey conveniently and efficiently.

McKinsey found that over 70% of consumers already expect personalization when visiting an E-commerce store.

Real-time Order Tracking and Support

Chatbots enable shoppers to track orders in real time, which helps retailers build trust by eliminating uncertainty and offering transparency in the shipping process.

Plus, retailers can offer proactive communication via automated updates and notifications about a delivery. This keeps shoppers in the loop every step of the way.

Ensuring chatbots are attentive and engaging helps manage shoppers’ expectations and reduce frustration, which increases customer satisfaction and loyalty.

Instant Customer Feedback Collection

Chatbots give shoppers a voice.

Instant feedback helps online retailers solve problems that may arise during the shopping process. They also help retailers discover pain points, which is insightful data that be used to optimize the chatbots. Ecommerce businesses can leverage feedback to fine-tune product recommendations, improve the user experience, and enhance customer support.

Image by storyset on Freepik

Collecting feedback helps customers feel like their opinion matters, increases engagement through collaboration, and results in a more satisfying shopping experience.

Sales and Marketing Optimization

Conversational commerce is a powerful tool that can be used to optimize sales and marketing efforts.

Let’s explore how.

Chatbot-Powered Sales Funnels

Chatbots are revolutionizing sales funnels. They’re a cost-effective way to generate leads, increase customer engagement, and offer real-time support.

Customer Engagement: Chatbots offer shoppers the ability to quickly navigate the shopping journey by providing personalized recommendations and support. These interactive conversations can guide shoppers through the sales funnel. By addressing users’ individual interests and needs, chatbots keep shoppers engaged and satisfied.

24/7 Support: Chatbots offer real-time support for common queries at any time of day. By providing instant responses, chatbots keep shoppers satisfied while freeing up human support for more complex requests.

Chatbots automate many parts of the sales process and are reshaping the sales landscape as we know it.

Their ability to leverage data and continuously improve helps sales teams promptly and effectively streamline the sales process and drive significant revenue.

Upselling and Cross-selling Strategies

Many shoppers use chatbots to find products they want to purchase. By analyzing user history, purchase behavior, and preferences, chatbots can identify opportunities to cross-sell and upsell.

The most effective way to do this is to offer recommendations that help shoppers discover relevant products. Personalized recommendations that align with what they’re looking for, upgrades, or complementary items that help complete their purchase are proven to increase conversion rate. Additionally, retailers can use chatbots to promote sales, discounts, or items that further support their bottom line.

Product recommendations increase conversion rate, average order value, and revenue. If you’re not using chatbots to upsell and cross-sell, you’re leaving money on the table.

To make sure your strategy is helping achieve your desired results with customer support, we recommend setting and tracking the relevant Ecommerce KPIs.

Interactive Promotions

Interactive promotions alert shoppers to deals, discounts, and promotions that encourage them to buy. They are a lucrative tool for increasing customer engagement, optimizing conversion rate, driving customer loyalty and retention, and helping your brand stand out.

Promoting personalized sales through chatbots or Ecommerce Merchandising is a proactive way to increase customer engagement. Helping shoppers find suitable deals will help you strengthen relationships with customers, create positive user experiences, and build sustainable sales success.

Streamlined Customer Support

Conversational commerce offers real-time communication, which is extremely powerful for customer support. The moment shoppers have a question or concern, they can get the answer they’re looking for, quickly absolve their frustration, and stay satisfied.

Here are a few ways chatbots can improve the customer support process.

AI-Driven Chatbot Assistance

Chatbots can be programmed to answer most inquiries immediately. By automating routine answers and offering personalized 24/7 support, online retailers can reduce wait times, and keep shoppers informed.

Answering support questions quickly and accurately helps build trust, increases customer loyalty, and inspires return visits.

Escalation to Human Agents

If automated replies don’t provide the information shoppers want, chatbots can pass them on to human agents. Human agents can streamline the support process by ensuring that more complex inquiries are handled with the proper care and attention.

Offering human support when needed will ensure shoppers get accurate information regarding their requests. Implementing human support in your conversational commerce strategy will resolve queries faster and improve overall customer satisfaction.

Post-Purchase Support and Returns Management

Chatbots and virtual assistants offer a wide range of post-purchase support. They can provide order information like tracking number or delivery status as well as resolve issues that may arise.

Chatbots can help address modifications to an order, concerns with shipping, and help shoppers with returns. Offering instructions, providing return labels, and passing shoppers onto human customer support ease the post-purchase process.

Plus, chatbots can offer post-purchase recommendations too. If a shopper isn’t happy with a purchase, chatbots can provide suggestions for alternative products based on their return.

Multichannel Communication

Conversational commerce increases online retailers reach by enabling customers to engage with them at various touch points through their preferred communication channels.

Offering real-time interactions across many channels helps meet users where they are, facilitates convenient communication, and maximizes potential for customer engagement and sales.

Here are a few common communication channels.

Social Media Messaging Platforms

Over 4.7 billion people use social media, with the average person spending two and a half hours daily on their preferred platform. So, it only makes sense that online retailers incorporate social media into their conversational commerce strategy.

Image by storyset on Freepik

By offering real-time communication via social media, shoppers can engage with their favorite businesses, explore products, request support, and make a purchase- all within their platform of choice.

Social media integration increases online retailers’ reach and promotes seamless interactions with shoppers by making it easy to communicate through their platform of choice.

SMS Integration

Shoppers can communicate with their favorite businesses via SMS (Short Message Service) too. Instead of navigating to an online store’s site, shoppers can quickly message retailers using the native messaging app on their mobile devices.

With a simple text message, users can receive updates on their orders, view promotions or discounts for products they’re interested in, ask for customer support, and more. Implementing SMS into your conversational commerce strategy is an effective way to offer convenient assistance and enhance the overall perception of your brand.

In-App and On-Site Messaging

While it can be easier for shoppers to communicate with online retailers through their preferred apps, it is crucial to offer chatbots and virtual assistants to shoppers on websites and in apps too.

As users navigate your online store, chatbots can analyze shopping behavior and prompt conversations or answer questions at important touchpoints. Chatbots can answer questions about products, offer personalized recommendations, and answer support questions all from the store’s website or app.

In-Store Retail Applications

Most conversational commerce communication is designed to take place virtually, without the need for a physical storefront. However, chatbots and virtual assistants can be used to enhance the in-store shopping experience as well. Take a look.

5 Examples of Successful Conversational Commerce

Successful conversational commerce use cases keep shoppers engaged and informed at key touch points throughout the shopping journey.

Let’s look at how online retailers have successfully implemented conversational commerce in their stores.

1. Dollar Shave Club

Dollar Shave Club’s chatbot is simple. Shoppers receive 24/7 support by selecting a common support topic about order status, products, and sign-up questions, or they can ask a question.

By providing real-time support, Dollar Shave Club ensures customers receive fast answers to their questions. If the chatbot doesn’t have the answer shoppers need, they do a great job passing them on to human support. Take a look.

Keeping shoppers informed and ensuring they receive the exact support they’re looking for improves the shopping experience and creates a positive impression of your brand.

2. Lego

Lego’s chatbots do a great job of building customer trust from the get-go. They start by ensuring users their data is protected, then ask for a first name to personalize the experience. Plus, they ask for an email address in case follow-up is required later.

You’ll notice their chatbot has a name too. These small details go a long way in creating interactions that feel natural, authentic, and tailored to each shopper.

3. HM

One thing H&M’s chatbots do exceptionally well is ask for customer feedback after every interaction.

Asking users if their query was solved, how satisfied they were with the interaction, and how accurately the chatbot understood what they were looking for is the best way to discover what’s working well and where there is room for improvement.

Chatbots rely on generative AI and are designed to get better over time. Directly asking shoppers for feedback can help streamline this process and continuously optimize chatbots for the best possible user experience.

4. Clinique

Clinique is a prime example of how chatbots can work in conjunction with human agents. They offer support on a handful of predetermined topics or immediately connect you to a live agent.

If a shopper is looking for a product, Clinique’s agents ask questions to personalize their recommendation. Look how efficiently and effectively they help shoppers find what they’re looking for.

Plus, they make it easy to add recommended products to shopping carts and keep you engaged by offering relevant discounts and promotions. This shopper-first approach is an effective way to shorten the path to purchase, build customer loyalty, and drive sales.

5. 1-800-FLOWERS

The 1-800-Flowers chatbot does an excellent job guiding users through the shopping journey.

Shoppers can give the intended recipient’s name and address, explore flowers that fit a specific occasion, and quickly navigate the check-out process- all with help from the chatbot.

One of the best parts about this chatbot is that it offers images of relevant flowers and bouquets to help shoppers narrow down their search. This is a convenient way for shoppers to view the different arrangements offered so they can make confident purchase decisions.

The conversational commerce approaches and techniques mentioned above highlight some of what’s possible with chatbots and virtual assistants. However, keep in mind that customers’ needs vary from industry to industry. When implementing a chatbot in your store, you must understand your specific shoppers so you can program your chatbot accordingly.


Conversational Commerce is a game-changer. By leveraging chatbots and virtual assistants, retailers can meet customers where they are and engage with them in real-time. This enhances the user experience, optimizes sales and marketing efforts, and streamlines customer support.

Many online businesses are already using conversational commerce. However, advances in conversational AI are transforming the Ecommerce industry, reshaping what’s possible, and creating new opportunities for retailers.

If you aren’t already implementing conversational commerce into your Ecommerce strategy, the time to start is now.


How can conversational commerce impact my online retail business?

Conversational commerce significantly impacts retail business in many ways. By providing personalized and interactive communication with customers in real-time, retailers can increase engagement and offer a more satisfying shopping experience.

One way to increase engagement is by offering personalized responses and product recommendations on customers’ preferred channels. By showing shoppers they understand them and can meet their needs, retailers can develop stronger relationships and drive more sales.

Additionally, chatbots provide automated customer support, which helps retailers cut costs on overhead (think physical storefronts, staff, etc.). Delivering a seamless multi-channel Ecommerce experience to shoppers can improve customer satisfaction and helps maximize overall business growth.

What are the risks and challenges of implementing conversational commerce?

There are many advantages to conversational commerce, but there are risks and challenges businesses must consider too. It’s important to understand that the lack of human support may hinder the customer journey for certain shoppers. This is largely because chatbots and artificial intelligence algorithms struggle to understand shoppers’ inquiries, which can result in irrelevant or non-useful communication. The best way to prevent this happening is to implement algorithms and machine learning for Ecommerce specifically.

Privacy and security concerns are prominent too. Customers may fear sharing sensitive data like their address or credit card information with a chatbot or virtual assistant. Lastly, the integration process can present problems for Ecommerce sites as well. That said, online businesses can help prevent or mitigate these problems by continuously testing, monitoring, and optimizing their solutions.

How can I ensure my customers have a positive experience with conversational commerce?

The best way to create a positive experience with conversational commerce is by providing clear communication, personalized services, and proactive assistance. Offering convenient, immediate, and relevant answers to shoppers’ inquiries will help build brand trust and a positive impression of your store. It is also important to ask for feedback to continually improve the user experience.

On the technical side, finding conversational chat platforms that integrates seamlessly across all channels will help you maintain a consistent shopping experience. Lastly, make sure to inform shoppers about the security and privacy measures your store takes to protect their data. Each of these steps will help enhance the customer journey with conversational commerce.

Paige TyrrellHead of Marketing – Prefixbox

Paige is the Head of Marketing at Prefixbox, a leading eCommerce site search solution. She’s an American who’s been living in Budapest since 2017 and loves giving #alwayslearning sessions to help people optimize their online stores.

What is Conversational Commerce?

What is Conversational Commerce?

Imagine communicating with your favorite brands anytime without needing to go to a physical store, wait in line, or spend hours on hold.

This is the future of Ecommerce, and it has a name: conversational commerce.

In this article, we discuss:

  • What conversational commerce is
  • Benefits
  • Best practices

The conversational commerce market is set to grow by $290 billion by 2025, which means the time to start developing your strategy is now.

What is Conversational Commerce?

Conversational commerce is a new channel that enables retailers to interact with customers online, most commonly through messaging platforms, chatbots, and virtual assistants.

Instead of navigating to online retailers’ sites, shoppers can interact with businesses on their preferred social channels (think: Facebook Messenger) and get an immediate answer.

With conversational commerce, shoppers can ask questions, view product recommendations, request support, or purchase products with fast and personalized communication.

Users can open a mobile messaging app like WhatsApp or Facebook, ask an online retailer for wireless headphone recommendations, view relevant products, and immediately purchase what they’re looking for without navigating to the online store.

With advances in conversational AI, shoppers’ queries can be accurately understood, making communication more effective and authentic. 

The Evolution of Conversational Commerce

The modern evolution of technology shows that consumers have consistently opted for convenience. When Apple introduced the iPhone in 2007, mobile devices quickly outperformed sales of desktop computers for one simple reason: users could access whatever they needed, when, how, and where they wanted it.

mobile and pc sales worldwide chart

Shortly after the iPhone was introduced, messaging apps like WhatsApp and Facebook Messenger gained popularity, and conversational commerce emerged. Online businesses used Facebook Messenger and other apps to interact with customers via chatbots, which sparked a new era of sales and customer care.

WeChat paved the way too, offering a wide array of Ecommerce services and customer support within their application’s ecosystem. The popular Chinese messaging app made it easy for users to make purchases, book taxis, and pay bills all within the app. WeChat’s success inspired other messaging platforms to develop and offer a multitude of features merging Ecommerce and customer communication.

It didn’t take long for businesses to see the lucrative potential of conversational commerce, with numerous companies exploring new ways to increase sales and the customer support experience. Many initial chatbots and virtual assistants were not intuitive enough to provide the support customers were looking for. However, as technology improved, things changed.

