10 Autocomplete Search Best Practices – How Predictive Search Will Generate More Revenue for Your Store

10 Autocomplete Search Best Practices – How Predictive Search Will Generate More Revenue for Your Store

One thing is certain: around 30% of your online store visitors will use your on-site search function – and 25% of them will click on a search suggestion.

If you provide suggestions, that is.

This is why predictive autocomplete search is an essential tool for any online retailer.

And we’re here to show you how to leverage it to maximize conversions and revenue.

Autocomplete Search for eCommerce stores

We need something here that we want to clarify the basics first.

Chapter 1

What is Autocomplete Search?


Autocomplete is the function that displays keyword and product suggestions in real-time, based on what the user is typing into the search field.

The feature works in a very simple way: it detects what a customer is typing, and matches the query with data in the search index. If there are keywords or phrases stored in the index that matches what’s being typed in, it suggests those.

Search Autocomplete detects what a customer is typing, and matches the query with data in the search index.

In reality, it’s a bit more complicated because they also take into consideration the popularity of different products and keywords when ranking suggestions.

For example: in an online store selling clothes, if you type in “sh”, it might suggest shoes or shirts. If the store is selling bathroom appliances, it might suggest shower curtains or shelves.

Chapter 2

How does Autocomplete Search work?


Apart from using your site’s search index, autocompletes also takes previous user behavior into account, as it keeps track of what queries were previously searched and clicked, and which led to a purchase.

There can be other factors that determine exactly which suggestions appear, and in what order, like the frequency certain terms are entered or click-through rates of individual suggestions.

Autocomplete Search takes previous user behavior into account
Chapter 3

Achieve Better Sales via More Effective Autocomplete


There are many advantages of using autocomplete. If we want to summarize it, it helps shoppers make successful searches.

Here are some additional ways it improves the customer experience in your store:

  • It decreases search time, as the user is presented with relevant suggestions and quickly arrives at what they are searching for.
  • It makes the users more confident in the search and encourages them to add more details, leading to more precise matches.
  • It decreases the number of times a user arrives to a 0 result page, which provides a better experience overall. If relevant queries that are connected to existing product pages,are suggested, it effectively guarantees a successful search.
  • This also leads to the reduction in the number of people leaving your site, which means you have more time and opportunities to convert visitors to buyers.
  • It also educates potential customers about your product range, working as kind of a soft cross- or upsell opportunity.
List of autocomplete features that improve better search and UX

In short: by making search faster and ensuring relevant results, autocomplete will decrease exit rate, increase conversion rate and likely even your average order value.

We know from the B2C Retail Benchmark Report that

“Conversion rates are significantly higher where consumers have higher intent, i.e. they are searching for products.”

Now that we got through the basics, let’s dive into actual best practices to ensure those results we just talked about.

We included 10 of these with detailed descriptions here – let’s start with…

Chapter 4

10 Search Autocomplete Strategies


1. How Ranking the Suggestions Should Work


Even with autocomplete, you have a very limited number of chances to show the user the right queries, which makes ranking essential.

Ranking Suggestions has a limited number of chances to show the user the right queries

As we mentioned before, there can be many factors influencing the ranking of suggestions. Based on user behavior you can show queries that are popular (entered most frequently) first.

You can also opt for ranking queries that are more frequently purchased. Or you can rank queries related to ongoing promotions or special offers first.

2. Personalization Makes Autocomplete More Effective


There are three basic ways you can personalize the autocomplete suggestion in on-site search:

  • Consider the location of the customer, and show them queries that are popular in their area – or exclude ones that are irrelevant.
  • Consider the language: if your online store is multilingual, show each user suggestions in their preferred language for a better user experience.
  • Include their search history: make suggestions that are relevant to what they previously searched for on the site.
Personalized autocomplete based on search history,location and language of the user.

3. Keep Suggestions Simple and Few


Your suggestions should not extend the available space or clutter it – which is even more important on a mobile screen, considering that keyboards usually take up 30% of the screen.

Autocomplete suggestion list need to be short and simple.

a. Keep the Autocomplete List Manageable


The best practice is keeping your suggestions at 10 items or less (and this is why raking them correctly is essential).

If your suggestion list is longer than that, a number of unpleasant things can happen:

  • It makes the search time longer, as the user scrolls through them.
    Suggestions that appear off-screen may be ignored altogether.
  • The paradox of choice might kick in, leading to choice paralysis. This basically means that if we are presented with too many options, our brains often choose to just opt out entirely instead of wasting energy on weighing all of them.
  • On a mobile screen, the preferred number of suggestions is 4-8, and may even be less if they include not only queries, but precise products with photos and descriptions.

If you want to display more keywords and products, consider a 2-column layout instead.

b. Avoid Scroll Bars


If your suggestions extend into an area accessible only by scrolling, again, there are many problems that can arise.

First, these initially hidden suggestions are likely to be ignored, but if they are not, search time increases again.

Also requiring an additional task from the user also deteriorates the experience. As does the fact that they can’t get a quick overview of their choices right away.

A search bar in the suggestion field can also cause technical problems with design, but we are not going to detail those here.

c. Reduce the Visual Noise


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

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

Our suggestion is to keep the visual noise to a minimum. Include both keyword and product suggestions, prices, and photos where relevant.

4. Highlighting Autocomplete Suggestions


Highlighting certain elements of your predictive suggestions helps the user keep their focus and use the feature more naturally. Here is what to keep an eye on.

a. Highlight the Differences


Instead of highlighting (which usually means bolding) what the customer already typed in, it’s much more effective to instead highlight the predictive part of the suggestions.

This way they can focus on that more easily and determine the difference between suggestions, leading them to a faster decision.

Don't highlight what customer already typed in, highlight the predictive part instead for better UX

b. Highlight the Active Suggestion


When choosing between suggestions, you should clearly indicate which one the users’ mouse is hovering over or which one is active for shoppers using keyboard navigation (which must be supported in your autocomplete feature).

This provides clarity and helps in eliminating mistakes: choosing the wrong suggestion and having to go back.

Also, the active suggestions should be copied into the search bar. This helps users understand how the autocomplete works and makes it possible to expand upon the suggestion by providing more details, which leads to more precise results.

Highlighting the active suggestion is usually best done with a simple background shading.

c. Style Different Suggestions Differently


As we have discussed, multiple different suggestion types may appear in your field, and you must help the user understand the difference between them.

Let’s say that besides predictive queries you also include products and/or product categories. If you group these together, make sure to differentiate them. For example, style the text a differently. e.g. giving it another color.

If all different types of suggestions are displayed as the same, the users might not understand the difference, and ignore them or choose ones that aren’t really relevant.

Small changes in style make it easier for the user to scan the presented suggestions, and focus on those they are interested in.

Help search users to understand the difference between the search results for example with styling and different colors.

d. Style for Readability


Especially on mobile devices, it’s very important shoppers can actually read the suggestions, and also easily select the ones they are interested in.

Keeping readability in mind, the suggestions should be presented in a large enough font size, and with enough spacing, maybe even with separators, so that tapping on them doesn’t lead to accidentally selecting another option.

5. Provide Clear Instructions


The exact functionality of an autocomplete feature may not be completely clear to users right away, especially considering how different on-site search solutions can be.

In order to help them use the feature, providing instructions and labels can be greatly useful. These may include headings in the list, e.g. separating “Search suggestions”, “Categories”, “Articles” and so on.

Provide instructions and labels in search autocomplete, like "categories" and "articles".

This will help users understand how the list is structured, scan it more easily and direct their attention to the ones that are relevant to them. Without clarifying these details, mixing the different suggestions into one list, the user may pick an article instead of a product, or go to a category page instead of a more general results page despite their initial intention.

6. Visual Focus and Simplicity


When the customer is using the search feature, the autocomplete field together with the search bar should be given absolute priority in terms of visual attention.

a. Design for Visual Depth


Giving the autocomplete field priority can be easily achieved with darkening the rest of the site – the background in this case.

Help search user to focus on search results instead of other parts of the online store.

This will help fade the elements on the site that are fighting for shopper attention – CTA buttons, banners, product photos and so on. This way, the customer can easily keep their focus and not get distracted.

b. Reduce Visual Competition


On mobile, directive elements like navigation or shortcuts may appear beside or even above the autocomplete field, which actually ends up making navigation problematic and distracting.

Be careful where you place your live chat option, an icon for the shopping cart, or even sticky headers, to make sure it doesn’t detract from the search experience.

On mobile, hide navigation shortcuts until visitor search for products

By minimizing these distracting elements, you can minimize mis-clicks and provide a much smoother experience.

7. Support Both Mouse Interaction and Keyboard Navigation


Customers should be able to see which suggestion they are hovering over. This can be done by highlighting the given row. You may also invoke the hand cursor to make it clear that they can click the suggestions and it will take them to a result page.

Support keyboard and mouse interaction in site search

It’s important to provide keyboard navigation (especially since we mostly use Google for off-site search, and it has trained us to use this functionality).

Using the up and down arrows, customers should be able to switch between the suggestions, and select one by hitting Enter.

8. Mobile Specific Optimizations


There are a few things that are very, very important to keep an eye on when designing autocomplete for a small screen.

Here are the most important ones:

a. Use Text Wrapping


We already mentioned how you shouldn’t try to expand your suggestion field with a vertical scroll bar. We also recommend not using a horizontal one. 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.

If you just shorten the suggestion by including “…” at the end, you confuse the customer who won’t know exactly what they might be clicking on as part of the info is missing.

So how do you solve this problem?

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

Providing adequate information before the customer has to commit to a click is essential.

b. Partially Obscuring the Last Visible Suggestion


On mobile, scrolling is unavoidable in many cases, especially if you have to wrap suggestions.

Instead of adding a scrollbar, there are a few other things you can do.

The best one is probably partially obscuring the last result – which is a clear indication that the list continues below.

Now, considering the different screen sizes, browsers, fonts etc. it’s nearly impossible to get this right every single time because there are just too many variables.

So what you might want to do is check your analytics, find out which devices are used the most to access your store, and optimize for those.

Most users will still be selecting one of the suggestions that are visible right away, but with this method, you can provide a smooth experience for those who want to explore the whole list.

c. Make it Easy to Exit Autocomplete (and Remove a Query)


If a customer decides they no longer want to use the search bar, and wants to return to browsing the site, it should be easy for them to do that.

Providing an “X” icon to delete the query instead of asking shoppers to do it manually, is a handy solution to enhancing shoppers browsing journey.

9. Provide Category Search Suggestions


When a customer starts to type a query in the search bar, they might just want to explore what you have in a given product category.

Providing them with category suggestions is a very convenient way to enable them to browse your products and find the one they want to buy.

This saves time for the customer and provides a clear path, making the user experience smoother.

However, you want to avoid visual clutter and confusion – as we have discussed before – clearly indicate that category suggestions are not keyword suggestions. Do this with a simple heading and/or by using a different style.

10. Speed is Essential: Real-Time Autocomplete


Your autocomplete should always provide suggestions in real time.

If it’s slower than that, it can be downright irritating for the user, as they can visually perceive the lag – like with a website slowly loading individual elements.

If the autocomplete is not real-time, all of the above best practices are worthless as no one will be using a search bar they perceive as not useful.

Suggestions have to appear right when the first character of the query is entered, and should change with every subsequent keystroke to be updated to show relevant options.

Summary


Providing the highest level of quality during a customer’s journey will help you directly increase your store revenue. A better search experience leads to higher satisfaction, better experience, and overall higher conversion rates and average order value.

By using the best practices in your store, you can achieve exactly that.

Provide the highest level of quality during customer's journey

Remember the most basic guidelines:

  • Autocomplete should work in real-time.
  • It should provide relevant results – which can be personalized.
  • It should provide clear visual guidance as to how to use it.
  • If it’s in use, all other site elements should be faded into the background.

Of course it can quickly get complicated, and fine-tuning can be time-consuming to keep up with. This is why, to achieve the best results, we recommend working with on-site search experts.

As always, if you have any questions, or suggestions for the expansion of this list, reach out to us!

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.

How Data Integration Can Aid In Hyper-Personalized Ecommerce Site Search

How Data Integration Can Aid In Hyper-Personalized Ecommerce Site Search

In 2020 having a hyper-personalized site search is key for any eCommerce business. On its most basic level hyper personalization is defined by Business2Community as “the use of data to provide a more personalized and targeted products, services and content.

In today’s fast-paced and increasingly competitive eCommerce industry, having a strong targeted personalized site search will allow you to reach your customer base quickly and show them exactly what they are looking for.

