Composable Commerce: The Future of Flexible and Agile E-commerce Solutions

Composable Commerce: The Future of Flexible and Agile E-commerce Solutions

Composable commerce is emerging as a frontrunner for businesses looking to transform their traditional monolithic E-commerce platforms into more flexible and agile architectures. Composable commerce offers businesses more freedom and scalability in creating seamless customer experiences.

Join us on this journey as we delve into the convergence of composable architecture, and explore how businesses can leverage it to unlock new possibilities in their E-commerce ventures.

We’ve recently covered the basics of Headless Commerce and how it’s different from traditional monolithic sites. Composable commerce is the next step in the evolution of Headless commerce.

What is Composable Commerce?

Composable commerce is made possible by headless technology, but the two are not interchangeable.

Elastic Path describes composable commerce as the process of composing the best possible commerce components to create a cohesive solution that meets your unique business needs.

These components, often referred to as “composable building blocks” and Packaged Business Capabilities (PBCs), handle specific E-commerce functionalities such as product catalog management, search, checkout, payments, etc., and are connected via APIs.

Businesses can easily put together multi-vendor commerce solutions based on their preferences and business requirements.

This modular approach has allowed online businesses to gain more control over the customer experience across multiple touchpoints. Composable commerce platforms also enable retailers to quickly adapt to changing market demands or experiment with new features by easily swapping out or adding new components without disrupting the entire system.

MACH architecture

We can’t talk about composable commerce without mentioning MACH architecture.

The letters stand for Microservices, API-first, Cloud-native SaaS, and Headless. MACH is a set of technology principles that enable businesses to build best-of-breed, modern platforms, and is the first building block of composable commerce.

Let’s take a look at each of these “letters”:

M – Microservices: These are individual, independently developed and managed pieces of software. The composability of Packaged Business Capabilities (PBCs) is enabled by a microservice-based architecture, as PBCs are built up by one or several aggregated microservices.

A – API-first: The storefront is connected to the back-end system through APIs, enabling several applications or services to tie together.

C – Cloud-native SaaS: Software-as-a-Service that leverage cloud features, like automatic scaling and high availability. This software automatically updates, so you don’t need to worry about making upgrades.

H – Headless: Headless architecture is the base of the composable approach. As the front-end of the storefront is completely decoupled from the back-end, it allows retailers to easily update the user interface. The application can be tied to several endpoints, different channels or devices.

Salesforce is a proponent of composable commerce. It enables retailers to work with a composable storefront (“an industry-standard framework for creating innovative Progressive Web Apps”).

Salesforce recommends composable storefronts to all those businesses that:

  • need more operational agility to stay ahead of customer expectations
  • want flexibility and freedom in choosing which third-party solutions to integrate that match their objectives best
  • strive to create unique digital experiences.

Benefits of Composable Commerce

Increased speed

By separating the back-end and front-end systems, you eliminate the need for requests to pass through both. With the help of headless solutions and/or a composable commerce approach, many requests can be handled on the front-end. This results in faster loading times, which corresponds to a better user experience for your shoppers.

Greater flexibility and agility

The modular approach of composable commerce architecture allows businesses to easily swap out or add components as needed, without interrupting the rest of the system.

It heavily relies on APIs (Application Programming Interfaces) to facilitate communication between different components, which defines how they interact with each other, allowing for seamless integration and interoperability. APIs make it easier to connect with external systems and third-party services, further enhancing flexibility and agility.

For example, if a business wants to change its payment processor or add a new feature to the checkout process, it can simply integrate a new component via APIs without needing to rebuild the entire platform.

Reduced cost

The pay-as-you-go model that the modular architecture of composable commerce enables means that retailers can choose to only pay for the components they need, avoiding overinvestment in features their business needs don’t require.

This is a significant advantage compared to monolithic E-commerce platforms.

More scalability

Traditional, non-composable E-commerce platforms often present challenges with scalability since they are usually originally built as a single, tightly integrated system. As a retailer’s business grows, they may encounter limitations in terms of system performance, capacity, and the ability to accommodate increasing traffic or transaction volumes. Scaling such monolithic architectures and systems typically requires significant investments in hardware, software, and infrastructure upgrades.