With the introduction of generative AI and advances in Natural Language Processing, chatbots can now understand and respond to complex requests authentically.

Amazon Alexa and Google Assistant are two key examples of success with conversational commerce – both devices help users engage with brands using voice commands and quickly make desired purchases.

Conversational commerce is improving and demand is growing, proving it’s here to stay. With the market set to grow by $290 billion by 2025, Ecommerce chat apps and conversational services will likely become an integral part of our lives before we know it.

Why is Conversational Commerce Important?

Conversational Commerce is a powerful tool that enables online retailers to interact with their customers exactly where they are.

By being present in the same channels their customers regularly use, brands can make themselves more accessible and develop a new sales channel: an online chat shop.

With 73% of shoppers saying the customer experience is a deciding factor in the purchase process, conversational commerce is more than important – it’s crucial.


Customers can communicate with businesses via messaging platforms, chatbots, and virtual assistants 24/7. They can ask questions, purchase items, see personalized recommendations, or receive customer support when they want it – all within their preferred channel.


Thanks to AI and machine learning for Ecommerce, businesses can provide personalized recommendations based on customers’ preferences, user history, and individual needs. Individualized messages, promotions, and support help create an engaging online experience that increases customer retention.


With chatbots, virtual assistants, and messaging apps, businesses can offer shoppers immediate assistance. Chatbots are adept at executing routine requests like processing orders or answering FAQs, which saves customers time and reduces costs by up to 30%. Nearly 80% of inquiries can be answered by a chatbot.

By reducing the need for human interaction, conversational commerce benefits shoppers and retailers. It allows retailers to meet customer expectations and build stronger relationships efficiently and effectively.

Popular Channels for Conversational Commerce

Businesses can engage in conversations with customers using several different messaging channels, chat platforms, and conversational technologies. Here are the most common types.

Social Messaging Apps

The key to a successful conversational commerce experience is convenience. Social messaging apps are one of the most convenient ways for shoppers to interact with your store because they are already an essential part of our daily lives.

Image by storyset on Freepik

Customers can use apps like WhatsApp or Facebook Messenger to get automatic answers to their questions. They can also receive customer support, explore relevant product recommendations, and navigate the shopping process from search to completed transaction.

If an avid runner needs new shoes, they can open their preferred social messaging app on their phone, message a store, explore personalized recommendations, and purchase a new pair of shoes in minutes.

Alternatively, if an item isn’t delivered on time, customers can quickly learn why on their messaging app of choice.

Statista estimates that 60% of global E-commerce sales are already happening on mobile in 2023, generating almost 2,200 billion USD.

Messaging apps generally consist of a combination of chatbots and live human agents. Chatbots handle most inquiries and can pass a customer on to receive more personalized human assistance when required. This approach to social shopping cuts customer service costs and ensures shoppers receive the stellar customer support they need.


Chatbots leverage natural language processing to understand user intent and stimulate authentic human conversation in an instant. Advances in generative AI have made it possible for chatbots to understand complex requests, provide answers to user queries, offer 24/7 customer care, and guide users through the shopping journey.

There are two main types of chatbots. Rule-based chatbots follow a set of predetermined rules to respond to customer questions. AI-powered chatbots are more complex, leveraging machine learning algorithms to understand user intent and improve replies over time.

In addition to handling the majority of user requests, chatbots can generate significant Ecommerce revenue for businesses. By seamlessly highlighting relevant promotions, offering personalized product recommendations, and collecting user feedback, chatbots successfully drive sales.

Voice Assistants

Voice chats are a powerful way to improve customer interactions. Apple’s Siri, Amazon Alexa, and Google Assistant are the most popular voice search assistants on the market.

Image by storyset on Freepik

Like other conversational commerce tools, voice assistants help with product discovery, provide information, assist with purchases, and offer customer support.

By integrating voice assistants with additional technology like NLP or sentiment analysis, E-commerce brands can create advanced customer conversations.

Modern voice technology can determine a user’s mood by analyzing their tone of voice and returning responses accordingly.

Digital voice assistants help E-commerce websites further create convenient, personalized shopping experiences by making it easy for users to navigate the purchase journey without needing to type or research what they’re looking for.

Conversational commerce is all about keeping customers’ best interests in mind. As technology continues to evolve, new platforms and channels are sure to surface.

Conversational Commerce Use Cases

The conversational commerce landscape is rapidly growing, evolving, and opening up an entirely new avenue for sales.

Chatbots function as “chat shops,” where shoppers can conveniently navigate the shopping journey through conversation.

Let’s explore two most common, beneficial, and lucrative use cases for conversational commerce: product discovery and customer support.

Improving Product Discovery

Most conversational commerce platforms leverage NLP (natural language processing) to understand user intent. Therefore, shoppers can ask for the products they want however feels natural to them and instantly see relevant results.

By collecting and analyzing user behavior data and interactions, Ecommerce retailers can better understand what shoppers are looking for and effectively tailor a wide range of product recommendations to meet their needs.

Let’s explore how data-driven product recommendations can improve the shopping experience and drive sales.

Showcase Relevant Products

With chatbots or other conversational support offerings, shoppers can state their preferences and quickly explore relevant products for any query.

If a user wants to buy a pair of running shoes but is undecided on brand or style, they can simply tell the chatbot what they’re looking for, their size and color preferences, and explore the most relevant items.

Even more impressive is that chatbots understand colloquial language and detailed queries that could never fit in a search box.

If a shopper types, “Show me a laptop good for gaming that” then specifies “that are easy to carry in my backpack,” chatbots can immediately present the most relevant options.

In addition to helping shoppers feel understood by intuitively responding with relevant products, chatbots can shorten the path to purchase by presenting products shoppers are most likely looking for.


Upsell and Cross-Sell with Product Recommendations

Chatbots are a valuable tool for upselling and cross-selling.

If a shopper is looking for a laptop, chatbots can be programmed with Ecommerce merchandizing capabilities to recommend specific brands or popular models.

Additionally, if a shopper purchases a laptop, chatbots can recommend complementary or additional products like a computer mouse or earphones to round out their purchase.

Provide Product Information

Shoppers often need product information before making a purchase. Users may be interested in sizing information, pricing, discounts, product reviews, or return status. Chatbots streamline the search experience by providing responses instantly.

Keep in mind, just like with Ecommerce search result page design, the product information must be presented in clear and easy-to-understand ways that guide customers through the purchase journey.

Customer Support

In the digital age, shoppers expect to have their needs met immediately. If they don’t find the products or information they’re looking for, they’ll leave your store and head to a competing site.

Chatbots and virtual assistants can improve customer relationships with people by understanding their concerns and providing real-time customer feedback. Let’s look at a few ways chatbots can assist with customer support.

According to a research by Facebook, two-third of users would prefer using a chat app than calling customer service.

1st Line Customer Support

Chatbots understand customers’ questions and immediately respond with answers from your knowledge base. In addition to alleviating frustration and creating a quick user experience in your store, automating support with chatbots saves Ecommerce businesses money and resources because it prevents the need for human interaction.

Connect to Live Support Agents

While chatbots can effectively handle a large number of inquiries, AI-driven conversations are not capable of doing everything.

When online or mobile users need additional support, they can be seamlessly connected to live chat agents on the customer service team.

Having company representatives provide personalized support for necessary requests will help shoppers feel cared for and resolve their issues more efficiently.

Track Deliveries

Chat commerce enables shoppers to communicate in real-time, making it easy for them to inquire about the delivery status of their purchase and receive an immediate answer.

By providing instant notifications, updates, and instant answers to customer concerns, conversational commerce is a powerful way to meet customer demands, reduce frustration, and improve the tracking experience.

How Ecommerce Retailers are Using Conversational Commerce

More and more retailers are adopting conversational commerce in the E-Commerce space. Companies like H&M, Burberry, and American Eagle Outfitters offer chatbots to help their user base find products, offer styling advice, and provide special care on different platforms.

Retailers using conversational commerce illustration

While conversational commerce has been prevalent in the online retail industry, companies have only cracked the surface of what’s now possible with generative AI. Advances in technology have made it possible for online retailers to better understand customer support requests, provide more personalized interactions, improve customer engagement, and increase online sales.

Let’s take a closer look at some of these benefits.

Advantages of Conversational Commerce in Ecommerce

Conversational commerce benefits shoppers and online retailers by offering on-demand support without traditional overhead costs.

Businesses that utilize online messaging platforms, chatbots, and virtual assistants to interact with users improve the customer experience, drive sales, and create significant business impact.

Let’s take a look at a few key benefits.

Improved Customer Engagement

Conversational commerce enables businesses to interact with potential customers on demand. Providing personalized communication efforts to shoppers exactly when and where they want them can help businesses build trust and inspire loyalty.  Helpshift found that 83% of customers would contact a brand messaging service if the response there is immediate.

Chatbots can accurately respond to routine customer queries, suggest relevant products that shorten the path to purchase, and offer human-like correspondence that keeps users engaged, satisfied, and coming back for more.

Furthermore, chatbots can offer exclusive discounts and promotions. Targeting deals and offers to individual customers creates a sense of urgency, engages shoppers, and encourages them to purchase.

These interactive experiences help users seamlessly navigate the shopping journey from start to finish and inspire them to return for repeat purchases.

Higher Conversion Rates

By leveraging AI and machine learning algorithms, businesses can understand user intent and accurately provide shoppers with the products, information, and support they need to make confident purchases.

Offering data-based recommendations via conversational commerce effectively inspires catalog discovery, helps you hit key Ecommerce KPIs, and builds loyal customers.

If a shopper wants to buy a laptop on a budget, a virtual assistant can provide recommendations and answer questions about product specifications like size or hard drive space.

By ensuring easy conversation with customers and offering the information they need to make a confident purchase, Ecommerce businesses can achieve a rise in conversion rate, customer satisfaction, and online revenue.


Conversational commerce is conducted online, which reduces the need for overhead costs like physical storefronts and employees.

Conversational commerce leverages automation, enabling businesses to answer frequently asked questions and perform routine tasks without physical labor. Automating support and the sales process saves time and resources when handling orders or inquiries.

Additionally, chatbots and virtual assistants can handle high volumes of customer requests at once, making it easy for businesses to scale up or down depending on demand.

Personalized Experiences for Customers

Personalizing the shopping experience shows shoppers you understand them and can meet their needs.

Chatbots use data mining and machine learning to analyze patterns in user behavior and make tailored recommendations that align with their preferences.

Leveraging AI to predict what customers need is an effective way to help shoppers find what they’re looking for and help guide them through the purchase journey.

Chatbots can also send personalized messages and updates to customers. Welcome messages, order confirmations, and shipping updates via chatbots help shoppers stay up to date with previous purchases and engaged as they navigate your site.

As technology continues to evolve, chatbots are getting better at interacting with customers and understanding what they’re looking for. Nowadays, chatbots for Ecommerce fashion stores can ask shoppers about their style preferences, analyze thousands of products in a catalogue, and suggest clothing that aligns with their tastes.

Studies found that 80% of consumers were more likely to make purchases when getting personalized offers.

And it’s not just the E-commerce market. These advanced communication methods are transforming the hospitality industry, the banking industry, and so many more. 

Valuable User Behavior Data

Conversational commerce provides online retailers valuable insights into user behavior and preferences, which can improve personalization efforts, products, and other services.

Data can be collected in a variety of ways.

Machine learning algorithms collect and analyze user behavior data, which improves product recommendations and tailored customer service efforts.

Messaging platforms store chat logs of interactions between chatbots and customers, which offer insightful information about customer preferences, behavior, and common pain points.

Chatbots can be programmed to request feedback from users after an interaction. This information can help gauge customer satisfaction and address room for improvement for the chatbot.

Conversational commerce platforms track user demographics and shoppers’ purchase history, which is useful in offering data-driven recommendations and discounts.

By collecting data at all phases of the online shopping journey, Ecommerce businesses can identify room for improvement and make optimizations for increased customer satisfaction and sales.

Reduced Abandoned Carts

As the Ecommerce industry continues growing, so does the shopping cart abandonment rate. About 70% of online shoppers add products to their cart via autocomplete search or along the customer journey and leave the store without purchasing them. However, conversational commerce can help mitigate the problem.

If a shopper is on the verge of abandoning their cart, chatbots and virtual assistants can intervene.

Proactive customer engagement like reaching out to customers with carefully crafted messages can increase the chances of a customer completing their purchase.

Furthermore, AI-based conversational commerce chatbots enable shoppers to purchase their items directly in the conversation window. Streamlining the shopping journey to prevent shoppers visiting another page can help reduce the abandoned cart rate and keep businesses ahead of the curve.

5 Conversational Commerce Best Practices

While implementing conversational platforms into your Ecommerce strategy is crucial, it’s important to keep the following best practices in mind to maximize its potential.

1. Prioritize the Customer Experience

The goal of conversational commerce is to improve the customer experience. In addition to implementing site search best practices in your store, one of the most effective ways to prioritize customers is by creating convenient shopping experiences.

Make sure you put what customers need at their fingertips.

The best way to prioritize customers is by leveraging data like demographics, browsing behavior, and purchase history to inform targeted response algorithms and return relevant results.

Data-driven responses that improve over time to accurately address shoppers’ questions and help them explore relevant products will ensure your conversational commerce solution is convenient, engaging, and creating customer satisfaction.

2. Use a Conversational Approach

Simply integrating a chatbot into your online store and app messaging will not suffice. You must establish rules and guidelines for chatbot responses to create a consistent, reliable, and quality experience. The same applies to voice assistant interactions; communication must feel natural.