Personalized eCommerce Site Search

But that just isn’t enough in today’s world, Merchants who are truly successful in the space are using data gained through personalization and using data integration to automate their applications together in a future-proof headless environment.

Let’s take a deeper dive into what types of hyper-personalization are available and how data integration in a headless environment can level up your eCommerce performance and compete with the best.

What is Hyper-Personalized Ecommerce Search?


With all ecommerce efforts, whether that be improving website design, personalization of eCommerce site search and even data integration of applications – the goal is to make business processes easier and efficient for Merchants and improve the overall customer experience. Some examples of website personalization that can help focus your customer experience journey can include increasing metrics like average order value, bounce rate, conversion rates, customer retention rates and overall profitability.

personalized customer experience journey in eCommerce

Shoppers increasingly expect merchants to deliver contextually-relevant experiences that take into account their past interactions with the brand. Every interaction a customer has with your brand is a data point that can be used to improve their customer experience. 74% of customers feel frustrated when website content is not personalized. Customers expect to be made to feel special and have thoughtful interactions with Brands.

Given that statistic, it’s clear that adding in site personalization applications like Nosto or Klaviyo to your eCommerce application mix will allow you to adapt product recommendations to every individual customer behavior level and create unique customer experiences for every customer and increase conversion rates, average order value etc.

How To Future Proof: Hyper-Personalization and Headless Commerce


There has been continuous focus on Headless Commerce this past year. Touted as the next stage in e-commerce, Headless Commerce is in essentials; API-driven. The main function is to remove the content management layer from the front-end of a website and it’s checkout. The content management system thus becomes hyper-personalized.

API-driven Headless Commerce

Having a headless system allows you to individualize every aspect of the content and products on the front-end of the site. This includes focused site search that can remind a previous customer of a past purchase, showing customers detailed relevant products similar to their past purchases as well as improving average cart value with individualized add-on products options.

Benefits of A Strategy Driven Hyper-Personalized Site


These are just a few simple examples of what is possible with a well rounded, strategy driven hyper-personalized site focused on customer experience. Remember,

People don’t buy objects, they buy experiences. Especially now because no one is shopping in-store anymore. Personalizing the experience, being everywhere your customer shops online from marketplaces, to your Shopify store is now more important than ever.

Merchants that are winning at the game of eCommerce are future-proofing their businesses by implementing headless technology that allows them to have a hyper-connected customer through implementing individualized customer experience across their e-commerce shopping journey.

Headless Commerce: The Future of Commerce


VL OMNI has written extensively on Headless in their latest Guide: Headless Commerce: The Complete Integration Guide This integration-first ebook looks at what it will take to make headless commerce a reality for many. From different ways to approach headless commerce, to major issues and implications a headless future will have on the ecommerce and commerce industries, readers will come away with a true technical understanding of what it takes to become headless.

Data Integration: Agile and Scalable Automation


So, with a hyper-personalized website and marketing processes, combined with headless technology that allows you to efficiently and effectively individualize products, orders and the overall customer experience for each customer. How on earth do you tie it all together?

Data integration and automation between applications is the easiest and most effective process for businesses at scale to eliminate costly and time consuming manual data entry and manual business processes.

But what is Data Integration and why is it important?


Data integration connects disparate applications together, allowing for consistent automated movement and delivery of data to create business processes across a wide range of applications.

Data integration plays an important role in the world of eCommerce because it provides users with a real-time outlook of business performance and transforms data into valuable, usable information by combining it from different sources.

As commerce in the physical world and online continues to evolve, your understanding of data integration can help inform your business’ ability to scale and build a more robust future for itself.

Data integration between different applications can be created in an agile and scalable manner, allowing you to automate hyper-personalized processes and individualized products at scale.

eCommerce Data integration between different applications

This allows you to focus on what’s most important to Merchants: creating a great customer experience. Data automation’s real value is connecting disparate systems together to eliminate manual processes.

In a hyper-personalized headless environment that can mean integrating your eCommerce store with your CRM, ERP, loyalty or personalization program.

This allows all the order and customer data collected from your eCommerce store, for example Shopify to be integrated into your CRM, allowing you to keep track of customers personal information and ordering habits.

This information can then be integrated into the content layer of a website in a headless environment to get specific personalized information and individualized offers to each and every valuable customer.

Hyper-Personalization in Site Search: The Role of Data Integration


Those who are succeeding in the ecommerce industry today are those who look at every aspect of their business, including their applications and business processes and look at how they can leverage all of their data into providing a better personalized experience for their customers.

Creating a hyper-personalized experience starts with the back-end data. The way that data is used and leveraged into providing valuable insights for your business will inform how successful your personalization targets perform.

By automating processes and integrating all applications together, your business can create a full picture of each customer, their habits and their shopping persona, allowing you to make educated decisions about how to personalize your website and site search for them. Ecommerce growth is truly open to those Merchants that take their data into their own hands and with it, create the best personalized shopping experience possible.

Vanessa MatosVanessa Matos, Marketing at VL OMNI

Vanessa is the marketing Coordinator at VL OMNI, a serverless platform for agile and scalable iPaaS ecommerce integration. From ecommerce platforms, ERPs, EDI, or marketplaces, we integrate your applications together to create a seamless experience at the operational level and enhance your business’ customer experience.”

What is a Search Index and How Does It Generate Revenue for eCommerce Businesses?

What is a Search Index and How Does It Generate Revenue for eCommerce Businesses?

No modern search engine can work without a proper search index. Everywhere, but on the smallest of sites, running a search would take seconds, minutes or longer, without an index. It varies based on how many pages the search solution would have to crawl.

This is absurd and would lead to huge drops in your revenue, as a 2 second delay in load time results in an 87% abandonment rate and even a 1 second delay instantly drops customer satisfaction by 16%.

eCommerce Search Index Revenue Generator Guide

So, let’s talk about search indexes and how we create them, so split-second searches are possible.

Contents

What is a search index?


A search index is a regularly, and automatically, updated database of all your products and related information in a simple form. It’s something that enables users on a site to perform fast and accurate searches.

It makes it possible for the search engine to perform any search in microseconds, because it doesn’t have to crawl hundreds or thousands of pages every time, it only has to search in the index.

What is a Search Index > Web Crawling > Search Index > Search Engine

It’s basically like an index at the end of the book where you can find the most important terms and phrases with the indicated pages where you can learn more about them.

Why Search is important in eCommerce – and why is it hard?


In short: because it’s very complex. You have to pay attention to a lot of details: things like providing the right attributes and tags, the natural language your customers use, seasonality, and the design of your product pages. There are many eCommerce search best practices you can and should try out, and fine-tuning is a never ending task.Your paragraph goes here.

There is a massive thought process behind every single purchase decision, even if most of it is subconscious, and there are so many little details on your site that can alienate a possible customer.

The user experience on your site is integral to the overall customer experience – and thus your revenue. Note that the conversion rate for visitors who use your on-site search is 1.8 times higher than the average – meaning they provide more revenue with every purchase.

And this isn’t possible without a proper search index.

Creation of a Search Index


In the case of books, indexes are created manually, usually by the authors and editors, which makes sense: the information included on a couple hundred pages is comprehensible for a single human, especially if they compiled it in the first place.

Now, if we are talking about websites, especially eCommerce websites, where it is not uncommon that thousands of pages are created for different products, attributes, content and so on – it’s essential that this indexing work is automated.

So, online search indexes are created using algorithms. Crawlers (or web spiders, as they are also known), which are basically automated algorithms, visit every page of the website regularly, scanning and collecting the information on every single one and assigning those to a simple database.

How Indexes Return Search Results


This is (or seems to be) a fairly easy process, in its essence, it isn’t very different from when you hit Ctrl+F in a document or on a website to find a certain word.

Of course, there is more to it, as modern site search engines have to account for typos, misspellings, relevant keywords based on semantics and user behavior, natural language and so on.

Of course, there is more to it, as modern site search engines have to account for typos, misspellings, relevant keywords based on semantics and user behavior, natural language and so on.

But these algorithms sort themselves out, and essentially as a user, you only see the results after you hit search on your query. These results usually include product names or content titles, some attributes or an excerpt, a picture and a price.

The Benefits of a Search Index for Your eCommerce Business


It will improve the user experience and click-through rates of your site search.

First of all, the faster you return relevant results, which are both improved from a proper search index, the more satisfied your customers will be.

And secondly, you can promote search results based on certain factors like relevancy, freshness, ongoing promotions and so on. If you want to learn more about this, have a look at our article on Searchandising Strategies.

Let’s have a look at some basic methods on…

Managing and Adjusting Site Search Results and Ranking


This enables you to define certain parameters, which influences the results shown to your customers when they search.

Utilize Searchandising to Show what is Important


Searchandising in itself is a vast topic, so you should really give a look at our article on it (link in the previous paragraph).

Utilize Searchandising

To summarize and simplify, you can boost certain products to appear at the top of the SERP based on how recently they were uploaded, how many are in stock, if there are any promotions connected to them, if there are available bundle offers that are relevant to the query, or any other criteria you want.

Guide Customers with Pinned Search Results


You can even temporarily, or permanently, pin certain results on the top of result pages – like offers in your holiday campaigns or evergreen content

Pinned Search Results

Customers won’t notice the pin as it appears as normal results, however it may become apparent if they run more searches.

Promote Certain Site Areas


You can also direct your customers to certain areas of your site, for example if you want to highlight a certain type of content like holiday gifts or products from a certain category before others.

Personalized Search Results


A big part of enhancing your user experience is giving everyone what they personally need the most. Since we can’t read their minds, we have to prioritize search results for them based on their previous behavior on our site: the products they looked at, the searches they performed, and the purchases they made.

Personalized Search Results

If you provide user-specific results, you can improve overall click-through and conversion rates together with overall user experience.

Analytics: Track Customers and Learn From Them


If you track the data about how people use your site search engine, and fine-tune results accordingly, you have a better chance of giving them what they actually want.

The main metrics to track are:

  • how often they use your search,
  • what queries they execute,
  • and their click-through rate (meaning they actually find something relevant).

Search UI and API


A search index, as we clarified, is the memory bank behind the site search function, which improves your user experience on its own.

But you can, in many ways, design your own search UI. For example, you can make sure that your 0 result pages are built in a way that encourages users to keep shopping, or you can use badges on certain results to highlight discounts.

But you can, in many ways, design your own search UI. For example, you can make sure that your 0 result pages are built in a way that encourages users to keep shopping, or you can use badges on certain results to highlight discounts.

It’s important that your search index is updated regularly and indicates the most recent results. You can do this by including an indexing API in the crawler.

Building a Product Database for a Well-functioning Search Index


The crawlers need data to work from, so it’s your (and your developers’) responsibility to organize your existing data in a way that the bots will understand and be able to translate to results as fast as possible.

This is why you should pay attention to…

Cleaning Your Data


Creating clean data for the search index (data cleansing) is the process of making sure that your data is actually valid. This can become especially problematic if you have a great number of products and the data that you get from the manufacturer is not compatible with your database.

If there is no regular cleansing process, you can end up with prices that are off by magnitudes or invalid values for product dimensions, among many other things.

Use Convertible Units of Measurement


Your data has to be uniform and in convertible measures, like from centimeters to millimeters, or centimeters to inches.

Imagine that you get screen sizes for TVs or smartphones from the manufacturer in millimeters, but on your product page you have to display those values in inches, because your customers are used to that measurement with these products. By having uniform and easily convertible units of measurement, you save yourself a lot of trouble.

Include Inventory Stock Data


Your stock should be continuously updated in your online store for multiple reasons. This helps you avoid situations in which you’re actively selling a product you don’t have in stock, which means your customers would have to cancel their orders. Or the flip side, your inventory could be piling up, but no orders are coming through.

Stock data can also indicate whether you should give more prominence to a product in the search results via Searchandising or push it back when stocks are low.

Consider the Product Variants


Your search index must be capable of handling different variants.. There are many instances in which you’re selling products that are similar, but have slight variations – shirts with different size and color, phone cases with different art, smartphones with different memory sizes, etc.

Product Variants handling in eCommerce Search

These variants have a tendency to appear very quickly – let’s stay with shirts for a moment and say that you have a T-shirt in 4 colors and 4 sizes. That is already 16 variants for the same product. So make sure that everything is in order in your database – and test it in your search solution, to ensure shoppers can find the exact product they want as easily, and quickly, as possible.