In contrast, composable commerce solutions enables retailers to scale their technology stack more dynamically and efficiently as they grow, minimizing unnecessary costs by this all-in-one platform approach.

They can scale

  • horizontally by adding additional instances of specific components to handle increased loads
  • vertically by upgrading individual components to handle higher demands.

Challenges and considerations for retailers

While composable architectures offer many advantages, it’s always beneficial to be aware of any challenges that may arise with adapting a new, modern approach.

Challenges rooted in integration

Integrating multiple software components from different vendors or providers requires careful planning and coordination. Each of these components may come with their own set of APIs, data formats, and protocols, especially if they are developed by different teams instead of a single vendor.

Testing the separate components together might be the best way to ensure that they’re 100% compatible and interoperable, which also requires effort and time.

Maintenance of individual components

It can happen that the different components of a system have different update cycles, dependencies, and compatibility requirements, which can increase the overall maintenance burden.

Dealing with several vendors can also add to the complexity and the cost of the processes, but an efficient coordination of communication and support helps a lot with ensuring the smooth operation of a composable system.

Does composable commerce impact your customers?

In short: yes!

Composable commerce can have several significant impacts on your online shoppers.

As 80% of shoppers agree that the experience a company (including their website) provides is as important as the products and services they offer and sell, now is the best time for brands to embrace innovation and stay on top of trends.

Now, let’s see how composable commerce can assist in this matter:

Faster and smoother customer journey

Increased speed is not only beneficial for your business operations, but contributes to higher customer satisfaction and an increased conversion rate. By decoupling the front-end and back-end systems through headless commerce architecture, composable commerce allows for faster loading times and smoother user interactions. Shoppers experience quicker page load times, seamless checkout processes, and reduced friction when navigating the website or app.

Personalized shopping experiences

With access to a wide range of specialized third-party tools and technologies (and by choosing those that offer data analytics and utilize AI algorithms), you can personalize the shopping experience for each customer, deliver product recommendations based on previous user behavior, display promotions and special offers.

Access to innovative features

AI-powered product recommendations are not the only innovative feature shoppers can enjoy access to.

If you decide to utilize other best-in-breed components in your store, your shoppers can have virtual try-ons, ask for assistance from interactive chatbots, or engage in an entire social commerce experience.

By prioritizing personalization, performance, and innovation, you can build loyalty, drive sales, and differentiate your store and brand in a competitive landscape.

Wrap up

In summary, composable commerce marks a significant evolution in E-commerce strategy, enabling businesses to swiftly adjust and innovate according to market changes.

By breaking down commerce functionalities into interchangeable modules, companies gain flexibility, scalability, and agility in their online endeavors. Embracing this method unlocks avenues for tailored solutions, seamless integrations, and enriched customer interactions, positioning businesses at the forefront of digital commerce innovation.

Prefixbox’s solution optimizes the search experience on all headless and composable storefronts. What’s more, we are deeply integrated into many of these platforms, including native integration with Salesforce Commerce Cloud.

Karolina GecseMarketing Assistant – Prefixbox

Karolina is working with Prefixbox’s Marketing team on projects related to content, online presence and PR. She lives in Budapest, has a Bachelor’s in English, and is currently a Business student.

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

  • Explain what vector search is
  • Showcase 7 Main Advantages Vector Search has 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.

Vector Search explained

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 [2024]

How to Implement Conversational Commerce? 5 Steps to Success [2024]

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.

For a comprehensive understanding of conversational commerce, check out our other articles on this topic covering its fundamentals, types of platforms and use cases.

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 user experience, all of which revolve around real-time interactions that lead to satisfied customers who feel understood and valued. See Toptal’s article for more chatbot UX best practices.

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.

It discusses improving e-commerce search experiences through chatbot UX best practices.

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. 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.


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.

For a comprehensive understanding of conversational commerce, check out our other articles on this topic covering its fundamentals, types of platforms and implementation strategies.

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.