The best way to create authentic communication is to keep the customer in mind. Take advantage of key user touch points and offer personalized interactions throughout the most crucial stages of the purchasing journey. Carefully planning your conversational commerce strategy will help ensure you create an engaging experience with a personal touch.

A Forrester and Google joint research found that 68% of shoppers are more likely to buy from businesses that offer convenient communication ways.

3. Monitor, Test, and Refine Your Conversational Experience

AI-driven conversations are not a set-it-and-forget solution. You must consistently ensure your chatbots are responsive and effective. This will help you provide shoppers with the best possible experience.

To monitor performance, identify your specific goals and track the right metrics. A few insightful metrics are conversion rate, customer satisfaction ratings, and response time. These key metrics will help you identify room for improvement and make adjustments where necessary.

It’s also a good idea to test messaging strategies and tools to get an accurate idea of what keeps shoppers engaged and drives sales. Consistently monitor results and optimize your solution to get the most out of your conversational commerce efforts.

4. Provide Valuable and Relevant Information

Customers trust that information provided through conversational commerce channels is relevant and accurate. Therefore, all interactions, answers, and assistance must align with what shoppers want. If users ask for headphone recommendations and see suggestions for computer mice, they will likely grow frustrated, lose trust in your brand, and not return to your store.

Leverage user behavior data to provide relevant and accurate responses. When shoppers receive factual information that guides them seamlessly through the purchase process, this creates a positive impression of your store and inspires repeat business.

To ensure chatbots and virtual assistants return relevant results, track analytics and monitor performance data. This will show you what’s keeping shoppers engaged and where there’s room for improvement.

Furthermore, the conversational nature of chatbots makes it easy to ask for user feedback. Program your chatbot to ask users if their query was addressed properly with a simple thumbs-up or thumbs-down button. Directly asking for feedback will help you see if shoppers find their interactions valuable and relevant and help you discover room for improvement if necessary.

5. Maintain a Human Touch

While chatbot responses are automated, it is crucial that interactions feel authentic and personal. Even if shoppers ask general questions or perform routine actions, communication shouldn’t feel robotic or impersonal.

Create natural-feeling interactions by using a conversational tone. Refer to customers by name and incorporate personality and your brand identity into your messaging so your chatbot feels like a natural extension of your store.

Make sure your chatbots respond promptly, too. Answering inquiries in a timely matter will show you value customers’ time and help build trust.

Lastly, keep in mind that chatbots need an abundance of data to be most effective. When first implementing conversational chatbots into your conversational commerce strategy, it’s best to run a co-pilot scenario with a human that can review replies. Having humans monitor chatbot interactions during the learning phase will ensure replies accurately address users’ inquiries while feeling authentic and natural. 


Conversational commerce is a powerful tool that helps businesses improve the customer experience and drive sales. By providing personalized, accurate, and timely responses to customer requests, chatbots and other types of conversational commerce can keep shoppers engaged, inspire them to purchase more items, and create a positive impression of your brand.

The most prevalent forms of conversational commerce include chatbots, virtual assistants, voice assistants, and social media platforms. However, rapid advances in artificial intelligence will continue to make conversational commerce even more engaging and effective.

When implementing conversational commerce in your store, make sure to adhere to the best practices, consistently measure performance, and stay on top of growing trends to exceed your shoppers’ expectations and keep your Ecommerce store ahead of its competition.

Paige TyrrellHead of Marketing – Prefixbox

Paige is the Head of Marketing at Prefixbox, a leading eCommerce site search solution. She’s an American who’s been living in Budapest since 2017 and loves giving #alwayslearning sessions to help people optimize their online stores.

The All-Inclusive Guide to AI-Driven Ecommerce Product Recommendations

The All-Inclusive Guide to AI-Driven Ecommerce Product Recommendations

AI-driven Ecommerce product recommendations are everywhere.

They can increase sales and improve the customer experience, which makes them essential to a thriving Ecommerce business.

In this article, we’ll uncover:

  • How AI-driven Product Recommendation Engines work
  • Where to place recommendations in your store
  • Best practices to maximize impact

Let’s jump in.

What are AI-Driven Ecommerce Product Recommendation Engines?

Ecommerce Product Recommendation Engines display relevant product recommendations to shoppers throughout their journey. To do this, AI algorithms identify patterns in customer behavior to place shoppers into groups and automatically recommend products that match their preferences or are similar to what they’re viewing.

Product Recommendation engines that leverage AI to return data-driven results are the best way to help shoppers discover relevant products. This increases engagement, strengthens customer loyalty, and boosts revenue.

Thanks to recent advances in AI and GPT technologies, recommendation engines are becoming faster, more accurate, and more effective. They are a crucial tool for anyone running an online business.

How do AI-Driven Ecommerce Product Recommendations Work?

Ecommerce Product Recommendation Engines use machine learning and advanced AI-based algorithms to collect data, analyze shoppers’ behavior, and return relevant product suggestions.

They recognize shoppers’ habits, preferences, and browsing history and effectively return personalized recommendations for products they want to buy.

We’ve outlined how AI-based recommendation engine technology works to help you use it to your advantage.

Collaborative Filtering

The most common way to personalize recommendations is with collaborative filtering.

Collaborative filtering is a recommendation system that analyzes customer tastes, preferences, and browsing history to predict what they might want to buy next. The logic is simple. If Shopper A and Shopper B like the same product, then Shopper A might be interested in a product Shopper B has previously purchased.

This system identifies meaningful associations between items and users to provide accurate product recommendations for products they may not have sought out.

You need an abundance of user data for this method to be effective. Without sufficient data and rich customer profiles, recommendations may miss the mark and create a poor perception of your Ecommerce business.

There are two types of collaborative filters you should implement in your store. Let’s take a look at them.

User-Based Collaborative Filtering

User-based collaborative filtering analyzes user behavior to identify similar groups of shoppers and recommend products to those with corresponding purchase habits.

As individual customers navigate your store and make purchases, an algorithm collects that data to calculate a similarity score. Customers with matching similarity scores are then grouped together and provided with similar recommendations.

This approach assumes past users with similar preferences can help determine what similar shoppers will want in the future.

By creating rich customer profiles and accounting for changing user behavior, user-based collaborative filtering effectively tailors recommendations that align with shoppers’ tastes and preferences.

Item-Based Collaborative Filtering

Item-based collaborative filtering analyzes the relationship between types of products rather than users. This method identifies products frequently purchased together and groups them accordingly to make recommendations.

For example, in a Consumer Electronics store, this filtering system will recognize that users often buy cell phones and cases together. The next time a shopper searches for a cell phone, they will see a recommendation for the highest-rated phone cases.

Item-based collaborative filtering is most effective in stores with large product catalogs. The more items there are, the easier it is to determine relationships between them to ensure recommendations are relevant and effective.

Content-Based Filtering

Content-based filtering makes recommendations by taking a product’s attributes, related keywords, and categories into consideration. This method uses keyword-based recommendation algorithms to determine which products best suit users based on their previous activity.

For example, in a Health and Beauty store, content-based filters will look at a shopper’s purchase history and identify products with similar ingredients, formulas, and certifications.

Content-based filtering is most effective in stores with rich product attributes listed in their catalogs. This filtering method is an effective way to recommend items that align with shoppers’ preferences while providing insights that help better target ads and promotions in your store.

Hybrid Recommendation Systems

Hybrid Recommendation Systems leverage two or more filtering methods to suggest products that encourage catalog discovery and inspire sales.

For example, online stores can implement both content-based and user-based filtering systems (or any other combination) to provide recommendations to shoppers.

Implementing more than one type of recommendation system in your store is the most effective way to improve recommendation accuracy and relevancy.

There are different ways to approach hybrid recommendation filtering. You can use one of these AI-based recommendation techniques to modify or enhance another or combine the outputs of both filtering systems into one long recommendation list.

Next, let’s take a look at how product recommendations can benefit your store.


Benefits of Ecommerce Product Recommendations

AI-driven product recommendations engines are a powerful tool that offer Ecommerce retailers countless benefits. Here are a few of them.

Better Understand Your Customers

Product Recommendation engines leverage AI and data mining to identify meaningful connections between shoppers and products.

Advanced algorithms collect purchase history, browsing habits, ratings, reviews, search activity, and more to create comprehensive profiles of shoppers and return accurate results.

This invaluable data helps you understand your customers’ preferences and interests, which is key to effectively tailoring store offerings to meet shoppers’ needs.

Improved User Experience

If shoppers can’t quickly find the products they’re looking for, chances are they’ll leave your site and go to a competitor’s.

Providing personalized recommendations that align with shopper intent improves the user experience and keeps visitors engaged. By using AI-based personalization techniques and strategically placing relevant product suggestions throughout your store, retailers can save shoppers time and energy, encourage product discovery, and prevent frustration.

Creating a positive personalized shopping experience that makes customers feel understood will help build trust and inspire them to return.

Higher Customer Engagement

Users have very short attention spans. Placing relevant recommendations at every phase of the shopping journey will catch their attention, keep them engaged, and encourage them to spend more time on your site.

When customers are offered personalized recommendations, they are more likely to return for follow-up visits and less likely to compare prices elsewhere – leading us to our next key benefit.

Increase Average Order Value and Online Revenue

Personalized recommendations have proven to play a significant role in boosting revenue. 

Data-driven recommendations that reflect changing user behavior can alert shoppers to relevant products, deals, and promotions and inspire them to explore your catalog.

When visitors see items tailored to their tastes and preferences, they are more likely to make a purchase.

As you can see, AI-driven product recommendations benefit shoppers and businesses alike.

Next, let’s look at where you should place them for maximum impact.

Strategically Placing Ecommerce Product Recommendations

Recommendations should appear seamlessly in your store to enhance the shopping experience, not overtake it. As shoppers search, browse, and add items to their baskets, recommendation types should meet shoppers where they are on their journey and help guide them through it.

Let’s look at how and where Ecommerce websites should place AI-driven product recommendations to increase engagement and shorten the path to purchase.

Search Engine Results Pages

Over 30% of visitors go directly to the search box upon entering an online store. Therefore, encouraging product discovery via Autocomplete search and on Search Engine Results Pages is lucrative and essential.

When a shopper navigates to a search results page, you can assist with their discovery by placing popular products, complementary products, or related product recommendations below the SERP results.

Keep in mind that good Ecommerce search result page design is crucial. Placing recommendations in a visible location on the search page is the most effective way to increase conversion rate.These items can help shoppers refine search intent, explore similar products, and stay in the purchase flow.


Data-driven recommendations can help kick-start the shopping journey from the get-go.

For first-time shoppers, we suggest showcasing trending, seasonal, discounted, or new products from the biggest brands on your home page. These recommendations can entice first-time shoppers to explore the products you want to promote.

For repeat customers, personalized recommendations that align with their past preferences, browsing history, and purchase history can help them pick up where they left off. They will also show them you understand what they’re looking for.

For example, products a shopper recently viewed or discounted items that match previous user behavior can work wonders. Take a look at how Selsey recommends personalized products on their homepage.

The homepage offers prime recommendation real estate to highlight products, improve the user experience, and boost sales. Be sure to implement some of the practices listed above to maximize your store’s potential.

Category Pages

Category pages showcase the most relevant items within a given product category. If a shopper searches for a microwave in Autocomplete, your recommendation engine should make it easy to navigate to a category page displaying the most popular options in stock.

Placing relevant products, such as a microwave with a grill or new models offered by a well-known brand on a specific category page can help shoppers quickly find items they want and may not have otherwise seen.

Product Detail Pages

Use the space at the bottom of the product page to your advantage.

If a shopper has decided the item they’re reviewing is not for them, you can keep them engaged by showing similar products in your catalog. Or, if they’ve added the item to their cart, you can encourage additional purchases to help them round out their order.

If a visitor is looking at a laptop, recommend other popular models at the bottom of the page. Once they add the laptop to their cart, suggest complementary items like a mouse or keyboard.

Product detail pages are a prime location to keep shoppers engaged, encourage further product discovery, and boost average order value.

Checkout Pages

If a shopper has decided to buy an item in your store, that’s great! But their purchase journey doesn’t have to end there. You can increase average order value by upselling or cross-selling relevant items on the checkout page.

Offering advanced models with a bigger profit margin or data-driven recommendations for frequently purchased together products can help with your bottom line.

Suggesting products you know a shopper will be interested in can inspire last-minute purchases at the most critical decision-making point.

Zero Result Search Pages

Shoppers expect to find desired products immediately. Therefore, unsuccessful product searches are one of the most frustrating experiences users can have in your store. If they land on a zero result research page, you risk losing them to a competitor.

That said, placing recommendations on the zero result pages can help ease the pain. We recommend checking out these no result page examples for Ecommerce and implementing the best practices.

Suggesting products that align with a customer’s intent can show you understand them and make it easy for them to stay in the purchase flow.

404 Pages

404 pages, also known as “error pages” or “page not found” pages, are a bummer that can reflect poorly on your business. Conversely, you can use them to your advantage.

Placing recommendations for popular, discounted, or personalized products on 404 pages can intrigue shoppers and create additional viewing opportunities for a wide range of products.

This will create a seamless shopping experience instead of driving shoppers away.

How Can You Assess If Your Product Recommendation Strategy is Successful?

The best way to measure success is by setting recommendation-specific Ecommerce KPIs. Here are a few examples.

  • Number of product clicks
  • Add to basket actions
  • Product checkouts
  • Unique purchases
  • Product revenue

These metrics are more insightful than measuring conversion rate or average order value and can help you identify if your recommendations are effective. Customer feedback, return visits, and positive reviews can also indicate how shoppers feel about them too.

Keep in mind success is defined differently from company to company. So once you identify what you want to achieve with product recommendations, track the corresponding KPIs and measure them consistently to see if you’re achieving your goals.