Deduplicate Products


If there are hundreds, or thousands, of products in your store, which is common, especially if you take product variations into account (e.g. different sizes, colors), it is very likely that duplications will occur. These sometimes will go unnoticed, for example if the same product is uploaded into different categories.

These duplications need to be found and eliminated. This is most easily done by running an automated algorithm to check photos, product descriptions and attributes.

Support Multi-language eCommerce


Finally, if your target market is wider than one country, you should have dedicated fields in your product database for every language and pay close attention to filling them in correctly. This enables each of your customers to use their own language and find the products they’re looking for.

Also look for a search solution that has a built-in language identification feature.

What to Pay Attention When Building Your On-Site Search


Search Bar and What You Indicate With it


When considering your search bar, the thing you want to pay attention to is visibility: users should be able find it right away and understand how to use it.

This is why it can be beneficial to put text in the bar itself. For example, some stores allow people to search by article number, but in others this returns no results. This is why you have to let shoppers know how they can use your search bar.

Two things to note here:

  • If you have some kind of search criteria that is impossible to translate to relevant results, let shoppers know this immediately.
  • Include every important attribute in your search index, so you don’t have to steer shoppers away from certain search criteria.

The Redirect Function


Your search solution could include a redirect function where certain queries take the user to a landing page or category page directly.

Without getting into the technical details, this is something your developers would have to look into – but determining the pages where you want to redirect users is yours.

Search-as-you-type Function


If your index is built the right way, the site search solution should be able to suggest queries in real-time – you can see this every time you use Google. Their solution is a mix of frequently used terms (user behavior) and terms that show up frequently in the index. You should follow a similar path.

Title of your sub-chapter


Based on user behavior and some custom product tags, you can provide cross/upsell opportunities on your result pages.

You could order results in a way that only a certain number of results are directly related to the query itself, and the rest are related products or bundled offers.

Faceted Search in Your Store


In order for faceted search to work properly, this detailed product database is essential, because results are edited in real-time based on the filters selected (which also need to update based on available products). These filter options are based on the various detailed attributes in your database.

Faceted Search in Your Store

We could go on for an entire article about this topic, and we already have: if you are interested about it, check out our guide on faceted search!

Your Product Pages are Important


The way you structure your product pages greatly impacts how effectively the crawler is able to gather information. To get the best results, your product pages should be uniform and fairly simple when displaying details and data like sizes, colors, etc.

Use Analytics to Learn About Your Search Index Performance


Analytics can say a lot about the health of your search index. Some of the basic metrics that can indicate a problem are:

  • Loading time of your result pages
  • The percentage of no result pages
  • Conversion rates of your result pages
Search Index Health Metrics

Conclusion


As you can see, it’s important that your search index stays up-to-date and is full of well-structured data in order to work properly. When you have a high-quality search index, you can provide the best possible search and customer experience via providing fast results.

A lot of what goes into a great search engine is very, very technical and complex – but some decisions cannot be made by developers alone. This is why it is important to always work together across units – and for you to pay close attention to the details.

  • Make sure your databases are compatible with each other
  • Make sure all information and data is up-to-date
  • Create pages where a crawler can easily find information
  • Design your result pages so they don’t only load faster, but also provide more opportunities for conversion

And you won’t have any problems!

Balazs VekonyOnline Marketing Manager – Prefixbox

Balazs is an Online Marketing Manager at Prefixbox, a leading eCommerce site search solution. He’s a Budapest based marketing enthusiast, who’s interested in new technologies and solutions and believes in the power of search.

13 Searchandising Strategies To Generate More Revenue For Your eCommerce Business

13 Searchandising Strategies To Generate More Revenue For Your eCommerce Business

Promoting products offline is a common and successful business practice.

But for online businesses, this is often neglected, because it can be difficult to help shoppers navigate to promotions. This guide will teach you how to effectively leverage searchandising on your webshop to increase revenue.

You’ll find out:

  • How to transform your result pages to increase your revenue,
  • How you can offer exact products in real-time, like autocomplete,
  • And which factors should impact your searchandising strategy.

Ready to start?

13 Searchandising Strategies for eCommerce

Think about how often people use the search bar on a site, be it a news site, an online store, a social platform or a message board. I bet nearly every visit.

As Econsultancy puts it: 

“Typically, up to 30% of visitors will use the site search box, and each of these users is showing a possible intent to purchase by entering product names or codes.“

This means that your search can make or break the success of your business. Your search function gives you a great opportunity to apply marketing and sales tactics to your search pages. 

Chapter 1

What is Searchandising?


In traditional brick-and-mortar stores, merchandising is basically the practice of guiding the shoppers’ attention to the offers and products they want them to notice.

This can be done in a large number of ways – hanging signs, rearranging the products on the shelf or the entire store, putting price tags with different colors on items that have a discount, and so on.

In eCommerce, there are many different ways to do this: putting large CTAs on your site, colorful offers above-the-fold on your main page, pop-up windows, and so on.

Where eCommerce merchandising becomes difficult is on the search page. Banners or pop-ups are not going to be very effective if a customer has a specific product in mind and is actively using the search bar to find it.

And this is where the power of search + merchandising, searchandising for short, comes into play.

As with every online marketing and sales process, searchandising isn’t a single step, but a whole process.

Let’s look at it now.

Chapter 2

The Process of Effective Searchandising


There are three very basic golden rules of searchandising.

  1. Understand your business’ basic priorities and goals. This will help you choose from the abundance of searchandising strategies available, many of which we describe in this article – and their potential benefits for your business.
  2. Have your KPIs ready. As with all business decisions, you should know what metrics you want to use to measure your success or failure. When using searchandising, click-through rate, conversion rate, average order value can all be important. But also, to better define what products and offers to showcase, you have to know your profit margins, inventory, and availability.
  3. Implement, watch closely, monitor, and refine. Monitor the performance of the rules you set, and fine-tune your strategy as you go. Incorporate searchandising analytics and decisions in your regular meetings and brainstormings, and define intervals for changing up things.

Does this all sound a little vague? Don’t worry.

Here are 13 very specific things you can do…

Chapter 3

Searchandising Strategies


In this section, we’ll show you some specific ways to highlight promotional offers to your customers, while maintaining their sense of control over the search process.

Keep in mind: the goal is not to bombard the customer with offers until they give up and convert. It’s to find the best offer for them by paying attention to what they’re doing, and what they’re searching for. 

Giving them what they want (even when they don’t know what that is), helps create grateful customers who are likely to return to your store for future purchases.

To do this, the first thing you want to do is…

1. Boosting Products: new arrivals, on-brand products


Simply placing certain products on the top of the results page can be successful, but it’s important you make sure it benefits your customers. 

When selecting products to move to the top of the results page, make sure they’re relevant, popular and are something your customer wants to buy.

This is a great thing to do with new models or products. 

Think about this: by searching for something specific, shoppers might miss a better, upgraded version, or they might not know a new product is available, so when you highlight a relevant, related product the benefit is clear.

If you have your own brand products, you might also want to showcase these first. 

We recommend you do this when these products are already preferred by your customers, validated by positive feedback, and you have clearly defined unique benefits that the competition doesn’t.

2. Custom collections and bundles


A great way of creating a cohesive shopping experience  while guiding your customers toward different products, is to not just place solitary products in front of them.

Creating custom collection offers can be particularly effective during holidays and special events. 

To do this, pick items that are especially popular during these periods or are frequently purchased together..

Then create Christmas bundles, Super Bowl offers or anything you want.Display these when your user includes the relevant keywords in their search query (like “christmas”). By displaying these bundles beside the product results, you retain relevance while guiding shoppers’ attention toward other products you can upsell and cross sell.

3. Boosting your highest-margin products


It makes sense to tweak your results pages in a way so that your best high-margin products are displayed first – as products at the top of the page are purchased more frequently. 

If you decide to boost products this way, make sure to monitor user behavior as this method can backfire. Keep an eye on your click and conversion rates, because altering results in this way can create a negative search experience and hurt your business in the long term.

4. Embedded Product Listings (Autocomplete on Steroids)


Suggesting keywords and phrases that your customer might be interested in, while they are still typing, is a great way to increase conversions.

Why not take it a step further, and display products that best match the query right there in the suggestions field too?

You can often do this through searchandising functionality.Like faceted search, this is a real-time solution that can greatly reduce a shopper’s path-to-purchase, which improves their overall experience.

ikea site search autocomplete feature

5. Promotional Banners Near the Search Bar


Banners may not be as popular as they once were, but if used correctly, they can still be powerful tools in increasing conversion rates.

Placing banner near the search bar and at the top of the results page effectively directs your customers’ attention to the categories, products, or discounts you want them to check out. 

Asos.com Faceted Filter function

6. Promotional Badges


Adding badges is a great way to communicate discounts to customers without interrupting their shopping experience. 

It’s one of the basic and most effective merchandising methods because you don’t have to alter the search rankings in any way.

You can use badges to announce: 

  • New product arrivals
  • Upgrades or new available products (e.g. new colors or sizes for clothes)
  • Available-in-bundle offers
  • Limited-time discounts
  • Last-chance products or sales

For a simple example, look at how Google clearly indicates which pictures are licensable when you perform an image search.

7. Optimizing and Re-ranking Product Results


When your eCommerce store has many products, most search queries yield dozens or even hundreds of equally relevant results

In order to effectively guide shoppers to the products they’re looking to buy, the next thing you should do is set up additional ranking rules to display the most popular and relevant products first.  

However, with searchandising, you can edit these ranking rules any way you want.

For example, you can choose to display relevant products that are on sale at the top of the search results page, in order to quickly clear out your stock. 

Or, you could opt to show your own brand of products first. Whatever you decide to do though, make sure that you keep relevancy and popularity as important criteria, so you don’t disrupt the shopping experience too much.

8. Personalized Result Optimization


Continuing that thought, what you should also take into account with ranking is the behavior of the given customer on your site.

If the customer has searched for men’s sneakers before, you could direct them to other men’s sportswear. 

Try to avoid the mistake that many retargeting campaigns make and don’t offer the customers the same exact thing that they previously bought.

This way, you provide a better shopping experience to the customer while increasing your cross-sell and up-sell opportunities.

9. Personalize Your Category Pages


Category pages are useful for shoppers who have some kind of idea of what they’re looking to buy, but aren’t looking for an exact product. 

By adding elements of personalization to these pages, you can quickly increase your conversion rate

As a pro move, personalize these pages based on personal preferences, behavior and their search intent – these yield the most relevant results.

10. Boost Products Based on Availability


One of the main things to consider when boosting products is their availability.

If you have a lot of a particular product in stock and want to move them quickly, boost them on the results page. 

However, if you have new arrivals and releases that are not yet in your inventory, you could also boost them so you can achieve nice pre-sales numbers. 

However, if you have new arrivals and releases that are not yet in your inventory, you could also boost them so you can achieve nice pre-sales numbers. 

This is a highly effective strategy if you are using a search that ranks products based on popularity. 

New products don’t yet have the clicks and purchases to boost them to the top of the results page, so if you know they’re going to be a hit, you can adjust the positioning to get them in front of shoppers immediately.

11. NLP Autocomplete


As we wrote in our previous article, 12 Best Machine Learning Strategies for eCommerce Businesses, natural language processing is an essential part of any site search solution. 

Here’s why:

Natural language processing and machine learning have to understand the kind of language and phrases your customers use, how often they use them, if the results are satisfactory for those phrases, and even common typos along with the correct spelling.

This way, every user can feel that the search engine is truly there to help and pays attention to the smallest details, all without being annoying.

Using the same language as your customers automatically improves any search function while providing a subconscious positive affirmation for the user about the usability and overall the customer experience of your site.

Oftentimes, you can also boost product and keyword suggestions in your autocomplete search, while taking into consideration NLP relevancy.

12. No-result Pages


Your no results pages present a huge opportunity to direct attention of the customers. 

While there might be 0 results for precisely what they’re looking for, you can use this opportunity to promote other, relevant products or things like: your current discounts and bundle offers, the most popular products (even better when personalized) or simply the products you want to move.For more advice regarding how to design no-result pages, take a moment and check out these 12 Awesome “No results found” Pages!

Sears No Search Result Found Pages

13. Updating product catalogs


Make sure your product catalogs continually stay up-to-date. Without accurate products and attributes, it’s nearly impossible to provide shoppers with a good search experience – whether or not you leverage searchandising!Look for merchant tools that allow you to easily update your product catalogs. Batch updating attributes is the easiest way to do this.

Chapter 4

Summary


Searchandising is not actually that hard to do – however, you have to know what you are doing, and why.