6 Strategies to Maximize the Impact of Product Recommendations in Ecommerce

In the highly competitive Ecommerce industry, AI-driven product recommendations have become standard. Providing personalized suggestions enhances the experience in your store, increases the likelihood they’ll become paying customers, and drives customer retention.

However, not all product recommendations are equal.

The following tips and strategies will help you properly leverage recommendations to create a seamless shopping experience, inspire purchases, and boost revenue.

1. Leverage all paths to conversion, not just cross-selling and upselling

Using product recommendations for cross-selling related items and upselling products is an effective way to increase conversion rate, but there are other strategies too.

Offer personalized Ecommerce recommendations. Product suggestions that reflect customers’ browsing history, demographics, location, and previous purchases are more likely to drive clicks.

Don’t undermine the power of social proof. Shoppers are more likely to buy products when they see others have already purchased and liked them. Include social proof in your product recommendations by highlighting good reviews and showcasing trending products.

Recommend related products. If a shopper searches for a sofa bed, recommend the most popular items in stock that align with their initial purchase intent. For example, a u-shaped sofa bed or a corner sofa bed.

Show complementary products. If shoppers search for a video game console, recommend controllers or trending games. Encouraging shoppers to round out their purchases with related items is an effective way to drive conversions and increase average basket size.

Use scarcity. Highlighting limited-time promotions or items running out of stock with recommendations can create a sense of urgency and encourage shoppers to make faster purchase decisions.

Take advantage of E-commerce personalization and all other recommendation opportunities and use cases in your store. This will help you offer a positive customer experience that keeps shoppers coming back for more while improving your bottom line.

2. Ensure personalized product recommendations are data-driven

Recommending any old products to shoppers is not enough. Recommendations should help shoppers continue their journey effectively. One effective way to do this is by creating personalized experiences.

To create a personalized online experience, Ecommerce businesses must invest in the proper technology. AI and machine learning will analyze user behavior data to understand shoppers’ preferences and automatically return accurate product recommendations. 

Recommendations that reflect customer behavior, taste, and purchase patterns are more likely to resonate with shoppers. If you want to increase conversion rate, customer satisfaction, and sales, you need to leverage the right technology to maximize the potential of your personalization efforts.

3. Strategically place product recommendations throughout your store

Item recommendations must be visible to be effective, which means placement is paramount. Offering relevant product suggestions throughout every step of the shopping journey is important. However, you must ensure the right recommendations are in the right places.

Above, we discussed the different areas you can place recommendations in your store. We also highlighted which recommendation types most effectively assist shoppers at different stages in their purchase journey.

For example, related products help shoppers explore other options in your store. It’s best to offer them on the SERP, during the consideration stage where visitors browse products, rather than on a checkout page when they’ve already made a decision.

For checkout pages, complementary product recommendations are the most effective. These will allow shoppers to round out their purchases with items that align with what they’re about to buy.

Recommendations should streamline the shopping process. To create an efficient and enjoyable customer experience, you must place them strategically.

4. Create Category Pages for specific audiences

Category pages for specific audiences are unique landing pages designed for groups of users with similar tastes, interests, and shopping behavior. They help all kinds of customers navigate to the areas of your catalog most relevant to them.

You’re probably familiar with the category pages found in online fashion stores. These stores generally offer pages for men, women, and on-sale items to help shoppers quickly narrow down search intent based on their interests.

You can add more specific category pages too. For example, if someone clicks on the women’s category page in a fashion store, they can further narrow their search intent by clicking on a page for dresses. This page will show the most relevant products in the dress category and should give shoppers the ability to filter results per their desired attributes too.

In addition to being useful, category pages enable you to tailor recommendations, discounts, and promotions to the people most likely to be interested in them.

5. Use merchandizing to your advantage

Merchandizing tools allow you to promote the products you want to sell. For example, you can recommend products on sale, in high demand, or with a high-profit margin to help you improve your bottom line.

For these reasons, we recommend implementing a product recommendation solution with merchandizing capabilities that make it easy to create custom banners and campaigns. Leveraging Ecommerce merchandizing best practices in your recommendation strategy will increase product visibility and inspire shoppers to explore parts of your catalog they might not have been interested in.

Merchandizing and searchandising (search-specific merchandizing) are powerful tools for using product recommendations to your advantage. Just make sure to keep an eye on your inventory and monitor your profit margins to ensure your promotions are financially worth your time and energy.

6. Optimize your recommendations by running A/B tests

Optimization is essential to all recommendation practices. Continuously experimenting with placement, recommendation type, and visual appearance will help you identify what recommendations are engaging your audience and where there’s room for improvement.

Incorporating A/B testing into your recommendation strategy can be time-consuming, especially if you test new ideas frequently. But this optimal approach is worth it. Dedicating the proper time and resources will help ensure your recommendations drive desired business results.

What factors should you consider when choosing a product recommendation solution?

When considering Ecommerce product recommendation vendors, it is important to consider the following criteria.

Choose a data-driven solution

As we mentioned, product recommendations must effectively guide shoppers through your store. Your solution should leverage AI, machine learning, and robust automations capable of analyzing all facets of user behavior. This will best return accurate results that meet visitors’ needs and streamline their shopping journey.

While your Ecommerce product recommendation system project may focus solely on product discovery, the best-known approach is to find an all-in-one enterprise Ecommerce search provider. Finding an AI-driven product recommendation engine is a convenient way to optimize your search and discovery with data-driven results.

Make sure it’s easy to integrate

Before investing in a product recommendation engine for Ecommerce, make sure the solution you’re interested in will integrate with your platform easily. This will save you time and money, create the best possible customer experience, and allow you to scale down the road if necessary.

Ensure recommendation settings are customizable

Every business has different needs. Therefore, your solution should be user-friendly and offer easy-to-fine-tune recommendation settings. A customizable solution will help you tailor suggestions to your shoppers and give you more control.

This is crucial to targeting specific users and customer groups with personalized products or items you want to promote. It will also allow you to adapt to changes in your industry and ensure you’re always working toward your business goals.

Pick a solution that provides detailed analytics

Detailed analytics will show you how customers interact with your recommendations. These invaluable insights will help you identify where to optimize your algorithms to better meet visitors’ needs.

Recommendation engine providers offer different analytics.

Do your research to ensure your solution tracks the metrics you need to continuously improve your solution and stand out in a crowded market.

AI-driven E-commerce Product recommendations are an invaluable tool to optimize the user experience and increase sales. The right recommendation engine can set your store up for success, so be sure to choose one that adheres to the criteria above.


In the current Ecommerce landscape, AI-driven Ecommerce product recommendations are essential.

Product recommendations that leverage artificial intelligence most effectively catch shoppers’ attention and shorten the path to purchase. Therefore, enabling retailers to improve the customer journey, increase conversion rates, boost sales, and build customer loyalty.

The best recommendations are data-driven by a mix of filtering methods to best meet shoppers’ needs at every point in their search. So be sure to invest in the proper technology to provide relevant suggestions in your store.

Implementing a product recommendations solution and adhering to the best practices above will help you maximize your store’s potential and be a win-win for your customers and your business.

Rebecca Pacun
Rebecca PacunCopywriter – Prefixbox

Rebecca is the Copywriter at Prefixbox, a leading Search and Discovery solution for Enterprise Ecommerce retailers. Originally from California, Rebecca works at Prefixbox’s office in Madrid.

25 Essential Ecommerce KPIs to Improve Business Performance

25 Essential Ecommerce KPIs to Improve Business Performance

If you want to improve business performance but don’t know where to begin, Ecommerce KPIs are a great place to start.

Ecommerce KPIs help companies discover room for improvement and determine if they’re progressing toward their goals.

Many KPIs offer insight into different areas of your business, so it’s important to outline your specific objectives when choosing which ones to track.

In this article, we:

  • Explain what KPIs are
  • Discuss how to choose the right KPIs
  • List 25 useful KPIs to maximize business performance

Let’s jump in!


What are Ecommerce KPIs?

Ecommerce KPIs are key performance indicators, quantifiable measurements that indicate business performance. KPIs help track progress in many aspects of your business: sales, marketing, customer service, and more.

Identifying areas for improvement and choosing relevant KPIs is the first step toward achieving your business goals.

Why are Ecommerce KPIs Important?

Ecommerce KPIs show how an online business progresses over time. KPIs are used to set goals, track customer behavior, monitor business performance, and determine progress.

If your online store isn’t performing how you’d like, tracking KPIs can help alert you to the heart of the problem (like these common online shopping problems), so you can take steps to address it.

Discovering pain points and creating KPIs can help your company formulate business strategies and make better decisions.

The Difference Between KPIs and Metrics

Metrics are units of measurement that show overall business health. KPIs are the most relevant metrics.

When a business chooses the right KPIs and tracks them correctly, they receive actionable insight that can inform effective strategies.

If you’re still struggling to differentiate metrics and KPIs, we’ve outlined some of the distinctions.

DIfferences between ecommerce KPIs and metrics

Now that you understand the differences between KPIs and metrics, let’s dive into how you can create them.

How to Create Impactful KPIs

When deciding which KPIs to track, you’ll want to choose metrics that:

  • Provide actionable insight
  • Offer accurate measurements
  • Deliver data instantaneously
Ecommerce KPI examples

These attributes will show if your day-to-day decisions and operations are effectively helping achieve your objectives.

That said, numerous KPIs check these boxes.

So, how do you know which KPIs are best for your Ecommerce business? Follow these steps to identify the ones that work for you.

Pinpoint Room for Improvement

To find the right KPIs, you should first decide which part of your business you want to improve.

Here are some examples:

  • Sales
  • Marketing
  • Store Performance
  • Customer Service

If the suggestions above don’t align with your specific goals, don’t worry. Choose categories that best suit you.

Once you identify where you’d like to make the most impact, you’re ready to move on to the next step.

Identify Your Goals

Next, hone in on your specific goals. Your goals will dictate which part of your business you should monitor and which KPIs will be most beneficial.

Let’s take a look at how identifying specific goals can help you choose the right KPIs.

Ecommerce Goal #1

If your main goal for the year is to increase traffic to your Ecommerce store, you may want to track:

  • Ecommerce Site Traffic
  • Marketing Conversion
  • Social Media Engagement

Ecommerce Goal #2

If you want to increase overall revenue, KPIs that can help achieve this are:

  • Average Order Value
  • Conversion Rate
  • Zero Result Search Rate

As you can see, the right KPIs for your business will be determined by your unique objectives, so it is crucial to identify them first.

Once you’ve honed in on your area of interest and found a few suitable metrics, let’s see how you can narrow down the KPIs that work best for you.

Choose KPIs that Offer Meaningful Information

You’ll want to ensure your KPIs provide necessary and meaningful information for your business.

We recommend selecting KPIs that have the following attributes.

Based on Historical Data

Analytics based on historical data will help you discover areas you’d like to improve and help you track progress over time.

Historical data will alert your business to patterns and trends so you can set realistic goals, focus your attention on the right areas, create a baseline for comparison, and effectively monitor progress.

Use historical data to your advantage by creating KPIs relevant to your business, then map out an actionable plan to address them.

Collectively Measure Growth

There are many KPIs to track growth: overall revenue, average cart value, number of visitors, and more.

We recommend picking more than one to give you a complete picture of your business’s growth.

These KPIs will help you benchmark performance, focus on continuous improvement and make more informed decisions.

Establish Concrete Goals

Lastly, as we mentioned, when creating a KPI, you’ll want to make sure your goals are clear and concrete.

Concrete goals provide clarity and focus, and they allow progress to be tracked over time.

For example, let’s say you want to focus on marketing. Concrete marketing goals can vary depending on your business but may include increasing sales, boosting website traffic, or achieving ROI on Ad campaigns.

Key performance indicators provide a basis for setting targets and performance benchmarks, so ensuring they establish concrete goals is an effective way to drive improvement.

Choose the Right KPIs for Your Business

Now that you know how to assess your business goals and decide on a few target areas, you’re ready to choose the KPIs that best address them.

If you need some ideas, here are 25 different Ecommerce KPIs you can use to improve business performance.

25 Essential Ecommerce KPIs for Maximum Business Performance

To help you choose the right KPIs for your business, we’ve compiled a list of 25 useful metrics, discussed their impact, and explained how to track them.

Let’s get started!


1. Customer Acquisition Cost (CAC)

CAC is the average cost of acquiring a customer. This KPI shows how effective advertising campaigns and investments are.

To find CAC, track your marketing efforts by channel (advertisements, SEO, etc.) and divide the total spent in each category by the number of new customers acquired via that specific channel.

Customer Acquisition Cost illustration

Tracking CAC can highlight which marketing channels are most effectively generating sales.

That said, it’s important to keep in mind that customers may have been drawn to your business by the combined effort of many channels rather than one customer acquisition campaign.

2. Average Order Value (AOV)

AOV is the average amount shoppers spend on a purchase at one time. You can find this retail performance metric by dividing your store’s total revenue by the number of shoppers who make purchases over a set period of time.

Average Order Value illustration

You may have considered trying to increase total orders rather than average order value. However, it is generally more lucrative to encourage shoppers already in your store to purchase additional items rather than to attract new business.

3. Conversion Rate

There are many conversion metrics you can track. Conversion or click-through rate is generally found by dividing the number of targeted shoppers by the number of them who took a desired action (i.e. clicked on a search result or added an item to their cart).

Conversion rate formula

4. Cost Per Acquisition (CPA)

CPA is the cost of acquiring a non-paying visitor to your store. To find CPA, first calculate the cost of your marketing efforts (by channel, if desired). Then, divide it by the number of visitors to your store over a specific time period.

Cost per acquisition formula

5. Customer Lifetime Value (CLV)

Customer Lifetime Value is an estimate of how much money a customer will spend during their entire tenure in your store.

Increasing the number of new customers is more expensive than retaining return visitors. Additionally, return visitors spend over 60% more money than first-time buyers, so this is an important metric to track.

Customer lifetime value formula

If you want to increase CLV, you can start by creating customer loyalty programs and improving the user experience on your site. These optimizations may be time-consuming but can lead to significant increases in revenue.

6. Zero Result Rate (ZRR)

Zero Result Rate is the percentage of searches that lead to zero result search pages.

Zero result search pages often lead to frustration and cause shoppers to prematurely end their shopping journey. This is because shoppers think you don’t have what they’re looking for, even if you have the item in stock.

You can lower this number by implementing an effective search solution with a Rich Autocomplete that understands user intent and guides shoppers to desired results for every query.

While you can drastically lower ZRR with an optimized search solution, it is important to know that zero result search pages are inevitable. Check out this article to learn how to prevent frustration in your store and keep shoppers engaged.

7. Average Cart Abandonment Rate

Average Cart Abandonment Rate shows the percentage of shoppers who added items to their cart and left the store without making a purchase.

According to SaleCycle, Cart Abandonment Rate is much higher on mobile devices than on desktops, so it is important to pinpoint why shoppers aren’t completing their purchases to address this KPI.

A shopper may abandon their cart for many reasons:

  1. Shipping costs
  2. Item availability
  3. Difficult UI

Once you start tracking cart and checkout abandonment rates, you can target the specific causes and help alleviate shoppers’ pain points.

For example, you can acknowledge shoppers’ struggles during the add-to-cart process, address shipping costs, and take additional action you see fit.

8. Branded Online Search Impressions

Branded Online Search Impressions tell you how many people are searching for your brand online, organically, and across different channels.

This key performance indicator can be tracked via Google Ads (or another keyword tool like Wordstream or SEMRus) and used to show how effective marketing efforts are.

9. Customer Churn Rate

Customer Churn Rate is the percentage of customers who terminate their relationship with your business over a specific period.

You can calculate CCR with the following equation:

Customer Churn Rate formula

This KPI is important because customers with repeat visits to Ecommerce businesses generate more revenue over time than new shoppers who only make a single purchase in your store.

One way to lower your churn rate is to implement an advanced search solution. This will help shoppers find what they’re looking for more efficiently, create a positive brand image, and encourage repeat visits.

10. Gross Profit Margin

Gross Profit Margin is a strong indicator of your business’s health and performance.

To calculate Gross Profit Margin, use the following equations:

Gross Profit Margin formula

Generating a profit is one of the most important aspects of running a business, so this KPI is a very effective way to measure success.

11. Conversion Rate Per Traffic Channel

Tracking Conversion Rates Per Traffic Channel will help you discover which marketing efforts are most effectively bringing in business.

This KPI measures traffic volume and will help inform where your customers are coming from, which campaigns are most effective, and how to best allocate your budget.

12. Customer Retention Rate (CRR)

CRR is the percentage of customers a business retains over time. Most revenue comes from repeat customers rather than first-time shoppers.

This KPI will help you understand what aspects of your Ecommerce store are encouraging repeat visits and what’s causing them to leave.

Customer Retention Rate formula

Pinpointing areas of your business that can be optimized for better retention rates can drastically increase revenue, so this KPI is crucial.

13. Add-to-Cart Rate

Add-to-Cart Rate tells you the percentage of shoppers that added an item to their cart.

This metric doesn’t track purchases. However, it can help you understand if the visitors in your store have come with a specific product in mind or if they’re browsing. It also shows how effectively your Ecommerce store was able to help shoppers find desired items.

14. Repeat Purchase Rate (RPR)

Repeat Purchase Rate is the percentage of customers that return to your store to make a purchase.

This metric can help you discover how strong your customer loyalty is. This information can inform strategies that strengthen the impression of your brand.

Repeat Purchase Rate formula

15. Purchase Frequency

Purchase Frequency measures the number of purchases shoppers make in your store over a specified period. This KPI can help you determine which products perform well and help you gauge customer loyalty.

Purchase Frequency formula

16. Average Purchase Revenue Per Visitor

This KPI tells you how much revenue your Ecommerce store is making per visitor on average.

You can find this number by dividing total revenue by the total number of visitors in a set period of time.

17. Cost Performance Index (CPI)

CPI measures the cost efficiency of specific projects. It also shows if a project is performing well relative to its budget.

Cost Performance Index formula

CPI is a great way to determine how effectively your spending is generating your desirable outcome.

18. Return on Investment (ROI)

ROI measures the efficiency and profitability of an investment.

Calculate ROI by dividing net profit by initial cost. This will help determine how quickly and effectively your investment generated a profitable outcome.

19. Return on Ad Spend (ROAS)

ROAS measures the amount of revenue generated from money spent on specific advertising efforts.

This KPI determines how your marketing spending efforts impact actual revenue.

Return on Ad Spend formula

Track ROAS to ensure you’re not wasting your budget on channels that are losing money.

20. Email Signup Conversion Rate

This KPI measures the percentage of subscribers that opt into your sales funnel as a direct result of your email outreach.

Email campaigns are an effective way to target new sales prospects. There are many ways to create engaging email outreach campaigns; we recommend:

  1. Personalizing your email to the target audience
  2. Demonstrating you understand the recipient’s pain points
  3. Optimizing the content with relevant CTAs 

When done correctly, tracking your email list growth rate and email click-through rate can be incredibly lucrative.

21. Website Traffic

Website traffic is one of the most important metrics to track. The number of people who visit your site directly impacts purchases and revenue.

Measuring the percentage of customers coming from social media posts, blog traffic, newsletter subscribers, or other channels can help you determine where visitors are coming from. Then you can use this information can to better target people who will most likely increase traffic to your store.

22. Time to Purchase

Time to Purchase tells you how long it takes a shopper to make a purchase. Depending on your industry, shoppers may visit your store many times before buying something. Or they may come once and purchase an item from your Ecommerce business immediately.

For example, in a Consumer Electronics store, shoppers often make repeat visits. They want to ensure they research a single product thoroughly before buying it. In this case, it may be best to make detailed product information easily accessible so shoppers can make confident purchases without leaving your store.

On the other hand, shoppers in online pharmacies often want to buy medicine quickly. Thus, it is best to provide them with reviews or pharmacy pick-up details to shorten the average purchase time.

Tracking this metric will help you understand your shoppers and make data-driven decisions to streamline their purchase journey.

23. Repeat Visits

Repeat visits include shoppers who continuously look at items when making a purchase decision and repeat customers looking to make another purchase.

If you notice many visitors coming to your store without buying anything, pinpoint where shoppers are terminating their journey. This will help you determine which part of your store to optimize.

And, if you have many repeat customers, that’s great! But don’t get complacent. Shoppers’ needs and habits change frequently, so it’s best to continuously enhance the customer experience to strengthen brand loyalty and encourage more repeat visits.

24. Bounce Rate

Bounce Rate shows the percentage of visitors who enter your store through a search engine or other referral source and leave without making a purchase. This metric indicates whether or not shoppers are finding the products they’re looking for in your store.

One way to lower your bounce rate is to focus on search engine optimization. An optimized search engine that leverages Machine Learning and AI is an effective way to help shoppers find items they want to buy.

Search engines that generate relevant recommendations, suggest popular products or product bundles, and provide accurate rankings will encourage repeat visits and decrease your store’s bounce rate.

25. Referral Traffic

By measuring Referral Traffic, your business can see which sources are sending the highest number of visitors to your site.

This metric can help you ensure you’re spending money on the most effective channels.

Now that we’ve gone outlined 25 useful Ecommerce KPIs, you probably have an idea of which ones you’re going to use. So let’s dive into our final question.

How often should you track your Ecommerce KPIs?

The frequency you check your KPIs depends on the specific metric you are tracking, as well as your individual business goals.

That said, we’ve outlined commonly used time frames that you can use as a guide.

Weekly Metrics

Ecommerce metrics that give insight into the day-to-day health of your business (impressions, social media networks engagement, website traffic, etc.) should be monitored weekly. 

For example:

  • Conversion Rate
  • Website Traffic
  • Sales

Bi-weekly Metrics

Metrics that require a larger sample size to offer an accurate picture are best checked bi-weekly.

  • Cart Abandonment Rate
  • Average Order Value
  • Ad Campaign Performance

Monthly Metrics

Many KPIs are best tracked on a monthly basis for the most accurate results.

A few monthly KPIs include:

  • Customer Churn Rate
  • Email Signup Conversion Rate
  • Conversion Rate per Traffic Channel

Quarterly Metrics

Metrics that determine business growth should be checked quarterly to ensure you have a clear sense of how your business is performing in relation to the goals you’ve set out to achieve.

For example:

  • Customer Acquisition Cost
  • ROI
  • Gross and Net Profit Margins


Choosing the right Ecommerce KPIs for your business will be determined by your company’s objectives.

No matter which facet of your business you want to improve, we recommend choosing KPIs that establish concrete goals, are based on historical data, and collectively measure growth.

Once you decide which aspects of your business you’d most like to target and optimize, you can effectively narrow down the right KPIs and take actionable steps to maximize business performance for long-term success.

Rebecca Pacun
Rebecca PacunCopywriter – Prefixbox

Rebecca is the Copywriter at Prefixbox, a leading Search and Discovery solution for Enterprise Ecommerce retailers. Originally from California, Rebecca works at Prefixbox’s office in Madrid.

Testing Shopware: An In-Depth Look at the Open-Source Platform’s Site Search  

Testing Shopware: An In-Depth Look at the Open-Source Platform’s Site Search

At Prefixbox, we want to ensure Ecommerce retailers offer the best possible online shopping experience, and this starts with search.  

Many Ecommerce businesses set up their stores on Shopware, so we looked at its search functionality and created a guide to help you optimize Shopware for maximum performance

In this guide, you’ll find: 

  • Insight into Shopware’s product import process 
  • A checklist of essential search features (and an in-depth look at them) 
  • Best practices to optimize your Shopware search solution 

Let’s get started.  

Shopware Site Search Test Results

Shopware’s Dockware PLAY platform is the free, community-based version they offer. It has a basic search solution that takes time to set up, but the community behind it makes it possible to enhance and improve if you take the time to implement best practices and additional features. 

Below, we shared our experience using Shopware and outlined the steps you can take to optimize your store

What is Shopware? A Quick Summary

Shopware is an open commerce platform that many businesses use to build their online stores. 

The technology is open-source and uses an MIT license. Like Magento and many other Ecommerce platforms, it can be shaped and formed by the community and developers that use it

Tens of thousands of online stores use Shopware, including big brands, and it is most prevalent in Germany. Most notably, Euronics, Jacques Lemans, Tigha, Discovery Channel EU, Lufthansa Cocktail, the Mercedes Benz Classic Store, and Oktoberfest use the platform.

Shopware was established as early as 2000 in Germany and has been open source since 2016. In its over 20-year history, Shopware has garnered a strong community behind it. 

But what we really want to know is…  

How Does Shopware’s On-site Search Work and Perform?

To answer this question, a Prefixbox developer set up an online store using the demo version of Shopware so we could get first-hand insight into its functionality. 

Preparing Shopware for Testing

We didn’t plan to include a section on the set-up process; however, we ran into a few issues while setting up our store and couldn’t find much documentation addressing them online. 

We’ve outlined our experience with the set-up process and shared ways we overcame the difficulties to help other stores save time. 

Before you set up your shop, it’s important to know… 

Importing a Large Number of Products Takes Time

For this test, we used an existing product feed from an online consumer electronics store. The feed was complete with about 100,000 products and included product attributes and images. 

For our purposes, we needed a Shopware environment that had already been set up. Shopware provides this environment via Docker, which has multiple versions. The most popular of these is the Dockware PLAY edition, which provides the easiest, fastest solution for testing. 

Building the Docker environment was simple: it’s a popular task among developers and many free resources are available. 

After installing the Dockware PLAY environment, we got three endpoints to access it via browser: 

  • {domain}/adminer.php – We can access the underlying relational database, write queries, edit tables, columns, and rows here. 
  • {domain}/admin – We can access the admin panel to set up the entire store, upload, manage and maintain it here. 
  • {domain} – We can access the front-end of the online store here. 

The default environment includes a basic theme, some dummy data, and products with the web shop. However, we got rid of most of this to monitor the few remaining modified products in the database through the admin panel. 

After a quick overview, we looked for a convenient way to import our database of about 100K products. By default, you can only upload products individually in the admin panel; however, we discovered there is also an option to import or export multiple products at once

Unfortunately, the bulk import/export process was not as straightforward as we’d hoped. Our first attempts to import products were unsuccessful, and we couldn’t find much documentation about why this was happening online. 

After a lengthy trial and error process, we discovered Shopware could not import our products because our product naming convention didn’t match what Shopware used in their product database. Upper and lowercase sensitivity was causing a problem in a GUID. 

So, we had to find a way to change the format of all our product names from DisplayText to display_text or displaytext. 

Eventually, we wrote a program that converted our product feed into a properly formatted CSV for categories and products. This resulted in several rounds of generation, code correction, uploading, and then waiting for potential errors. After resolving some inexplicable invalid format errors, we found a way for Shopware’s import function to process our products and were finally able to start uploading categories to the database. 

We wrote a program that converted our product feed into a properly formatted CSV for categories and products. After resolving some inexplicable invalid format errors, we found a way for Shopware’s import function to process our products and were finally able to start uploading categories to the database. 

There, we ran into a second round of problems, because… 

Batch Sizes Matter When Importing

We quickly realized that uploaded categories don’t automatically appear in the shop; you must index them first. This is possible through the admin panel and could be done relatively quickly for our roughly 1300 categories by uploading batches of 50. 