The key takeaways from this article if you are looking for searchandising techniques that will definitely improve your conversion rates are these:

  • Personalize: always pay attention to the history and behavior of your users, not just their location and demographics. Try to give them what they actually want, direct their attention in a way that is useful for them.
  • Use Search Rules: don’t just trust the algorithm to make the choices for you. You have your business plan, your cash flow, your inventory to consider, marketing campaigns that are set, holidays that are coming up. Based on these, make the rules yourself, and tweak the results just enough to make the most of your offerings.
  • Recommend Products: don’t be shy to suggest similar or discounted products. Put them in bundles or packages if you have to, but keep in mind that while you don’t want to be annoying, you definitely have to be a salesman. Define what and when to recommend that your customers will be grateful for.
  • Run Search Campaigns: besides your everyday sales and marketing campaigns, come up with creative ways to offer upsell or cross-sell right on your search result pages.
  • Track Data & Measure Results: once you have set the rules, start to watch them work. If they don’t, try other ones. Always base your decisions on the data that you see on your dashboards, and not gut feelings. Data-based decisions are the ones that will help you scale your business.

If you listen to the eCommerce Search Best Practices and base your decisions on the data about what your users like and what they don’t, you will increase key metrics like conversion, average order value, retention, and more.

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.

11 Features To Look For When Choosing An eCommerce Search Engine

11 Features To Look For When Choosing an eCommerce Search Engine

Site search is easily the most important function of any online store.

Apart from determining a huge part of the user experience, providing data about shoppers, it also increases your online revenue.

However, with so many providers and functionalities, it can be difficult to choose the right provider.

This guide will explain:

  • The most important capabilities in a site search engine
  • List the pros and cons of building vs. buying

Ready to check it out?

eCommerce Search Engine Features Guide

Contents

Chapter 1

The Foundations of Great E-Commerce Site Search Engine

Chapter 2

Must-Have Capabilities for Your Site Search Tool

Chapter 3

In-house search engine development or SaaS vendor solution?

Chapter 1

The Foundations of Great eCommerce Site Search Engine


Providing Relevant Results


It may seem obvious, and even an easy task, that a search engine should provide results relevant to an executed query. This is because we are accustomed to Google, which we use daily, and which is top-notch in relevancy. Google has universally set the standard of what a search function should accomplish. 

But keep in mind that Google uses an extremely complicated, ever-expanding and changing algorithm to be able to do that, backed by hundreds of developers constantly fine-tuning it – and it took them literal decades to arrive at today’s model.

Take a moment to think about what “relevant search results” actually means. For example, let’s say a shopper enters the query “cooking book” on Amazon.

The results they get are not simply based on matching keywords in the title or description of the product, because there are other important factors. Like shipping logistics and/or availability: they might get the best cooking book as a result, but how is it relevant, if the product does not ship to where they are, so they can’t actually buy it?


What if there is a typo in the query? The shopper is still going to expect relevant results, and will only get frustrated with a “no results” page and the fact that they have to repeat the search.

Then there is the question of how do you weigh the importance of product attributes – hint: if the keywords appear in a title, it should be more relevant than if it’s only included in tags, but shipping to the shopper’s location is even more important, and so on.

As you can see, relevancy is a much more complicated question, especially if you have hundreds or thousands of products in your online store.

Reliability, Uptime and Speed


On the technical side, you also have to make sure that your search engine actually works: shoppers can run queries anytime, from any part of the world, and they get the results almost instantly. 

The average Google search, again, is a standard that we are used to, and most times it takes only a fraction of a second to complete. Even if you can’t compete with them, you should use a search engine and hosting that makes it possible for your shoppers to get to the result page as soon as possible.

Chapter 2

Must-Have Capabilities for Your Site Search Tool


1. Autocomplete


One of the most basic functions that shoppers expect is Autocomplete: this predicts shopper queries once a shopper focuses in the search box, or from the first keystroke. It suggests keywords, products, and categories that yield relevant results.

Predicting shopper intent  is only one aspect: what is even more useful is that it slightly guides shoppers down their path-to-purchase by suggesting searches that won’t end in zero result pages. 

There is not much more to this, except our advice: if a site search engine lacks Autocomplete, stay far away from it.

And autocomplete should also be…

2. Typo-tolerant


There aren’t many studies out there with numbers on the average amount of spelling mistakes, even fewer focusing on search engines because search engine providers don’t usually publish this kind of data. But we can take away some interesting points from a 2006 article by W. John Wilbur, Won Kim, and Natalie Xie titled Spelling correction in the pubmed search engine.

According to their analysis, there  is a “misspelling rate” of 26% for words on an academic site. It seems possible that the misspelling rate on a public site could be even higher.

Nordlie (1999) observes that two thirds of initial requests are unsuccessful in meeting their objective and an NPD survey (2000) finds that 77% of the time an initially unsuccessful search is modified and tried again on the same site.”

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 certainly can be possible, because we don’t really 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 no results – you run the risk of driving your customer away. 

3. Managing synonyms


Another important aspect: synonyms. In many cases, your shoppers are going to refer to products or categories, even certain attributes by a different name than you do. 

For example: if they are looking for a laptop, they may write “notebook” in the search field, luminosity and brightness might get confused with LED lights, someone who wants to buy an instrument panel may search for a control board.

And if your search engine can’t understand this, shoppers are going to end up on zero result pages, even if you do actually sell the product they want to buy.

Which, of course, is bad, because your products effectively remain hidden from shoppers with strong purchase intent, and you lose money on every one of them.

We recommend you choose a solution with built-in Synonym Management

You might think it would be easy to find a solution that includes this, maybe it’s just a matter of integrating a synonym database – but actually customizing a search engine this way is very tedious work and it’s not at all fast.

Which brings us to…

4. Customization


Out-of-the-box solutions are convenient, cheap, easy and quick to implement, but rarely satisfy all needs. They aren’t all flexible in terms of customization: usually you can’t expand on the existing functionality or performance.

Meanwhile, open-source search solutions can be customized as you want, but they are also resource-demanding – implementation, development, maintenance can take a lot of time and energy.

But what is a good, middle-ground solution?

The best middle ground is usually a search-as-a-service solution, where implementation is quick, there is great room for customization, and as with SaaS services in general, maintaining the system is relatively low-cost.

Before committing to any kind of site search solution, think about your unique business processes and the needs of your shoppers. 

Can the search provider meet both of these needs?

5. Personalization


Personalizing what your users see can be a great way of not only increasing your conversion rate, but also your average order value.

A few examples how you can personalize the result page based on the past behavior of your shopper:

Show them products they viewed (and didn’t buy) earlier, similar products to those, or products matching their previous searches. This way you may guide them to additional purchases, as they may see results they didn’t stumble upon before.

Overall, personalizing the result pages based on behavior can decrease site abandonment, increase engagement and conversion rates, and improve the user experience and customer journey of your webshop.

6. Dynamic filtering


Instead of providing a static results page when the shopper executes a query, you can improve user experience and increase your conversion rate by leveraging dynamic filtering.

What this means: the search engine displays relevant results and filtering options based on the initial query. The key here is that none of the filtering options will lead shoppers to a 0-results page. 

For a ‘real life’ example, let’s say you have an online book store. When a user enters “sci-fi novel”, they are presented by a number or results, and also a few checkboxes appear where they can filter by the most relevant authors like Isaac Asimov, Frank Herbert, Iain M. Banks etc. But they won’t see J. R. R. Tolikien’s name there, as he never wrote science fiction.

This also means that someone who searches for ‘romance novel’ won’t see the same filter options as those authors didn’t write romances. 

The search engine does this by analyzing the attributes of the results and applying relevant filters, which is why this is called faceted filtering

As the shopper starts checking boxes to filter results, the irrelevant filter options disappear. 

This not only guides shoppers to the product they want to buy, but it gives them a sense of control and improves their overall experience on your online store.

7. Natural Language Processing


Natural Language Processing (NLP) is a very complex topic as it encompasses both machine learning and AI, so we are going to concentrate on what it actually does when integrated into a search engine: it enables the search engine to better understand queries by, well, processing natural language.

NLP enables the search function to provide more relevant results, offer suggestions via Autocomplete, and learn from user behaviour based on the wording and language used. 

It also makes your search engine more language-independent, as NLP is not strictly tied to a specific language.

It is a resource-intensive feature to develop, and some solutions simply sell their advanced synonym management as NLP, so keep an eye on the validity of these claims. We can’t add much to the advice Shopify gives you:

When you don’t dig into the specifics [of the NLP feature], you might only be getting a demonstration of basic functionality like synonyms with a fancier label. That’s a problem if you’re expecting an automated system with sophisticated language parsing.

8. Ranking


Make sure that you have the option to customize certain ranking factors. While relevancy is the most important, if you want to be able to provide better customer experience, it might also make sense to highlight popular products on a result page for example. 

Ranking algorithms usually incorporate relevancy and popularity scores. However, search providers have dashboards to let their customers alter the boosting parameters to sell more of what they want.
These ranking algorithms should also be refreshed at least daily to ensure results remain accurate and shoppers get the best experience possible.

9. Analytics


Your on-site search engine is one of the most valuable resources of customer data. You can learn invaluable information about them including: how they search for procuts, what wording and language they use, what they’re searching for that you don’t currently sell/have in stock, if they are successful with their searches or need help, and much more.

You have to be able to view this data in an easy way. So you should be looking for a search solution, that

  • Actually can track and store this information.
  • Has the KPIs that are the most important for you (like click rates, “no results” queries, popular product, popular searches, average number of products/purchase,  average order value, etc.)
  • Has a user-friendly dashboard. 

If you have all of these, you can refine your customer journey, improve marketing messaging  and to achieve greater conversion rates!

10. Merchandising


Merchandising is a way to effectively promote the products you want to sell. These can be new products, products with a lot of inventory, or products on sale. 

You can customize the placement of these by adding banners, editing the products on the search results page, adding redirect rules, and disambiguation tiles.

11. Indexing


Indexing is the process by which the search engine creates a database with all the available data on your products and provides results based on this database.

With indexing the key is to choose a solution with a frequency that suits your business model. Many times the frequency with which the tool indexes products and attributes depends on how much you pay for the service, the tier you are in etc.

If you offer a few products and update them rarely, lower frequency would be fine – but if you add new products daily or weekly, a solution which indexes new data monthly will simply cause you harm.

Shoppers on your site expect to find products instantly – this includes new products. Most online revenue is generated by shoppers who use the search function. If your search doesn’t have access to an updated product database, it can’t direct shoppers to the products they want to buy.  

Which means you miss out on money.

Chapter 3

In-house search engine development or SaaS vendor solution?


When it comes to implementing site search in your webshop, you have three basic options to choose from:

  • You can select an out-of-the-box solution.
  • You can decide to develop your own site search engine.
  • You can opt for a SaaS solution.

We previously mentioned the problem with the first option, out-of-the-box solutions. They can be fast, easy and cheap to implement, but in the long term, they can be temporary solutions at best, as they are not at all flexible – it’s unlikely they will fit all of your needs.

Therefore,  the rest of this article will focus on in-house development and SaaS search solutions: we’ll provide you the pros and cons of both options, so you can make an informed decision yourself.

In-house Search Development with Elasticsearch or Solr


Elasticsearch and Solr are currently the most popular open-source search engines that you can work with. 

Sidenote: don’t try to develop something from the ground up, even if you have unlimited budget. The timeline of a project like this in itself will stretch out so much that you are way better off with an open-source engine as a basis.

The timeline for in-house development


Setting up an open-source search solution (1-4 weeks)

With Elastic or Solr you are getting a basic site search solution, for which the setup will take something between a week and a month. 

However, you should know that the time frame depends on your in-house capacity: the size of the dev team, their experience with search, how much time they have to focus on the project, and , the number of products and requests your online store receives. This means that if you have a small dev team (or one focused on other products) or a lot of products and shoppers, it can take longer.

Advanced Data Processing (2-8 weeks)

Your search engine must have all the data about your products – all the attributes, values should be standardized and processed, together with sentences from product descriptions, relevant keywords have to be extracted. 

This will provide the base for your engine to work, and continuously updated in the future. The time it will take to do it the frist time will depend on the expertise of your developer(s), but usually it will be around 2-8 weeks.

Configuring the Basic Features (4-8 weeks)

Synonyms, default facets, tokenizers, default stemmers and the rest of the core features get configured in this phase that will take somewhere between 1-2 months.