We initially tried uploading our 100,000 products in a 40 MB CSV file but kept getting an unexplained timeout notification. After another lengthy investigation, we found out the engine begins indexing the products during the import procedure, and after a few hundred items, it permanently times out. 

This is how we eventually realized we could only import batches of 50, and a developer later confirmed this is a known issue. That developer let us know the only way around this is to use a backend-facing API, which allows us to write directly in the database. 

We hoped there would be a little more documentation regarding the API; however, we eventually figured it out: all data imported this way must be againindexed manually, which wasn’t feasible with 100K+ products and 1300 categories. 

So, next up on our list of challenges was finding a proper batch size that could be indexed. We thought we could trigger indexing from the admin panel with the right queue message. However, without documentation available, we found this option to be a dead end. 

We decided to start importing different batch sizes until we found the right one. 

We started importing batches of 2000, which was a painstakingly slow process with its own set of challenges. Eventually we figured out products could be imported in batches of 50

Matching Images to Products

Once we uploaded our products, we had to match their respective images to them (we couldn’t assign IDs to existing images beforehand). 

Our images were linked to the products in multiple tables, so we had to test them one by one to find the minimum viable input. 

In doing so, we encountered inconsistent error messages. We eventually managed to upload and link images to products in tables where they weren’t previously displayed. Then we ran another indexing. We expected this to be slow, but it just didn’t run. 

We circled back to the beginning to experiment with batch sizes again; smaller batch sizes made indexing possible, but it was a very slow process. 

Once we finished uploading our products, we turned our attention to design. 

Modifying the Design

Finally, after weeks of work, we wanted to tweak the design slightly. This is another part of Shopware that isn’t well documented. We found documentation for a previous version, but it required thorough user knowledge of PHP, CSS, and HTML. 

Since we are not PHP developers, we looked for built-in themes we could use. These themes (and extensions) are available in the Shopware admin panel. You need to sign in with a Shopware account; we already had one because, like Shopware Demo, they provide a trial for anyone who wants to test the engine. That said, we couldn’t log in, which another developer explained was because ‘it’s not possible from a container.’ 

Thanks to the helpful Shopware developer community, we realized we ultimately couldn’t touch the design in our current test environment. This is where the experiment ended for our developer. 

Shopware Set-Up Summary

Based on our experience setting up a store with Shopware, our developer found Shopware’s non-Enterprise version to be a solution for those running a simple online store. When it comes to bigger businesses, the setup process requires a lot more time and resources to get everything up and running.   

Testing Shopware’s Search Features

Once we set up our demo store, we were ready to start testing the search function. 

First, we created a checklist of search features that matter most. Then, we took an in-depth look at their functionality

Checklist: Essential Search Features

  • Autocomplete
  • Search Engine
  • Zero Result Pages
  • Mobile Optimization

We’ve outlined our findings below and suggested best practices you can use to build upon Shopware’s existing features.  

If you want to ensure your Shopware search solution is fully optimized, get your checklist ready, and let’s dive in.  


Autocomplete is one most impactful features of any onsite search solution. Autocomplete functions within the search bar, which is usually located at the top of the page. 

At the very least, all search bars should have an autocomplete function that deciphers user intent and provides relevant keyword and product suggestions. If equipped with the right features, autocomplete is a powerful tool that guides shoppers to desired items. 

To see how well Shopware’s autocomplete performs, we made another checklist of autocomplete features we find most important

Checklist: Essential Autocomplete Features

  • Product Suggestions
  • Typo Tolerance
  • Layout
  • Accurate Rankings
  • Mobile Optimization

Let’s break it down. 

Keyword and Product Suggestions

Keyword and product suggestions are a staple feature in an autocomplete. They must be relevant and appear quickly. 

In the Shopware demo store, autocomplete product suggestions appear after three keystrokes, which is slower than the industry standard. 

If you are using the community version of Shopware, it is important to be aware of this because shoppers expect to see results immediately upon clicking in the search box. 

Furthermore, Shopware’s autocomplete results appear in the typical dropdown style. As you can see below, we also see basic product information (in this case price, which is a default setting) and an option at the bottom to continue to the full results page. 

Shopware Search Autocomplete Feature Example

The dropdown results include relevant product recommendations, but we can see Shopware’s store is missing keyword suggestions, which are essential for an optimized autocomplete. 



In addition to showing product suggestions in the drop-down menu, keyword suggestions help shoppers navigate to accurate, desired results.

When shoppers visit websites on a desktop device, 50% click keyword suggestions, 5% click product recommendations, and 45% just hit enter. Keywords guide shoppers to high-quality results on the Search Results Page,so it’s important to display relevant results quickly to improve the user experience on your website.

An easy way to show shoppers keyword and product suggestions is to use a 2-column layout. 


A 2-column layout is an effective, user-friendly way to provide keywords, categories, and product suggestions that help shoppers refine their search within broad categories.

These suggestions enable shoppers to explore a retailer’s catalog, find the products they want to buy, and enhance the shopping experience by providing a clear path to purchase. 

Rossmann is a good example of a store that effectively utilizes a 2-column layout: 

Rossmann's Effective 2 Column Search Autocomplete

When searching for product names, Shopware’s autocomplete provides relevant and accurate recommendations.

Shopware Search Autocomplete Relevancy Accuracy Test

When searching for something other than the product’s name (i.e. a product number), results are accurate as well. As you can see below, the first result is the product with the corresponding number, and the following items are similar.  

Shopware Search Product SKU Accuracy

Number of Suggestions

In the demo store, the dropdown menu displays exactly 10 products, which is in line with our recommended best practice.  

Shopware Search Results Number of Suggestions



Retailers should display a maximum of 10 product suggestions, which means accurate rankings are essential.

As outlined in our autocomplete guide, if your suggestion list is longer than 10 items:  

  • Search time increases as users scroll through them 
  • Off-screen suggestions may be ignored or missed 
  • Users might experience choice paralysis and avoid making a decision instead of wasting time weighing all the options 

Category Suggestions

We were surprised to discover Shopware’s platform doesn’t support category search suggestions, which are very useful for shoppers. 



Category suggestions allow shoppers to narrow down broad search queries to specific items directly within the search box. For example, a shopper searching for headphones can easily specify Bluetooth, sports, or wireless headphones. 

Category search suggestions save time, provide customers with a clear path to purchase, and are an effective way to increase the user experience in your store.

To see how simple and useful this feature is, look at how IKEA’s autocomplete offers categories related to a shopper’s query: 

Ikea's Search AutoComplete Category Suggestions

Category suggestions are effective on search result pages too. If you’re looking to enhance the user experience in your store, we recommend offering them to shoppers. 

Typo Tolerance

A prerequisite for site search usability is a strong error tolerance for typos, so we wanted to see how well Shopware handles misspelled queries. 

Shopware’s autocomplete handles misspellings fairly well; in most cases, you can get relevant results even when queries contain multiple spelling errors. 

Shopware Site Search Typo Correction

Autocomplete also handles special characters well:  

When we replaced special characters with regular letters, the feature continued to work effectively. However, you can see below that the first results are based on exact text matches rather than an understanding of user intent. 

Shopware Site Search Special Character Handling

That said, Shopware provides relevant results when shoppers misspell their search queries, which shows us their typo tolerance feature is effective and is in line with our recommended best practice.



Advanced typo tolerance features that recognize spelling mistakes and present shoppers with relevant products, categories, and keywords decrease zero result search rate and ensure shoppers can easily navigate their path to purchase.


As explained in this guide on choosing an enterprise Ecommerce search provider:

 “A typo rate somewhere between 1 in 4 and 3 in 4 might seem extremely high, but with keyboards, fast typing, the prominence of typo-tolerant search engines, and spell checking, it is possible because we hardly pay attention to spelling anymore.

If your site search engine can’t tolerate typos – as in, recognize them and recommend another search, or even better, show results for the correctly spelled keyword instead of returning zero results – you risk driving your customer away.”


Shopware’s basic autocomplete layout is a standard, one-column list that appears in the drop-down window. 

Shopware's One-column Search Autocomplete Layout

If you look closely at the image above, you can see the list has product names cut short. This is something we recommend avoiding. 



To prevent confusion with shoppers who may not know what they’re clicking on if a part of a product name is missing, it is important to display full product names in autocomplete dropdown lists.

Showing full product names is one way to generate more revenue in your store. 

Many suggestions, including long or multiple keywords, won’t be able to fit in their row, given the limited screen size and that you must use a big enough font for readability.

However, if you shorten the suggestion by including “…” at the end, you may confuse customers who might not know what they’re clicking on when part of the information is missing.

So how do you solve this problem?


While it’s important to include keyword and product suggestions, prices, and photos where relevant, we suggest keeping your autocomplete simple, straightforward, and distraction-free.

Use text wrapping and expand suggestions to multiple rows as needed, even if this means fewer will be visible.

With modern on-site search solutions, the suggestion field can contain a large variety of elements like text, prices, photos, short descriptions, etc.

While these attributes help shoppers, be careful not to include too many additional elements. This can overwhelm shoppers, take focus away from the actual suggestions, and confuse customers more than it helps them.

Hovering Feature for Product Recommendations

Shopware’s autocomplete doesn’t offer shoppers a way to see if the item they click on is the product they intend to purchase. This can be dangerous because shoppers might grow frustrated if they click on the wrong product without realizing it. 



When presenting shoppers with any results list, you can show shoppers their clicks will take them to the correct product page by highlighting the area the mouse hovers over.

Our Autocomplete Search Best Practices guide says:

“When a shopper is browsing suggestions, you should indicate which product the user’s mouse is hovering over. Or, if shoppers are using keyboard navigation, they must be able to see which suggestion is active. 
This provides clarity and helps eliminate mistakes, like choosing the wrong suggestion and having to go back. 
You may also offer a hand cursor to signal shoppers can click on suggestions to be taken to a result page.”

A state-of-the-art solution includes dynamic keyword hovering, an advanced feature that provides additional, relevant product suggestions to shoppers as they hover over a specific keyword in the search box. Dynamic keyword hovering is one way to take full advantage of autocomplete because it allows shoppers to see more results without taking up additional screen space. 

Price, Images, and Discounts

Shopware’s autocomplete results in the dropdown menu include images and prices for the individual product. The images are small and resized to match the text, but in most cases can be understood. 

We did not set discounts in our test store, so we don’t have information about whether or not they’re displayed in the default version. However, based on the layout of the results bar, it seems unlikely. 



Showing discounts in the autocomplete dropdown menu can encourage shoppers to make a purchase or explore areas of your catalog they may have missed.

Praktiker doesn’t use Shopware, but they do a great job displaying currently discounted products in their autocomplete suggestions.

Take a look:  

Praktiker Search Autocomplete Including Price Discounts


We saw that Shopware provides relevant product suggestions when we looked at their typo tolerance feature. Shopware seems to prioritize exact text matches over relevance or popularity score, but we aren’t exactly sure how Shopware’s autocomplete decides on relevancy. 

Shopware exact match search prioritization



To best provide an accurate hierarchy of results, autocomplete should be capable of deciphering user intent instead of simply text-matching keywords in a product name or description.

As mentioned in our guide on choosing an  enterprise Ecommerce search provider, there are many ways to go about providing shoppers with relevant results.

As you can see in the link, one way is to implement a feature that leverages AI to predict user intent. Intent-based recommendations “guide shoppers through their path to purchase by suggesting searches that prevent zero results search pages.” 

If you’re using Shopware, you can custom-develop a feature to decipher user intent or find a third-party provider to help optimize your search solution.

As we wrap up this section, you should be well-prepared to assess and optimize your autocomplete feature so let’s switch gears and look at another important aspect of Shopware’s search solution.

Site Search Engine

An optimized search engine is critical to streamlining the shopping experience. When equipped with the right features, the search engine is a powerful tool for increasing conversions and revenue in your store.

We looked at a few key components of Shopware’s search engine and outlined best practices you can use to improve the shopping journey and, in turn, maximize business performance.

Facets and Filters

Filtering is essential to Ecommerce stores. Filters prevent shoppers from getting overwhelmed with endless results by allowing them to select desired product attributes. 

We only found one filter in the demo version of Shopware: a price range filter. 

Shopware Faceted Filtering Example

Dynamic filters and additional faceted filters were not present. 

Let’s look at the difference between dynamic and faceted filtering and see how implementing these features can add to the success of your online store. 

Faceted Filtering

Faceted filtering allows shoppers to find desired items by specifying preferred product attributes like brand name or price. Usually, the filters appear and disappear with each refined search as the suggestions in the pool of results decrease. 



Faceted filters help narrow down search results based on desired product attributes and improve the user experience in your online store.

If you’re wondering which filters to add, here are some suggestions:

  • Brand
  • Price (or price range)
  • User Ratings
  • Color
  • Material
  • Size
  • Popularity

We recommend displaying ecommerce search filters on the left-hand side of the SERP so shoppers can find them easily and efficiently navigate to desired results. 

Dynamic Filtering

Dynamic filtering means a store’s filters change dynamically based on the search query instead of displaying standard, static filtersFor example, if someone searches for shoes, they can filter results by size, and if they search for a laptop, they can filter results by processing power or other relevant specifications. 

As we mentioned, from our limited test, Shopware’s filters don’t seem to be dynamic. 

Dynamic filters help shoppers avoid dead-ends; for every executed search, filters change to make sure no combination leads to a zero result search page by only presenting available options.

If you’re selling shirts that come in many colors but you currently have no green shirts in store, two things can happen: 

  1. Shoppers select the “green” filter and land on a zero result search page.
  2. Dynamic filtering automatically hides the “green” filter option and only shows red and blue.