Configuring the Advanced Features (20 weeks)

NLP-based suggestions and autocomplete, custom filters, contextual dynamic facets and some of the more complex features: these can take up to 20 weeks to configure.

Custom Ranking (1-4 weeks)

As we have mentioned, customizing the result pages to fit your business model and marketing efforts is an important function. 

Determining and setting the basic factors for this should take 1 to 4 weeks, depending on complexity. 

(And a few days each month for updating these values.)

Custom Search Functionality (3 weeks, at least)

Depending on what kind of extra functions you and your online store require, it will take at least 3 weeks to set these up. 

Think: search assistants, voice search, personalization of the results pages etc. 

The more you want to customize, the longer it will take – this could possibly be extended by many months.

Post-Live Launch Bug Fixes and Algorithm Improvements (3-4 months)

This is the fine-tuning phase after everything is set up – which is, of course, something that will go on as long as your site is live. The first testing, bug fixing and improving phase should last at least 3-4 months after launching your search engine.

To summarize: even with a well-staffed and experienced team of in-house developers, building your custom search engine based on an open-source solution will take you at least 1 – 1.5 years and that’s for a basic version without analytics. If you can’t afford that timeline (and the budget it implies), than a SaaS solution could be more advantageous for you.

Advantages of In-House Search Engine Development

Customization 

Developing your on-site search engine with your own team means that you have complete control over the process and what to include, how to build it. This allows you to tailor everything to your business needs.

Flexibility in Terms of Making Priority Bug Fixes

If you have an in-house team, priorities can be set as you want: they can get to fixing critical issues right away and you don’t have to wait on a third party, on customer service and so on.

Results Can Be Leveraged Beyond Search

Your custom-built search engine can be useful in developing other important site functions which your developers can create based on this work.

Disadvantages of In-House Search Engine Development

Team Recruitment 

If core members leave your team, crucial knowledge can be lost with them, even if all the documentation and written know-how remains. This cannot replace their experience and the fact that they have been working together as a team, and new team members always have to be onboarded, introduced to customs and policies ang it generally could take quite a long time for them to get up to speed.

Team Management 

Your search team should be an independent one from your core dev team – otherwise multiple projects running parallel will take time and capacity from each other – consequently both basic development and building/maintaining your search engine will have less progress made in the same time.

It Takes Years to Fully Develop Great Search

No matter what you do, basic development itself will likely take 1-1.5 years – and after that, adding extra functionality, customization, bug fixes, maintenance and updates will take years until your engine is fully formed. It’s essential that your team always stays up-to-date with e-commerce search best practices and continuously implements them.

Manual Infrastructure Setup and Maintenance

With no third-party partner or SaaS provider, you have to purchase, set up and maintain all the infrastructure needed for both development (tools and devices the team will use) and operating the search engine. In terms of resources, this means additional costs and time.

Continuous Performance-improvement, Monitoring and Optimization

You need to continually develop new features – the needs are going to be changing based on customer requests and competition, changing habits, alterations in your business model and a lot of other factors.

Lack of Up-to-Date Technology

Search engine development is a very specialized field, and most of the times you will not have relevant, fresh technology at your disposal to use – you have to do everything yourself, which will usually take months to accomplish.

No Support

With an in-house team, you can’t rely on outside expertise: if you hit problems, you will have to figure it out yourself or find the solution on dev forums – both of which can be time-consuming and frustrating.

SaaS Vendor eCommerce Search Solution


If you don’t want to hire and maintain a full development team, and still want a high-quality,flexible solution, your best option is to use a SaaS provider.

But you are going to have to be careful about which one you choose (see the comprehensive list above for the most important factors to look at when choosing a provider)-, because search-as-a-service is a highly specialized field where every vendor, every solution has their specific strengths and specializations.

Quick integration

When using a search provider, some offer integration within weeks, which means you’re up and running in no time.

Some SaaS site search providers have integration times that take months, though. 

So if you’re looking to get started quickly, check the timeline of each individual provider, along with their integration process, to see which best fits your needs. 

Proven ROI before commitment

You not only get better search in a shorter amount of time, but also get the opportunity to commit to a service that has history: case studies, testimonials to back up its effectiveness. The core features are going to be constantly updated based on data not only from your webshop, but from all the shops and clients the vendor has, meaning best practices could be implemented with a much greater effect.

Detailed Analytics

You are going to get a dashboard and likely options to customize the analytics and reports you get, meaning you will be able to implement any useful data in your sitewide marketing efforts and business model from day one.

Dedicated Customer Support

A team of experts will be at your disposal as a part of the service, and you don’t have to pay their salaries or for the tools and devices they use. You can also be sure that they are experienced in search technology and will likely have the answers you are looking for.

Fully managed search

You and your team will not be the ones who have to make updates, develop features, manage scaling or hosting: you can reach out the the SaaS vendor and simply tell them your needs.

Freedom in Scaling Along With Your Business

SaaS solutions are traditionally scalable: as your webshop and business grows, you can simply upgrade the service to fit your growing needs, from handling a larger amount of products to including more specialized, custom functions and options in the engine.

Predictable Cost

The expenses will be easy to integrate into your cash flow, and you are going to know exactly how much you are going to pay each month for the service – and if you need custom solutions, the price for developing and integrating them will also be set.

Disadvantages of Using a SaaS Vendor


No Real Control Over Development

As just one of the clients, you will have some say in what features have to be developed, what bugs are going to be fixed – but that say will be minimal. Their development team is going to focus on what the majority of clients and the market are demanding – which might not necessarily align with your personal needs

Important note: this is not the case with all vendors. Business models of SaaS can differ – notably, at Prefixbox we are developing features based on aggregated customer priorities. But this is not an industry standard.

Important note: this is not the case with all vendors. Business models of SaaS can differ – notably, at Prefixbox we are developing features based on aggregated customer priorities. But this is not an industry standard.

Operational Features to Consider


Free Trial

Before committing to any solution, you should be able to try it out beforehand. Always look for a free trial with ecommerce search solutions, because you are about to make a long-term decision. Also, make sure that your analytics is set up correctly, so you can track any changes in  user behavior, conversion rates, exit rates and all other important KPIs after launching the free trial.

On-going Optimization Support 

Don’t count on a moment happening when you can kick back and say, “well, we are done with site search”. As one of the most important elements on the site, intimately tied to user behavior and revenue generation, continuous optimization, fine-tuning, A/B testing and bug fixing will be a part of your routine. So make sure the solution you chose has the team to support these efforts and are available to help with whatever you need (in a quick manner!).

Analytics Dashboard 

A monthly PDF in your inbox will not be enough when it comes to site search analytics. Make it a point to have access to a live dashboard where you can not only see the most important data and changes of KPIs.

Data Centers, Uptime

Uptime is a critical factor: always check the location of your provider’s data centers along with their SLA to find out their policy  on uptime and redundancy. 

The best option is to work with a provider who has  their data center in the same time zone as your business, as this will help with potential latency issues.

What is their SLA?

Service Level Agreement 

Many important factors can be found in an SLA, for example the availability they vow to provide. 99% is the standard benchmark, but keep in mind that this is not all that good a percentage – if your site search works 99% of the time, it means that it is offline 7+ hours a month.

Monthly Cost

Monthly invoicing instead of a year-long commitment gives you both security and flexibility: you can expect fixed costs while also having the freedom to opt out of the service if necessary.

Occasionally, yearly invoicing comes with a discount – so be sure to check that out.

The Decision is Yours


Choosing a site search solution should not be a fast decision. There are a lot of factors to consider to give shoppers the best possible search experience – and also support any ongoing marketing efforts and your business model, to achieve the highest possible ROI.

If you have doubts, start with the comprehensive list above, and if you still have questions, don’t hesitate to contact us here in a comment or in emails, we are always happy to help with your decision.

Do your research before making a long term commitment, and keep in mind that what you go with will fundamentally decide the customer journey and shopping experience in your store!

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.

12 Best Machine Learning Strategies for eCommerce Businesses

12 Best Machine Learning Strategies for eCommerce Businesses

In today’s world of eCommerce, it’s impossible to run a successful online shop without leveraging Machine Learning.

Check out this article to find out how to incorporate Machine Learning into your
e-Business in these easy ways:

  • For price optimization
  • For search result optimization
  • For product recommendation
  • And many more

Let’s get started!

machine learning guide for eCommerce

Contents

Today, when global ecommerce sales amount to $4.88 trillion, it’s an innovator’s game.

According to Gartner, up to 80% of customer interactions are managed by AI today. 

Introducing AI into sales, marketing, even inventory management is both a natural next step in the evolution of commerce and an absolute must for those who want to keep up and make cost-effective decisions.

And in this article, we are going to show you how you could effectively be leveraging AI in your eCommerce business.

Let’s kick off with the answer to….

How machine learning works in eCommerce


If we want to define machine learning in the simplest terms, it is the study and creation of algorithms that can learn from given sets of data and extrapolate from those to predict trends and outcomes.

This is a necessary function of any algorithm-based system that has to deal with large, frequently changing data sets – from natural language searches (where wording, typos, and new phrases are common) to facial recognition (where the system basically never meets the same input twice, but still has to determine the key features). Machine learning is used in email filtering, weather forecasts, diagnosing disease and predicting socioeconomic trends.

eCommerce is a field in dire need of machine learning. Even a small webshop can create millions of relevant data points daily that a single human, or even a team of experts could never hope to fully comprehend and utilize.

But, a machine can do it. 

It will not only monitor these data sets, changes and trends in them, but make connections. 

An AI based on machine learning will reason. Deduce, based on experience.

For example, it can help with…

1. Pricing Optimization


Price is, unsurprisingly, one of the most important factors when considering a purchase. In fact, price is one of the major drivers for at least 47% of customers according to BigCommerce.

If your prices are high – or just higher than your competitors’ – your cart abandonment rate can increase, and even more so if you don’t set shipping prices correctly. If your store offers international shipping, you also have to display prices based on the location of the customer.

There are many other factors that may influence your prices – supply and demand, which promotions are running, what time of the day or year it is and so on.

Via machine learning, these factors could be assessed in a fraction of a second and your site will display dynamic pricing: showing the customer the most up-to-date price for them based on the aforementioned factors. 


This ensures prices are instantly understood (no “how much is that in my currency”, “does that include shipping” etc.), with no surprises, and no need for you to manually change them.

2. Segmenting, Personalization and Targeting Customers


In traditional brick-and-mortar stores, segmenting was done solely by salesmen, who approached the customers. By observing and asking a few questions, they could gather more than enough information about demographics, their needs and doubts, and their overall mood based on non-verbal communication.

This made it possible to immediately address any concerns about the products, matching the words and expressions used by the customer, being able to upsell them on the spot, and reinforcing their purchase intent.

When the customer has to deal with an online experience, all of this has to be replaced, and scaled. 

Segmentation has to be based on behavior that can be measured. 

And on-site search is a great place to start.

When searching, shoppers use natural language, which gives clues about their background and native language. Based on the results they click on, an algorithm can determine what they are looking for and offer more relevant results, which encourages them to make a purchase. 

And based on what other customers in the store previously bought, in conjunction with this particular search, cross- and upsell offers could be made with great confidence. Part of the demographic information is readily available as soon as someone signs up – most times you will know their age, location and whatever data you ask for. 

You can also monitor their behavior on your site – what content do they read, what materials do the download, how often do they return and how often do they make a purchase.  

You can also keep track of the kind of emails they open and when are they most likely to make a purchase during a day, a week or year.

There is an incredible amount of data generated from all these interactions – and machine learning is what makes it possible to assess behaviors to ascertain patterns. 
These patterns help you make sense of data sets and make more effective marketing decisions. For example, you can create ultra-targeted campaigns with the most relevant messages, and increase your conversion rate by offering customers exactly what they are looking for.

3. Search Results Optimization


Providing search results based on keywords is just the very first, most basic step in on-site search. In order to provide shoppers with the best experience possible, your search should go much deeper than that. 

Given a large enough data set, you could determine which results are better for people in certain locations, how to optimize search result filters, and which products best match their needs based on their previous behaviour.

By analyzing the data and figuring out what items go together, you can also recommend similar products, and even cross-sell items that are frequently bought together by your users. 

Machine learning is able to pinpoint the trends and patterns needed to automatically determine these.

Leveraging this leads to higher click-through rates on your results pages, higher conversion rates, and a higher average order value.

It’s worth noting that filtering results in real time based on user inputs, via faceted search, paired with AI-based recommendations is currently the single most effective method of providing relevant results.

But let’s stay for a minute with recommendations…

4. Product Recommendations


If you’re curious about how effective automatic product recommendations are, look no further than Netflix. According to McKinsey, 75% of what people watch on the streaming platform is suggested to them via an algorithm that analyzes user behavior. (The same is true for 35% of purchases at Amazon.)

You might think that determining which products go well together is easy – for example, simply track what people watch after they finish Futurama, and if it’s Rick and Morty, recommend that, and that’s it.

But you should also take into account the demographics – people in non-English speaking countries might go for movies and series in their native language with more enthusiasm. The preferences of young and older audiences will differ, as will the taste of those living in East Coast metropolitan areas versus those in rural European towns.

And this doesn’t even account for personal taste of genres, styles, lengths, eras etc. 

To be able to offer ultra-targeted products to your customer, you have to work with a very large number of variables, each weighed differently.

It is virtually impossible to do this without a machine learning algorithm – even if you have just a few hundred products.

As you can see, knowing your customers is a bit like predicting the future.

So, let’s spin up the crystal ball and see what exactly it can predict…

5. Predictions About Your Customers


Machine learning can tell you a lot of things about the people who visit your site and make a purchase – even things like how likely they are to buy from you again or what they might be interested in. 

Check out what machine learning can predict.

Customer Lifetime Value Prediction

To fine-tune your communication and messages, it’s useful to know how much money  a customer is likely to spend in your store over a given time period. 

If you can estimate a lifetime value based on behavior, you can also make your marketing more cost-effective and targeted. 

You can also identify customers who are the most valuable and deserve special attention.

Predicting if a customer will make a purchase

Imagine this: you have an online store for office supplies. You have a customer who orders the same amount of ink cartridges from you about every 6 months.

Let’s say 5 months pass, and this customer logs into your site, but doesn’t order anything. Logically, this could mean that they are checking the prices in order to budget the next order, or they might be comparing your prices to your competitors’.

As a store owner, you most likely will never learn that they’ve logged in and done this.

However, the AI will notice it. 

And it can deduce that this is the right time to provide a little incentive to increase average order value – as the customer is a returning, but hesitant one, maybe it’s time to fire up a workflow that provides them with a personal discount for their next order, thanking them for their loyalty.

Predicting customer return (and purchases)

If, based on their behavior, a customer is likely to return to your store later, then an entirely different marketing message may resonate better with them.

Algorithms can predict, on the long term, whether this is the case and can initiate longer workflows with messages that target loyalty and reinforce branding.

Customer churn prediction

Retaining existing customers is one of the most important tasks if you want to keep your marketing budget from bleeding. Acquiring new customers is much most cost-intensive.

A machine learning algorithm can determine which shoppers are the most likely to abandon your site – based on things behaviour such as: returning to your store less frequently, smaller purchases, etc.

When the AI realizes this is the case, it can initiate workflows targeted at retention, giving shoppers incentives to stay.

Client size prediction

Based on average order value and purchase frequency, along with other information like number of employees, and company type, an algorithm can estimate the size of the client for you.

This gives you great insight into deciphering which potential customers to pay special attention to. You can make more personalized offers and give them deals that are more cost-efficient in the long term.

As you can see, machine learning really tells your future by predicting what your customers will or won’t do.

Another forward-looking application of machine learning that deserves its own subsection is…

6. Site Search Autocomplete


A truly useful autocomplete has to learn, instead of scouring through different product attributes and description.

It has to understand the natural language of the users instead of the often technical and machine-like phrases of database entries.

Ecommerce search best practices dictate that online stores use an artificial intelligence-based autocomplete as it streamlines the shopping journey and provides shoppers with a sense of comfort as this is what they’ve come to expect. 

So, natural language processing and machine learning have to understand the kind of language and phrases your customers use, how often they use them, if the results are satisfactory for those phrases, and even common typos along with the correct spelling.

This way, every user can feel that the search engine is truly there to help and pays attention to the smallest details, all without being annoying.

Speaking of details…

7. A/B tests using AI


A/B testing is a powerful tool in online marketing, but it can also be tricky.

Let’s say you want to run an A/B test for a product page.

Firstly: what do you change? The display of pricing? The location of your CTAs? The background color?

You see, if you change more than one thing, you can’t really be sure what causes the next positive or negative change. 

But, if you change only one thing, the change may be so small it can’t even be registered.

And what KPIs should you track? 

Yes, conversion and purchase rate are the most obvious numbers to track. 

But time spent on page, number of clicks, and return rate are also important. 

Machine learning and AI makes this testing process easier:

  • Based on historical data, it decides which elements should be tested and automatically creates variants.
  • It can dynamically change page elements based on test results. For example, displaying pages differently for different demographics or locations.

It can find the optimal versions much faster, because it can take all the variables into account and find the connections between even small changes.

8. Chatbots for Automated Customer Support


With customer support, there rarely is an optimal choice. If you want to solve all issues with manpower, your support team will be huge and expensive – and not at all efficient, as many times they will be dealing with things that could be solved by redirecting the customer to an FAQ page.

On the other hand, you can’t completely automate support, because a lot of issues will require human assistance, and your customers will quickly get annoyed if they can’t get it.

On the other hand, you can’t completely automate support, because a lot of issues will require human assistance, and your customers will quickly get annoyed if they can’t get it.

The solution to this problem is often implementing a chatbot based on machine learning. 

These chatbots are able to maintain a conversation with the customer. Not only by using previously defined answers, but also via AI – they’re able to learn about natural language from every conversation.

Of course the chatbot will require time to learn, to get to know the products and services as well as the customers and their way of communication. 

It will never pass a Turing test, but it could, in time, identify opportunities for upsell, create customized coupons, and open tickets for humans in customer support to handle.

Keep in mind, however…

A professional custom chatbot can cost anywhere between $30,000 and $300,000, depending on the desired functionality.

Speaking about money well spent…

9. Inventory Management


You know how a smart fridge reminds you you’re out of milk and puts it on your grocery list for you?

ML does that for eCommerce, times a billion.

Well, a trillion actually, as around 7% of the US GDP (more than $1.1 trillion) is tied up in cash in inventory along with accounts receivable and accounts payable.

Inventory management and logistics is nothing to sneeze at in terms of complexity. 

If you run a successful online store, you have to monitor your stocks, reorder items, predict trends in demand, coordinate contractors, deal with manufacturers, suppliers, mailing services, and manage your revenues accordingly.

This is exactly the kind of job machine learning was made for. 

By monitoring all your inventory, and even predicting future trends in supply, demand and even cash flow, you can be sure that with AI, you won’t be the airline that overbooks flights or flies empty.

You will be the airline that plans their next year schedule with absolute confidence.

10. Omnichannel Marketing Boosting with ML


Let’s get the obvious out of the way: omnichannel marketing brings you higher retention and conversion rates and boosts your revenue. But only if you use the available channels wisely.

Of course, you could just hire a marketing team, where there are dedicated people for social, email marketing, content creation, and tell everyone to give it 100%.

But is there a better way to do it?

Actually, yes.

Analyzing the data your customers create when interacting with your activities on those channels is majorly important. 

Based on customer behavior – ads that perform well, content that’s frequently read, email open rates – machine learning algorithms can analyze your messages and display them in a way that ensures every customer gets the perfect one.

Online real estate became more important than television and radio partly because of how results can be tracked and campaigns can be optimized. 

ML is the natural next step in this evolution.

11. Image Processing and Recognition


Image recognition can be a great tool for an online store with thousands of products in their inventory. 

Ideally, it enables a customer to just upload a photo they snapped of a given product at home or at the store. The system then processes it on the store’s servers, and instantly displays a response with availability, current price, shipping info so the shopper knows where to buy it.

More often than not, this leads to a purchase as it’s the most convenient shopping method. 

Beauty.com, for example, was able to increase sales by 15% after implementing their visual search feature.

Another possible use of image processing is to give ultra-targeted recommendations. For example, processing a photo of the customer and then applying clothes available in store, so they can see how different styles would look on them.

12. Fraud Protection


Fraud is inseparable from commerce as a whole, and eCommerce is especially vulnerable. 

Online shopping offers huge opportunities for those who want to take advantage of automated systems, which is why it is important to have algorithms in place that can detect fraudulent activity.

Integrating a CAPTCHA is not enough. You also have to monitor behavior and look at how certain people use your site. 

Integrating a CAPTCHA is not enough. You also have to monitor behavior and look at how certain people use your site. 

With machine learning, you can identify repetitive patterns that don’t match with human behaviour; such as: filling in forms too quickly, opening dozens of pages for split seconds, entering multiple different sets of information rapidly at checkout, etc.

Conclusion


Introducing artificial intelligence in eCommerce processes is not something futuristic or even a highly complex task. There are applications and services readily available for most functions that have been developed by people over the past decade.

It’s not always cheap, but it’s worth the cost.

  • It will help you understand your customers and audience better
  • Increase your sales and average order value
  • Cut unnecessary work  
  • Give you deep insight that no human ever could

You don’t have to hand over everything at once to the machine of course. Start small. Implement a smart site search solution, start using recommendations based on machine learning – and get to the rest when you are ready.

But get moving, because the analogue methods are phasing out fast.

Balazs VekonyOnline Marketing Manager – Prefixbox

Balazs is an Online Marketing Manager at Prefixbox, a leading eCommerce site search solution. He’s a Budapest based marketing enthusiast, who’s interested in new technologies and solutions and believes in the power of search.

Algolia vs ElasticSearch: How To Choose The Best Site Search For Your Business [+2 Alternatives]

Algolia vs ElasticSearch: How To Choose The Best Site Search For Your Business

If you run an online business or a webshop, providing a seamless search experience for your customers is probably one of your main concerns.

However, choosing the right provider can be tricky as there are a lot of factors to take into account.

To help you make the right decision, we put this article together to:

  • Provide an overview of some of the most popular search solutions
  • Show different pricing models
  • Explain the pros and cons of different solutions

So, let’s get started!

Algolia vs Easticsearch site search comparison guide

Contents

Chapter 1

How do site search solutions work?

Chapter 2

Algolia vs Elasticsearch: what are the differences?

Chapter 3

What are some alternatives to Algolia and Elasticsearch?

Chapter 4

Site Search Solution Pricing Comparison

Chapter 5

Pros and Cons of the Site Search Solutions

Chapter 1

How do site search solutions work?


In essence, site search, as a whole, is the functionality that enables users of a website to search certain keywords and/or criteria and get relevant, ordered results from the site.

The functionality itself can greatly vary – on some sites, you will only find a search bar where you can write keywords, on other sites faceted search will guide you step by step, in real time, based on all relevant attributes.

The basic idea is the same as on Google, but the underlying mechanics can be vastly different. The way  individual site search engines interpret individual keywords and phrases, whether they can understand typos, which product attributes are weighed as more or less important, the speed, the functionality of facets and filters – all depend on how the site search solution.

Something important to note…

Most searches do not take place in real time. In general, a search engine will index the searchable content, create the possible results pages in advance, and display these when the search is performed, hence the great speed. 

However this also means that this index has to be updated regularly so that it takes changes into account and provides truly relevant results.

With other search solutions, such as with faceted search, the process is done in real time, based mainly on all the different attributes provided for the different results. This is of course a more resource-heavy, but also much more user-friendly solution than regularly updating the search index.

Now that we’ve gone over the basics or site search, let’s dive into a few of the site search solutions.

Shall we begin?

Chapter 2

Algolia vs Elasticsearch: what are the differences?


Algolia is mainly praised for its speed, easy implementation and excellent support. Typo handling and search analytics are some of the key features it offers.

In the case of Elasticsearch, the developer community values its powerful API, that it’s open-source and flexible.

What is Algolia?

Algolia is an on-site search engine that includes analytics. It enriches the search experience with Autocomplete,  filters, query suggestions and infinite scrolling.

For developers, it offers back-end API clients, front-end widgets, several integrations, a customizable relevance algorithm and extensive documentation. It is usually described as having a developer-friendly API and an extensive toolset for development.

Algolia is a more full-service search provider, but can still be built up further.

What is Elasticsearch?

Elasticsearch, by its own definition, is a “distributed, RESTful search and analytics engine”. The open-source solution offers various APIs and great search speed, and is widely favored by developers. It also has built-in analytics and is a fully managed Search-as-a-Service solution.

Elasticsearch is a basic search application, which developers can build a deep search on top of.

Hosting Services to Consider when Using Elasticsearch


AWS


Elastisearch is offered as a part of the Amazon Web Services as a fully managed search service, which means deployment is usually easy and fast, and security is provided by AWS. 