Dynamic filters prevent shoppers from growing frustrated with narrowing down results to products that aren’t available.

Faceted and dynamic filtering are different but work hand and hand; they both effectively present shoppers with desired items and prevent zero result search pages.


We discovered something interesting while testing for accuracy. 

We wanted to try searching for a product using its serial number. As you can see below, despite having that product (with the same serial number) in our cart, Shopware’s demo store search engine couldn’t find the product using the number we searched for. 

Shopware Shopping Cart Product SKU Search

While we previously saw Shopware’s autocomplete could analyze serial numbers and suggest relevant results, it seems this is not the case for the search engine. 

This tells us the default search engine most likely only checks for product names when performing the search, or at the very least, it seems to leave out some product attributes. 

This can most likely be amended by implementing a third-party on-site search solution. 



One way to ensure an accurate hierarchy of results is to use a ranking system that places relevant items on the search engine results page, regardless of what shoppers type in the search bar. 

Most solutions only rank products according to the number of times they’ve been ordered, which can lead to inaccurate rankings.

A good ranking algorithm usually considers popularity scores and relevance. Popularity scores considers product page views, search engine result page (SERP) clicks, cart actions, and the number of orders.


The Shopware demo store does not provide synonym mining and management tools, which means it is not optimized for synonyms. 

It’s important to note that this is an advanced-level feature, so it makes sense that a standard Ecommerce platform doesn’t have it. 

However, synonym management is still an important feature on our checklist and is included in this Ecommerce site search best practices guide.  

Optimizing synonyms reduces zero results rate and increases conversion rate.

Dead-end searches often occur when a shopper searches for a brand you don’t stock or if their query has a common misspelling. Instead of not showing any results, you can use synonyms to show relevant products from similar brands

For businesses with unknown vocabulary or many synonyms for their products, synonym management is a game-changer. 

If you’re wondering how to handle synonyms in your store, you can use advanced synonym mining and management tools to: 

  1. Find terms for which results can be improved with synonym management 
  2. Review the performance of search terms and products with synonyms 
  3. Customize synonym mining configuration settings 
  4. Reload the synonym database to update search indexes  

Synonym mining and management may seem daunting, but it’s an incredibly effective way to decrease zero result pages and increase conversion rate and revenue

Next, let’s take a look at what your online store can do to keep shoppers in the purchase flow if they are unable to find products on a search engines result page.

Zero Result Search Pages

Landing on a zero result search page is one of the most frustrating aspects of the online shopping experience.

While you can significantly decrease zero result rate by optimizing your search solution, shoppers will land on a zero result page at some point, so it’s crucial to handle them effectively. 

Landing on a zero result search page that doesn’t provide alternate products or information on what to do next can make shoppers feel like they’ve lost control over their shopping experience.

Well-handled zero result search pages re-route shoppers to desired products and keep them in the purchase flow. Alternatively, poorly handled zero result pages cause shoppers to leave your site and go to your competition instead. 

We looked at how Shopware handles zero result search pages and recommended best practices to help you keep shoppers satisfied and engaged. 

Relevant Product Suggestions

Zero results search pages in Shopware’s default demo store do not offer alternative product suggestions.  

As you can see in the screenshot, we entered a random phrase, but found that all zero result searches had the same outcome. 

Shopware Site Search Zero Result Pages

Instead of allowing shoppers to arrive at a dead end, there are many ways to help them find desired products.  



If a shopper encounters a zero results search page:

  • Clearly explain what happened 
  • Always take the blame 
  • Provide alternatives  
  • Suggest similar results

To learn more about approaching zero result search pages and how you can implement these recommendations, check out these effective no results page examples

Related Searches

A powerful way to help shoppers navigate away from no result search pages is to provide Related Searches. This feature offers shoppers suggestions for related keywords and related products and is an effective way to suggest similar items to shoppers. 

Related Searches is not part of Shopware but can be a great asset to store owners.  



Data-driven keyword and product recommendations help shoppers find the items they’re looking for and products that complement their original search.

Related Keywords

When shoppers land on zero result search pages, we recommend using Related Keywords to help shoppers reformulate their query with just one click. 

Look at how Nordstrom handles this simply and effectively:

Nordstrom Related Keywords Example

Related Products

Even better than related keywords are showing shoppers related products based on their initial query. offers a good example, take a look: 

As you can see, suggesting products related to the initial query allow shoppers to seamlessly continue their shopping journey instead of leaving them at a dead end and forcing them to re-execute their search. 

There are many reasons shoppers end up on zero result search pages. When setting up your online store, be sure to implement the best practices above to keep shoppers engaged throughout their shopping journey, especially if you have what they’re looking for in stock. 

Once we finished looking at the functionality of Shopware’s main search features, we wanted to see how Shopware’s search performed on mobile devices.

Mobile Optimization

Every year, an increasing number of shoppers make purchases on the small screen, so it’s crucial to ensure your online store is optimized for mobile devices. 

We looked at Shopware’s mobile user interface and laid out tips to help you optimize search in your mobile store. 

Let’s get to it. 

Search Placement

Shopware’s search bar (usually accompanied by a magnifying glass icon) can be found at the top of webpages. Shopware uses a standard layout that is clearly visible and easily accessible, which is in line with our recommended best practice. 



Your mobile Ecommerce store should prominently place the search box at the top of the page in the app and on the webpage version.

Search on mobile is critical. There aren’t many navigation options on phones, so the search box is the best way to help shoppers find what they’re looking for; good placement is paramount. 

Number of Recommendations

Next, let’s look at product recommendations. 

On mobile devices, Shopware’s product recommendations fill the entire screen and require you to scroll to view all of them. 

Shopware Mobile Search Autocomplete Number of Product Recommendations

We can’t see the full names of suggested products, which may confuse the customer and cause them to click on an undesired item because information missing. 



Mobile screens don’t allow for much text or visuals, so ensure the text and images add value to your shop. Limit content on mobile sites to only what’s essential to ensure quick page-load times and uncluttered pages.

In our mobile search box optimization guide, we suggest keeping the information for each product at a minimum; a photo, the product name, and the price are enough. You can include discounts and product descriptions but keep descriptions as short as possible, and make sure product images are small for quick load times. 

Search Results Layout

Search engine results pages should be well-formatted with products that load quickly and are ranked accurately. 

In Shopware’s mobile store, results are displayed in a single column and separated into pages. We were happy to see their search results layout adhered to most of our best practice recommendations. 



  • Provide clear tiles
  • Use large, high-quality images
  • Consider implementing quick-view windows with add-to-cart options
  • Show item prices and sale prices if you offer discounts
  • Implement paging

Shopware effectively uses paging, which is displaying search results on multiple pages so users can easily explore product options.  

The alternative to paging is infinite scrolling, which makes tracking search engine performance more difficult. Segmenting results by pages is more intuitive to the user, and offering fewer results per page creates a faster, less overwhelming shopping experience. 

Shopware clearly displays the number of results pages and makes sure the first result is at least partially visible, which effectively indicates the user can scroll down

Shopware Search Results Product Number Paging

The only thing missing here is text wrapping, which means we can’t see full product names. As we mentioned before, this can be confusing and lead to misclicks if you have many similar products in your store. 

Shopware Mobile Search Product Name Wrapping

The last thing we wanted to check for mobile Search Placement Layout is landscape mode. 

Shopware’s landscape mode handles the perspective change very well by changing the layout and including a grid. 

However, we noticed landscape mode accidentally causes product names to disappear.  

Shopware Product Search Autocomplete Landscape Mode

When setting up your online shop, make sure to test landscape mode to verify that product names appear for your shoppers. 

As we reach the end of our findings in Shopware’s mobile store, you should be ready to provide the best shopping experience for all visitors to your site, regardless of platform.


First of all, it’s important to reiterate that we only tested the Dockware PLAY version of Shopware for its Ecommerce site-search functionality. 

We described our experience setting up the platform for the test, did a thorough review of Shopware’s search features to test functionality, and provided best practices to help you optimize your Shopware search solution. 

Overall, we found the free Dockware Play version of Shopware to have a sufficient search when testing the basic functionality, like identifying typos or providing autocomplete suggestions. That said, we believe that if you’re looking for an industry-standard solution, you will need to further optimize your Shopware store with a custom solution or one from a third-party provider. 

When it comes to Enterprise size businesses, it will probably take a while to get everything up and running. However, taking time to implement the best practices above will ensure your store is fully optimized and set up for success. 

Because Shopware is an open-source platform with dedicated developers and time, optimizing the search solution is possible and can be made easier with the third-party extensions offered in the Shopware Store

Lastly, it’s important to mention that Shopware offers an Enterprise version of the platform, which includes many advanced features that make it easier to optimize your search solution. However, based on Shopware’s Enterprise Search configuration video, it appears this version can also be improved with the best practices and features recommended in this article. 

Rebecca Pacun
Rebecca PacunCopywriter – Prefixbox

Rebecca is the Copywriter at Prefixbox, a leading Search and Discovery solution for Enterprise Ecommerce retailers. Originally from California, Rebecca works at Prefixbox’s office in Madrid.

14 eCommerce Merchandising Strategies You Can Implement in 2022 (+ Examples)

14 eCommerce Merchandising Strategies You Can Implement in 2022 (+ Examples)

Traditional retailers (brick and mortar stores) have used digital merchandising strategies for ages, and eCommerce seems to be at a disadvantage. But you can actually learn how to implement their strategic techniques into your eCommerce store – with the help of technology and a little creativity.

In this guide to eCommerce merchandising, you will learn:

  • how to convince visitors to make multiple purchases
  • how to guide shoppers to the products you want them to see
  • offer them exactly what they want at exactly the right moment

Let’s get into it!

First, you have to understand the importance of these strategies. Millennials, the most important age group for most eCommerce sites, say they make 60% of their purchase online.

Additionally, 44% of all consumers say they will become repeat buyers if they have a personalized shopping experience. And of course, the pandemic only accelerated the shift to online retail – a trend that is here to stay.

This only makes the competition stronger, so you need to use the right techniques to engage your customers.

As always, we will start at the basics – then rapidly dive into methods you can implement right away.

Let’s start with the question…

What Is eCommerce Merchandising?

We can find a nice, basic definition from PracticalEcommerce, where they say

Ecommerce merchandising is the art and science of displaying products or offers on a website with the goal of increasing sales

This is a solid definition, but in order to make use of it, we will have to refine it and focus on the differences between offline and online merchandising in more depth than just that the latter is done on a website.

More specifically, in our opinion, eCommerce merchandising is a process of effectively highlighting the products you want shoppers to see and purchase without interfering, or interrupting, their shopping journey.

Ecommerce merchandising is a complex field of eCommerce itself, incorporating many methods, best practices, and strategies from marketing, UX, website design, sales, automation, and more.

In this article, we aim to gather the most important ones in one place for you; to create a guide that you can come back to and use as a sort of cheat sheet that answers the important questions: “what is product merchandising?” and “how can I use it to boost revenue in my online store?”

But first, there is a very important aspect we need to tackle…

How to Successfully Cross-Sell

Digital Merchandising can be used to cross-sell, so let’s first take a look at the difference between cross-selling and upselling.

Take the classic example:

  • “Would you like larger fries?” – This is upselling.
  • “Do you want fries with that?” – This is cross-selling.
Cross-Sell Campaign Example by McDonalds
McDonalds actually built an entire marketing campaign on this widely known phrase. We recommend checking it out.

With upselling, you simply take a product the customer already committed to and offer a bigger, more complex, more expensive version of it.

However, with cross-selling, you take the chosen product into consideration, and offer the customer something else that they are likely to buy in addition.

The key here is to consider the original intent.
In this case, this means products that the customer searched for on the site.

To make relevant suggestions and seamlessly guide shoppers, you can leverage many different strategies in addition to a “recommended products” section. We will cover many of these strategies right here if you scroll down.

Without wasting any more words, let’s dive into the basics.

This is where you have to start.

The Basics of eCommerce Merchandising

Before we get into the online merchandising strategies that you can use, here we will go through a few of the basic concepts.

Without wasting words, let’s start with…

Design Your Store Layout Wisely

First impressions have lasting effects – and in the case of websites, you only have a fraction of a second to make them. Somewhere between 0.05 and 0.1 seconds to be exact.

In order to make the best impression, and guide the user from the start, you must design your site with a merchandising focus.

Some of the essentials:

Some of the essentials:

  • Use large imagery with contrasting colors, high resolution and clear purpose.
  • Make navigation instinctive: put it where they would look for it, and make it very easy to use.
  • Make your search bar noticeable and make sure it has predictive search.
  • Make the layout simple
  • Promote the best-selling products.
  • Promote your current discounts, sales, campaigns.
  • Promote the highest-rated products.
  • Make content personalized if you can.
  • Avoid automated carousels (but use non-automated ones wisely).
  • Make sure your website displays properly across all screens and mobile devices.

Remember: with visual content, you have to replace the feeling of in-person shopping,
where customers can wander around a store, pick up the products, feel their texture, smell them and so on. You have one sense to use instead of four.

Product Grouping

The best place for product groupings are on custom search result landing pages, which you can leverage in marketing campaigns.

Keep in mind that if you are using faceted search, your customer will be quickly able to create custom groupings on the search results page based on all of the available attributes, like features, size, color, brand, and so on.

Suggesting related products

If you’re looking for further ways to cross-sell, suggesting related products or other popular products is a great option.

It is reasonable to assume that people shopping for certain products are more likely to take a certain cross-sell. For example, those looking for headphones will be more open to headphone chargers and cases.

These are best placed at the bottom of the search results page so that you don’t interfere in the buying journey, but instead complement it.