This makes it easier to develop and troubleshoot your own Elasticsearch based application in their environment and scale it as you need. 

Another strength of this offer is its cost-effectiveness: as with many SaaS solutions, you only have to pay for the resources that you actually use.

Elastic Cloud


You can also opt in for the Elastic Cloud managed service, which is compatible with not only Amazon Web Services, but also Google Cloud and Microsoft Azure.

The main advantages of this solution is its flexibility, as it is easy to configure and deploy (given you have experts for the job), it includes a lot of Elastic features like machine learning, Canvas, APM, workplace search, and it provides unified analytics. 

You also get backups, constant monitoring and ticket or SLA-based support as part of the managed service.

Chapter 3

What are some alternatives to Algolia and Elasticsearch?


In this section we are going to show you two options that you might opt for if Algolia or Elasticsearch is not suitable for you

  • Azure Search: a search solution by Microsoft
  • Prefixbox: a SaaS option with constant optimization and feature development with a focus on client needs.

What is Azure Search?

Azure Cognitive Search is a solution by Microsoft, and by its own definition, “the only cloud search service with built-in AI capabilities”. The aim of the service is to make search at scale easier and faster with AI.

It is based on the same natural language stack as Bing and Office, and includes the key features of auto-complete, geospatial search, filtering, and faceting capabilities, and also OCR, key phrase extraction, and named entity recognition.

What is Prefixbox?

Prefixbox is an  eCommerce search provider with products enriched with AI capabilities. The solution is composed of different modules, which make  it flexible and a suitable solution for medium to large eCommerce enterprises.

The modules are: Autocomplete, Related Searches, Semantic Search Engine, and Merchandising. These encompass features such as typo tolerance, advanced ranking,, thorough search analytics, and of course faceted navigation for enriched user experience.

Chapter 4

Site Search Solution Pricing Comparison


Every search solution has a different pricing model.

Here, we’re breaking it down based on what is available on each provider’s website.

Algolia pricing


Algolia offers three main options. They serve different volumes of searches, defined as units, where 1 unit equals 1,000 search requests.Your paragraph goes here.

  • A Free plan that will serve up to 10,000 search requests.
  • A Standard, $1.00/unit/month plan (with 20% off if you pay annually), including analytics.
  • A Premium $1.50/unit/month plan (with 20% off if you pay annually) with some advanced features including custom rules, merchandising and customization.

On their site you can also create your own custom package where you can set search volumes and the needed features for yourself.

Elasticsearch pricing


There are four main plans you can choose from with the Managed Elastic Cloud service:

  • Standard, $16/month, with the core security features and basic functionality.
  • Gold, $19/month, custom plugins and support during business hours.
  • Platinum, $22/month, with advanced security features, workplace search, machine learning, full 24/7/365 support.
  • Enterprise, with custom pricing, which includes endpoint protection, detection, response and event collection.

All these plans are available as a free trial, and you can learn more about the detailed functionality included in each one if you visit their site.

Azure Search pricing


Azure has many plans for smaller and larger businesses too, with a Free plan also available, with limited features of course. The prices are given as an hourly rate and per unit in US dollars.

  • Free: you get a 50 MB storage, 3 indexes per service and not much more – this plan is basically a demo version so you can test the service and decide which paid plan is ideal for you.
  • Basic: with 2 GB storage and  maximum indexes per service, it costs $0.101/hour
  • STANDARD S1: includes 25 GB storage (max. 300 GB per service) and 50 indexes per service for $0.336/hour. All standard plans have a scale out limit of 36 units per service.
  • STANDARD S2: Includes 100 GB storage (max. 1 TB per service) and 200 maximum indexes per service for $1.344/hour.
  • STANDARD S3: Includes 200 GB storage and 200 or 1000 indexes per service per partition in high density mode (max. 2 TB per service) for $2.688/hour.
  • STORAGE OPTIMISED L1: 1 TB (max. 12 TB per service) and 10 indexes per service for $3.839/hour.
  • STORAGE OPTIMISED L2: 2 TB (max. 12 TB per service) and 10 indexes per service. The pricing for this plan is custom.

As for image extraction, the basic and all standard plans are priced as follows:

  • 0-1M images – $1
  • 1M-5M images – $0.80
  • 5M+ images – $0.65

Prefixbox pricing


Prefixbox offers flexible pricing as they have no less than 6 plans you can choose from.

The first two plans are aimed at SMBs and include search analytics, on-boarding and technical support and front-end integration:

  • SMB S1, with 30-150k searches: €500/month
  • SMB S2, with 150-300k searches: €840/month

The three Prefixbox plans aimed at larger stores include, in addition to the features of the SMB packages, A/B testing, 24/7 technical support and API integration.

  • Corporate C1, with 300-450k searches: €1,260/month.
  • Corporate C2, with 450-650k searches: €1,680/month.
  • Corporate C3, with 650k-1M searches: €2,320/month.

The last plan is a custom enterprise offer, which includes an enterprise-level SLA, a dedicated account manager at Prefixbox, an expert team responsible for integrating the search solution, commercial TOS and priority custom feature requests for the client stores. 

The pricing for this  is custom, you can ask for a quote on the Pricing page.

If you’re not sure how much you should be spending on a site search solution, you can use this calculator to see how much revenue an optimized search will generate.

Or you can request a demo and talk to an expert about your search needs.

Chapter 5

Summary: Pros and Cons of the Site Search Solutions


Since we covered so much information, check out this quick list of pros and cons of the four site search solutions to get a simple overview of the core features and functionality.

Pros of Algolia

  • It’s fast and easy to implement.
  • It has excellent support.
  • The underlying technology is modern and easy to handle (for experts).
  • It can handle typos, which is one of the most important search engine functions.
  • It also provides detailed analytics.

Cons of Algolia

  • According to some developers, the documentation could be problematic and thus hard to work with because sometimes it is incomplete.
  • Algolia is one of the more expensive solutions, so it is usually not the best choice for small businesses. 
  • Scaling can be difficult.
  • Customizing the ranking with Algolia is not perfect, as it is based on prioritizing factors instead of weighing factors individually.

Pros of  Elasticsearch

  • It is generally considered easy-to-use.
  • It is well-scalable – easily managing Terabytes of data (given the technical conditions are in order.
  • It can handle complex keyword searches very efficiently.
  • Analytics is usually listed as one of the greatest pros as it provides a thorough overview of user behavior and search data for its clients.
  • With APIs based on REST, an HTTP interface and schema-free JSON documents, its relatively easy and fast to build different applications based on it for a variety of use-cases (including, in addition to on-site search, processing genetic data, managing and analyzing spatial information, modeling data behavior etc.).

Cons of Elasticsearch

  • In reviews, developers list a number of cons for working with Elasticsearch, such as occasional lack of documentation, debugging issues, and a steep learning curve.
  • Because of the pricing, it is not an ideal choice for small businesses.
  • Support is not always proactive and some developers noted that community support is more efficient than the one the company provides.
  • Switching between different versions and  configuring it can be tricky even for experienced developers. 

Pros of Azure Search

  • It can be seamlessly integrated with Azure Cloud, making it an ideal choice for clients who already use the Microsoft cloud service.
  • It provides a fully-managed service for loading, indexing and query content.
  • Cognitive search capabilities enrich not only the search experience, but also make it easier for the client to get in-depth analytics and data.

Cons of Azure Search

  • As a primarily enterprise-level product, it requires a larger budget.
  • It works well primarily with Microsoft products, can be tricky to integrate with other ecosystems.
  • Implementation requires experienced team members on the client side as for non-technical administrators this is a nearly impossible task.

Pros of Prefixbox

  • AI powered search provides a seamless search experience.
  • The faceted real-time search makes it easier for customers to find the products they are looking for on the site and improves their overall shopping experience.
  • Prefixbox is constantly releasing new features catered to eCommerce retailers.
  • Contains a full suite of products focused on increasing eCommerce revenue and conversion rates. 

Cons of Prefixbox

  • It’s not an ideal solution for SMBs where there are less than 30 000 searches performed on a website per month.
  • Does not include content search functionality.

A final few notes before you make your choice…


Pricing can often be complicated, so make sure that you correctly calculate prices based on your needs. 

Never make a final decision before consulting with the technical people on your team. Developers can encounter or even foresee many issues that others can completely miss.

Always look at the availability and proactiveness of support: site search solutions can be a bit complicated, and it can make a fundamental difference if you are able to get expert help when you need it.

And lastly: before making any final decision, always look up reviews from real clients who actually use these products: get first-hand information on their experience instead of reading general product reviews!

And as always, if you have any further questions, feel free to comment or contact us: we will be happy to help you with additional info!

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.

Can Shopper Searches Help You Write Sales Copy?

Can Shopper Searches Help You Write Sales Copy?

If you work in the eCommerce industry, you should be familiar with the value of reviewing user searches when it comes to adapting your store’s UI.

Find out what shoppers are searching for and you can put the most profitable in-demand products front and center, save people time, drive more conversions, and generally improve store performance for a negligible time and design investment.

Let’s go

And of course there’s clear value in determining your product range, too.

If your prospective customers are heatedly clamoring for an item that you don’t have in stock (or don’t stock at all), then you can take action to meet those needs.

But what else can you achieve by looking at how shoppers are searching for things? Can you, for instance, use that information to improve your product copywriting?

That’s what we’re going to investigate in this piece. Let’s review the kinds of things you can glean from searches, and consider to what extent you can use them to boost your writing.

The Complexity of a Search String


What’s in a search string? As it happens, quite a lot. Search engines have long struggled to parse searcher intent for a reason: it’s very complicated and much of the information is unavailable (and thus can only be guessed).

Just think about the factors that can affect how a search string is composed:

  • The brand awareness of the searcher
  • The vocabulary of the searcher
  • The presence of autocomplete or autosuggest options
  • The existence of products with similar presentations
  • The context of the search
  • The device being used
  • The input method

And that’s just a basic list — I’m sure I could drum up some more. Regardless, there’s clearly a lot to unpack.

If you approach your search analytics with a keyword-obsessed mindset, you’ll end up missing a lot of nuanced details that can give you meaningful pointers.

Let’s look at an example search to see how we can interpret it.

Suppose that you look into your store’s search records and find that someone searched for “buy book store”.

What could that mean? Well, let’s break it down. Buy has imminent purchase intent, so that part is entirely clear.

The next part is more ambiguous, though, because there are several possible readings:

  • They want to buy a book from a store (ideally yours).
  • They want to buy a book about stores, or about a particular store.
  • They want to buy a book about storage, or how to store things.
  • They want to actually buy a store that sells books.

These aren’t equally likely, of course.

Anyone interested in a book about a particular store would name it, someone interested in buying a business would be looking into businesses for sale through dedicated marketplaces, not eCommerce stores, and I don’t imagine many people would think to refer to bookcases as “book stores” — but the point is that they’re possible.

Here are some to get us started:


Are more of your searches very succinct, the kinds of search strings that you’d tend to get from savvy internet users? Think of bare-bones searches reduced to keywords.

“Buy pizza two toppings dessert” might be how someone would search for a place to buy pizza with two toppings and a dessert, for example. Alternatively, are your searches closer to natural English?

The less artificial the phrasing, the more likely you are to be dealing with people who aren’t all that comfortable with online searching.

There are places in the world where a pizza can be referred to as a pie and other places where the two are viewed as completely different.

By looking at your searches, you can get a comprehensive view of the terms your visitors are favoring, and discern patterns and relations. 

Your primary keyword for a page might not be the most common term — which would be a problem.

When searchers feel the need to narrow down their searches, they add to the strings, and the way they do this can tell you a lot about what they prioritize, and in what order.

For instance, “buy pizza within 30 minutes three toppings money back guarantee” says something slightly different from “buy pizza money back guarantee three toppings within 30 minutes”, because people will generally place important things first — though be sure to take standard adjective ordering into account, because it plays a huge role.

For instance: “buy pizza within 30 minutes three toppings money back guarantee” says something slightly different from “buy pizza money back guarantee three toppings within 30 minutes”, because people will generally place important things first — though be sure to take standard adjective ordering into account, because it plays a huge role.

Each one of these things requires no additional context to be useful and can be looked at quickly and easily (provided you have the right kind of search system in place). Now, onwards to the titular question — how can this help?

How Site-search Info Can Improve Your Sales Copy


Your sales copy is anything you write for the prospective customer during the sales funnel, created to drive them towards the next step: one step closer to making a purchase.