Learn more about the most important related search features to increase conversion rate & revenue by 6%.

Branding with visuals

Visuals are of course very important in guiding the attention of your customers, and they also have to be consistent across your entire site and with your established brand.

This means that you have to find visuals that represent your brand identity and at the same time not only catch the eyes of visitors but also accomplish the task of presenting your products and offers in an easily comprehensible way.

Depending on the type of product you sell, you can implement a bunch of different approaches to visual merchandising.

  • You can use demos if you have a virtual product.
  • Or 360-degree photography to showcase your products better.
  • You can also include your social media channels, including posts with branded hashtags to show your customers what others think and how they use your product.

Personalization and Online Merchandising

Personalizing what a visitor sees on your site offers a huge opportunity to increase your average order value (AOV).

As a first step, you can customize their experience based on simple demographic information, location, and season.

You can also recommend products and offers based on their history on your site, their previous purchases. Even better if they can create wish lists and if you are paying attention to abandoned carts – and the items in them.

Based on this information you can also create great personalized automated e-mail and advertising campaigns, but we will talk about those in another article.

By changing what your visitors and customers actually see on your site based on what you know about them you are likely to elevate their overall shopping experience.


eCommerce Merchandising Strategies and Visual Merchandising tips for Your Online Store

It is time to have a look at some online merchandising strategies using the basic techniques mentioned above and see how to apply them.

Here are 15 digital merchandising strategies for retail stores, with examples…

1. Home Page Merchandising

Your home page is one of the most important pages on your site and deserves special care.

Most shoppers will land here first, so it doesn’t just make a first impression, but it also gives you a great opportunity to guide your potential customers from the very beginning of their shopping journey.

Include your most important offer at the top.

One of the most effective strategies to go by – which is also easy to do – is to pick an offer that the majority of your potential customers would find attractive, and include it right there, above the fold on the first page.

This could be a seasonal offering, your all-time most popular product, or the highest-rated one.

For Apple, it is usually their latest product:


Basically, use your home page as brick and mortar stores use their windows to showcase their best products and invite in would-be customers.

Personalize the products you feature.

Below the single most important offer, you can start showcasing individual products – and as we have already talked about this, you should always personalize what you show.

Based on information about your users, set different criteria on what to display there to increase your chances of offering something truly personally relevant.

If you offer free shipping, show it right away.

Shipping costs are among the most common causes of shopping cart abandonment. Thus offering free shipping is a great strategy to convince more visitors to convert into customers – given that you can integrate the cost of shipping into the products anyway.

But it is also important to actually tell your customers that their orders are shipped free. One way you can do this is by placing a banner on your home page, so it can be one of the first things they notice.

Homepage Storytelling

Overall it is a good idea to give your homepage a structure, and for that, you can use the basics of storytelling.

  1. First, tell the most important information, with text and also visually. Make your brand clear: show who you are, what kind of products you sell, and what solutions you offer.
  2. Then comes the more specific information, like free shipping, your current special offers. As they scroll down, the information can get more detailed and guide them to specific categories, offers, or discounts even.
  3. Then, you have to reinforce why they should trust you – include testimonials, ratings, user product reviews, user-generated content as social proof, important badges, and so on.

Treat your homepage the same way you would introduce your brand to anyone if you wanted to make it extremely appealing. This is one of the most important rules of visual merchandising.

2. Site-Search Merchandising

We have already talked much about searchandising, i.e. using your site search engine for merchandising.

To recap some of the most important lessons from our previous guide:

  • Boost the products that bring you the most revenue: it makes sense to include products on the top of the results that are the most popular, the highest-rated, or simply the highest margin.
  • Optimize your no results pages by including some information on how the user might find what they are looking for, and also some personalizefild recommendations.
  • Personalize the search results: based on user history, you can place products at the top that are more likely to be relevant for them.
  • Use images: instead of just text results, display the most important information on the search result page, including visuals.
  • Use NLP search autocomplete – and if you can, include visuals right there, even before they hit enter.
  • Use promotional badges on your results to highlight ongoing promotions, offers, discounts.
  • And if you can, use faceted search, which greatly improves the shopping experience and makes the entire process faster.

Take a look at the Adore Beauty website, giving you instant results with visuals using autocomplete:

Search AutoComplete as Site-Search Merchandising Example

Learn more about the typical health & beauty challenges in eCommerce and important search features to increase conversion rate & revenue by 6%.

Also, intent clarification can be a great way to guide users to relevant offerings when their entered terms are too broad.

For example, if they search for headphones, there might be hundreds in this category, so you can offer them subsets of results like “Bluetooth” or “wireless” to narrow down the search.

3. Category Based Merchandising

Before setting out to design your category pages, take a moment and investigate how the most popular stores in your niche do theirs.

Best practices are always good to follow, and in most cases, you will find that category pages are informative. They display not only product names and images, but also some of the most basic information that could be deal-breakers for the customers, like the price, shipping information, and some of the most important attributes.

To make it easier to find specific products, if you have a wider range of offerings, include faceted search options on the category pages. Make sure that these options match the attributes in that specific category – this could be anything like brand, size, price range, release date, and so on.

Category Based Merchandising Example by boohoo
A nice example from boohoo, with a result page that features a lot of basic information, discount and uses faceted search.

4. Product Page Merchandising (With Visual Details)

Brick and mortar stores have a major advantage compared to online retailers. If you personally visit a store, you can see the products better, and you can touch, hold, and even smell them. You get a much more personal, immersive shopping experience, which in turn gives you more confidence to actually make a purchase.

There are a few ways you can allow your customers to inspect the products more closely on an eCommerce website:

  • One is using 360-degree product photos, so the customers can look at your products from every angle.
  • Using very high-quality zoomable photos allows for a closer inspection of the details.
  • Close-ups of the most important features help with answering some of the questions they might have about the product, like what features or accessories it has.
  • Photos depicting the products in use help with reinforcing the mental image they create, imagining how they will use it. (Best if you have user-generated content for this!)
  • Product videos are even better at this as they are more immersing, and can showcase the product in use and in a variety of ways.

At the Milk Bar, even for simple cakes, they include a large number of high-quality and close-up photos with many angles to awaken your appetite:

5. Collection-Based Merchandising

Grouping relevant products on a custom landing page is always a good way to cross-sell your offerings.

Let’s say you have an eCommerce business that sells clothes. Most people will of course search by categories and attributes – for shoes to wear in the fall that are waterproof or hoodies that are a certain size and color, and so on.

But many of them will look for certain styles. If there are clothes in your store displaying, for example, pop culture themes, this is a great opportunity to create collections. This way fans of a franchise like Star Wars or Marvel can browse these themed products together.

Also, if you feature multiple collections, make sure you create a category page for them, where people can easily browse through them.

A great and simple example could be Amazon, where if you go to the toys section, you can find the products grouped by the characters or brands they are based on:

Collection Based Merchandising Example by Amazon

6. Featured Products and Collection-Based Merchandising

To tie into homepage merchandising: besides personalized products, you can also display your most popular collection on your home page.

The top of the page should in general be a hero shot of one specific offering, however, if you want to display multiple products and collections above the fold, you can do that.

A slider, especially an automatic slider, is something in this case that you should avoid: they generally perform poorly and are frustrating for the users. But you can make use of tiles, for example, and display collections in addition to your top products.

This way you can trigger multiple different selling points, aimed at different segments and likely have a greater chance of showing the new visitors something they might be interested in right at the start.

Featured Products and Collection-Based Merchandising Example
Over the Moon introduces visitors to a collection right away on the home page – likely based on customer behavior.

7. Simple Product Merchandising Focus

If you have a smaller range of offerings, you might want to opt for focusing on a single one on your homepage. This is also a good strategy if your eCommerce business is new and you have a limited budget to publicize them.

Luckily focusing on a single product or unique type of product also means that you can use a website design that is much simpler.

A great example is the swimwear company KIINI. They have a very limited number of products, all in the same style. On the site, you are greeted simply by a hero image, and clicking through that you get to the single category page, showcasing their swimwear in different colors. It’s very simple – and very effective, useful for maintaining a consistent brand image.

Simple Product Digital Merchandising Focus Example

Rotate Your Highlighted Products for Returning Visitors

If you have a high number of repeat customers and a wide product range, a basic eCommerce merchandising strategy is to simply rotate your homepage visuals and highlighted products (if you don’t use personalization).

This can of course be simply automated: you just have to set the parameter for how often you want to show returning visitors different content on your site.

This can of course be simply automated: you just have to set the parameter for how often you want to show returning visitors different content on your site.

Just consider that even traditional stores use this technique. Not just by simply changing what is in the window – grocery stores sometimes switch up rows or change the location of sections to force their customers to look at more products while they search for what they originally wanted.

9. Cross-Selling In the Shopping Cart

Your shopping cart is an ideal place for cross-selling products. This works especially well with accessories. (Remember the “do you want fries with that?” method).

When a customer looks in their cart to check the items, overall price, shipping, and other details, eCommerce merchants have a unique opportunity to offer related, or complementary products, as you know in real-time from the contents of the cart what they are interested in.

When a customer looks in their cart to check the items, overall price, shipping, and other details, eCommerce merchants have a unique opportunity to offer related, or complementary products, as you know in real-time from the contents of the cart what they are interested in.

A good example here is Croniche – right after you put something in your cart, they offer relevant, similar products or accessories based on your choice.

Cross-Selling In the Shopping Cart Example as Digital Merchandising Strategy

10. Use Customer Data to Your Advantage

Customer data is the simple greatest asset for any company, and here, eCommerce stores have an advantage!

Your eCommerce site (and search) will likely be able to gather a lot of valuable data about customer behavior.

So, if you haven’t yet, enable Google Analytics on your site. The customer data you can gather will allow you to look at the paths your users and customers follow, so you can optimize your site to better guide them.

So, if you haven’t yet, enable Google Analytics on your site. The customer data you can gather will allow you to look at the paths your users and customers follow, so you can optimize your site to better guide them.

You will discover common exit pages, which you can optimize to boost sales.

Ecommerce merchandising, like most of eCommerce, is heavily based on data, so the more you can collect and analyze, the better you can optimize.

Use Customer Data for Digital Merchandising Strategy Example

11. Spark Loyalty in Return Customers

If you want your customers to make multiple purchases in your store, return often and check out your new products or reorder the ones they run out of, you have to focus on building loyalty.

The basics of loyalty have to do with the entire shopping experience: it should be fast, convenient, and with no unnecessary interruptions. This will make your customers love your store and continually return.

You can also encourage your existing customers to make more purchases if you implement loyalty programs – even simple ones, like point-based systems that can be redeemed for discounts or giving away one-time discount codes on birthdays. All of these can usually be done with a few simple add-ons.

You can also encourage your existing customers to make more purchases if you implement loyalty programs – even simple ones, like point-based systems that can be redeemed for discounts or giving away one-time discount codes on birthdays. All of these can usually be done with a few simple add-ons.

Also, look into creating special offers for products that are most often left in an abandoned cart, or the ones that are most prevalent on wish lists.

IKEA likes to really immerse you in its loyalty programs, giving you members-only offers. We borrowed this example from Antavo, where you can learn a lot more about customer loyalty.

12. Use as Many Decision Reinforcing Elements as You Can

Displaying products in an inviting way and providing discounts is not always enough to convince shoppers to make a purchasing decision.

You have to make sure that your would-be customers trust you with their money and that they feel good about their decision to make a purchase.

To do this, you can utilize a wide range of elements that encourage them, such as:

  • Product reviews, most importantly the ones that talk about the benefits of using your product.
  • User-generated content that shows actual people are using your product – and they are happy with it.
  • Ratings, preferably with some visual element, like five golden stars.
  • Expert proof: find some influencers in your niche, preferably professionals, who can test your product and give reviews.
  • Use numbers: show how many people have already bought this product, how many viewed it in the past few days, how many put it on their wish list and so on. Sometimes just displaying how many are in stock can incentivize a purchase.

Many of these can be displayed even on your search result pages – so go on and include them.

Reviews are used on a product page at, making sure that you make the right decision.

13. Use Banners on Search Result Pages

Banners might not be the best form of advertising in a brick-and-mortar store, but they can be effectively used on your online store.

These enable you to highlight promotional periods or specific products or brands outside of the search results so that you can inform shoppers of certain messages without interrupting their searching journey.

This is, of course, best used when you display banners on relevant results pages, so make sure you use an on-site search solution that allows for this level of customization.

These are highly effective during seasonal sales or promotional periods like Black Friday to boost sales of certain products, highlight bundle offers, or inform shoppers of limited-time offers.

14. Redirecting Searches to Landing Pages

There can be certain situations in which a shopper searches for information about your store and not for a specific product. When this happens, you don’t want to take them to a no results page, but instead, redirect them to an informational page.

The most common example is if they search for opening times, contact information, or the location of the store. In these cases, you can redirect the users directly to the relevant page of your site containing the needed information.

Conclusion: What is the Best eCommerce Merchandising Strategy?

Modern eCommerce merchandising is complex to break down into specific strategies and techniques to use. The best thing for you, as a merchant, to do is to take a holistic view and try to implement various techniques that make sense for your brand and business strategy.

In regards to online merchandising, eCommerce businesses do have a few disadvantages compared to traditional brick and mortar stores – but you can rarely find anything that can’t be replaced with technology and some creativity.

Up- and cross-selling techniques, using customer data wisely, designing your category, product, and search result pages are all very important steps in even the simplest of online stores.

There is only one question: where will you start?

Paige TyrrellHead of Marketing – Prefixbox

Paige is the Head of Marketing at Prefixbox, a leading eCommerce site search solution. She’s an American who’s been living in Budapest since 2017 and loves giving #alwayslearning sessions to help people optimize their online stores.