In the case of organic traffic, it starts in earnest the moment someone reaches your website — if you’re running PPC campaigns, it starts with the ads.

And while there’s a lot of room for creativity with sales copy (though adhering to the classic formulas, since concepts like selling benefits instead of features have been successful for a long, long time), there are certain things you must do, such as ensure that you make your best effort to match the language of your users.

After all, it doesn’t really matter how you prefer to talk or refer to your products — you’re not the prospective buyer, and your opinion isn’t significant.

People like their specific needs and styles to be catered to, particularly when it comes to search.

If someone is going to sell you something, then they should at the very least understand some basic things about you.

When the time comes to freshen up one of your product pages, take a close look at the search history for it, and compare that information to the existing copy.

When the time comes to freshen up one of your product pages, take a close look at the search history for it, and compare that information to the existing copy.

Are there keywords in there that don’t exist in your copy?

Descriptors that you never mention, even if you can actually adhere to them? Terms, explanations and tips likely to go over the heads of your searchers?

This isn’t about thinking less of your prospective customers. In the end, it’s about making sure that as few people as possible are driven from your sales funnel by a style of writing lacking appeal.

You’re never going to have copy that’s perfect for everyone, but you can flesh it out to the extent that no buyer-intent searches go wasted.

Patrick FostereCommerce Consultant

Patrick is a writer and eCommerce expert from Ecommerce Tips. Much of his time goes towards blogging about the latest developments from the eCommerce world. For updates on the latest events, head to the ET Twitter @myecommercetip

10 Easy Search Box Optimization Methods for eCommerce Sites

10 Easy Search Box Optimization Methods for eCommerce Sites

The search box has a big impact. It generates 50% of eCommerce stores’ revenue. Even though it’s important, it’s often overlooked. People implement an open source search box on their website and don’t think about it again, but this can lead to missed revenue opportunities.

By spending a bit more time optimizing your search function, you will see a measurable increase in revenue.

search box optimization for eCommerce

If you’re ready to start increasing your online revenue, start by making these 10 changes to your site search function.

The strategies listed below are incredibly powerful in enhancing your customers’ experience and improving your conversion rate.

So, let’s get started!

1. Position Your Search Box at the Top of The Page (Be Sure to Test the Placement)


Your website visitors should be able to find your search box easily; they don’t have the patience to scour your website in order to find it. The search bar should be the first thing they see, so those who come to buy a specific product can easily express their buying intent by typing in exactly what they want to purchase.

Be sure to test the placement of your search box to ensure it’s optimized to get the most use! If top of page placement isn’t getting much use, try placing it in the middle or on the left, if this makes it more noticeable.

You can monitor your search box usage by checking the On Site Search Report in Google Analytics. Be sure to collect data for each change you make to ensure you’re continually improving.

2. Make the Search Bar Large and Distinctive


Your search box should be large and distinctive so it’s easy to find — when more people use the search box, browsers are more likely to become customers. Make sure users can tell your search box is a search box (don’t place it near other input boxes) and include some text in the field like “Search” or “Enter products here”.

large and distinctive search bar on Sears

A large search box means that users can see long search queries as they type. Short search boxes often eclipse the full text as there isn’t space to display all the characters, which increases the rate of misspellings and the frequency of 0-results pages.

Search boxes are usually about 245 pixels wide, but for those with a small display, we recommend you implement a search box that expands to contain user’s full queries.

3. Include Text Such as “Product Search” “Type search and click Enter” in The Search Box


Provide prompts in the search box so users can easily recognize which fields are acceptable for search. Most search engines allow you to search by item number, so text saying “Search by item number” can be helpful.

Placing text in the search bar, can also be a way to express your company’s personality or to make the online shopping experience more personal.

"Search by name, keyword" text included in the search box of Lowe's

Lowe’s places a handful of hints (see above) in the search bar, which is placed prominently on their site.

Make sure your text prompts are in a large, clear font so people can easily read them. While it’s good to include these prompts, they should disappear when users click in the search box so it won’t interfere with their search terms.

This is usually dictated by a piece of JavaScript, so once you implement it, make sure to test it works correctly

4. Have Autocomplete in Your Search Box


Autocomplete suggests products and keywords to users as soon as they begin typing. It completes the user’s thoughts by finding the right keyword before they finish typing and can be exceptionally helpful for hard-to-spell search terms.

It helps users save and effort, since they can navigate to a product with just a few keystrokes and a click. Autocomplete also helps prevent typos.

Search Autocomplete on Best Buy

Autocomplete can either recommend keywords or specific products that take users directly to that product page (skipping the Search Engine Results Page). In order to do this, Autocomplete must be enhanced with data from your site.

With this data, it can recommend popular products as soon as users click in the search box as well as display product titles, images, descriptions, and price (including sale price).

5. Have More Keyword Than Product Suggestions


Simply because keywords suggestions are more important than product suggestions. Users are more likely to click on keyword suggestions since these will direct them to a SERP with many relevant results where they can browse to find something they want.

Product suggestions are almost too specific for most people because it takes them directly to a product’s page. These are especially helpful when people know exactly what they want to purchase.

For example, if someone searches “outdoor paint”, keyword suggestions will take users to a SERP for outdoor paints, where they can browse through colours and brands. While if they select a product recommendation that states the brand, colour, etc. they will be directed to that one page. Keyword suggestions appeal to a wider audience, thus it is more useful.

Autocomplete can also suggest categories, but this is usually not very helpful (you can find more nuanced best practices and explanations like this here). When you set up your web shop, you probably nested products under different categories and the chance that a search user could accurately guess the name of one of your categories to find a is slim.

For example, if you have an “iPhone 7” listed under “technology” and a user searches the category “cell phones” on your site, the phone won’t appear, which could cause the user to leave your site.

6. Label the Search Button and Allow the “Enter” Key to be Used to Execute the Search


Clearly label the search button with text like “Search”, “Find”, “Go”, or with an icon of a magnifying glass, which has become synonymous with search.

In addition to clearly labelling the search button, let the “Enter” key serve the same function. Many people use the “Enter” key to execute commands, so it’s best to accommodate this expectation. Since search user’s hands are already on the keyboard, this is faster and easier for them.

7. Keep the searched term in the box


Once a user has executed a search, keep their query visible in the search box so they can easily edit it. Sometimes people like to add a few terms in order to specify the initial query or correct a typo.

This is especially important for searches that end up on “no-results found” pages. Instead of forcing shoppers to re-type a query (oftentimes they don’t remember the initial search that lead to the “no results” page), keeping the keyterm in the search box enables them to easily make edits or finetune their search to help them quickly navigate away from the “no results” pages.

Search term fits in search bar on Ikea Online Store

Even in the cases the executed search yields results, keeping the search term in the box helps shoppers refine their query to find exactly what they’re looking for.

8. Place a Search Box on Every Page


By placing your search box on every page, you increase search usage since web visitors won’t have to navigate back to the home page to use it. Be sure to keep it in the same place on each page, so users know where to find it.

This means that it should be prominent on your homepage and should stay in the same place on your category pages, Search Engine Results page, and even on product pages.

By keeping the search bar on every page, you gives shoppers the opportunity to quickly (and easily) refine their search, so they can find what they’re looking for.

9. Place a Search Box at the Bottom of The SERP


By placing your search box on every page, you increase search usage since web visitors won’t have to navigate back to the home page to use it. As we said, keeping it in the same place on every page is beneficial so shoppers don’t have to look for it.

But in addition to that, place it at the bottom of the SERP as well – or make it “sticky”. This way, shoppers who land on the SERP, but realize they need to refine their query after looking through the results page – can easily update their query without spending time scrolling back to the top.

Sticky search bar on Walmart.com

10. Show Search History


Personalize your online store by storing visitors’ previous searches and using them as recommendations when they revisit your site. Previously searched query prompts help them pick up where they left off. Asos does this nicely and in general has a great search function.

Search history in search bar is the part of the personalization

If you do add this feature, include simple controls so users can delete previous searches if they wish. Be sure to put previously searched terms in a colour different to regular suggestions, so users can quickly discern what’s what.

By increasing your search box’s visibility and making it more user friendly, people will be more likely to use the search box, which takes them directly to the product they’re looking for, so conversion rates will increase.

If your search box is up to date, here are a few tips to optimize your search results page.

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.

6 Ways to Improve Product Findability in eCommerce Stores

6 Ways to Improve Product Findability in eCommerce Stores

Wouldn’t it be great if your customers always find the product they’re looking for on your website?

And wouldn’t it be excellent if your web store was so easy-to-navigate that your clients recommended it to everyone they know?

To achieve this, you have to improve the Product Findability and this article will help you do just that.

To improve Product Findability, you should focus on specific elements of visual sorting. There is a long list, but every aspect is important:

  • Applicable filters in the menu
  • The search function
  • Friendly URLs
  • New arrivals, discounts, and featured products
  • Related products
  • Product comparison

Some of these may seem obvious, but many online retailer don’t know how to optimize them in order to improve user experience.

Now, let’s take a closer look at all these features!

1. Applicable Filters in the Menu


Not all shoppers know what they want; many just browse an eCommerce website to find if a certain type of product is sold there.

So, why not help them narrow their search according to what they’re searching for?

A faceted filtering system that offers specific options on the Search Engine Results Page will help your customers easily find what they want.

Another issue is category-specific filters. Most online retailers don’t use them and thus they end up restricting their customers’ choices.

Applying these filters will show your customers that you know your product and think about what interests your clients, which results in a higher conversion rate.

Amazon's Product category filters in site search

Here’s another tip.

If you have hundreds of products for sale, it can be a real pain for you to check how they display on your site.

2. The Search Function


Nearly a third of all online shoppers prefer to use direct search instead of just browsing. So, it is vital to create a well-functioning search bar with autocomplete to help users find what they want without the unnecessary surfing.

Etsy has a full width site search bar

But just creating a smart search is not enough. The bar itself must be visible and easy-to-use; put it on the top of the page and highlight it, so users can easily find it!

3. Friendly URLs


Some visitors use URLs to understand their location, so if the product URLs on your site consist of masses of strange symbols, you will quickly confuse shoppers.

In order to make your web addresses friendly be sure to describe the essence of a page or product.

Break the URLs down into easily understandable sections so shoppers can use it to navigate.

Navigation friendly URL structure for eCommerce sites

4. New Arrivals, Discounts, and Featured Products


People don’t always search for a specific product, sometimes they want a special offer.

For example, “New Arrivals” and “Discounts” sections show your site’s visitors what is new in your store and what’s being sold at the best price.

A “Featured Products” section will drag the clients’ attention to various offers like the products on sale, “back-in-stock”, seasonal products, or just show the most popular goods.

New Arrivals, Featured Products and Discounts on homepage

The number of possibilities is endless and you can create your own categories. When doing this, be sure to think about how to improve your customers’ experience.

For example, you may use a “Most Viewed” widget to display a page with the most popular items. Or you can create a “Most Wanted” widget where you display the products most frequently added to carts. You can choose what your customers see first and second.

5. Related Products


If your client is already interested in buying a product, why not offer something that goes well with the item they’ve chosen?

A Related Products feature will do just that!

Related products on Amazon

A clients’ search history will tell you what they like, which you can use to offer them suitable complementary goods.

A Related Products section provides many opportunities for cross-selling, so products, based on personal preferences, listed here are more likely to be bought.

But don’t be too persistent – you should help shoppers make a decision, not choose for them.

6. Product Comparison


Shoppers love to compare products and prices because this helps them make an informed buying decision.

Having comparison tools will positively influence the user experience and help shoppers decide what to purchase, which increases your conversion rates!

Similar to the situation with the search box, simply implementing a comparison tool is not enough.

Detailed Product Comparison on eCommerce Sites

You need to make it easy to see and use. The following tips may help you:

  • Make the compare button noticeable
  • Display customer reviews and ratings
  • Allow comparison on search pages
  • Thumbnails should be clickable and large when they are being compared
  • Make editing and removing products intuitive

In conclusion


Visual sorting plays a crucial role in eCommerce since products that are presented well have a higher selling rate.

Visual sorting helps you direct your clients’ attention and gives you the opportunity to show them products you think will satisfy their needs.

Just don’t be overly assertive and be sure to respect your clients!

Let them decide what to buy – your task is just to help them.

Balazs VekonyOnline Marketing Manager – Prefixbox

Balazs is an Online Marketing Manager at Prefixbox, a leading eCommerce site search solution. He’s a Budapest based marketing enthusiast, who’s interested in new technologies and solutions and believes in the power of search.