Personalized product recommendations at ELC store: more than 10% revenue growth


Early Learning Centre (ELC) creates toys aimed at helping children to develop vital skills. ELC opened its first store in the mid-1970s. Now it has expanded to 150 stores in the UK, plus 80 more in 19 countries worldwide and an online store.

In 2006, the company launched their online store in Russia, The store reaches over 260,000 visitors per month and provides a wide range of products.

Product recommendations on

Customers have ever higher expectations from online shopping. When exposed to a large variety of products, customers want to be shown personalized offers that match their preferences. If the expectations aren’t met, the online store may lose their customers’ loyalty and their business. That’s what drove’s desire to provide product recommendations.

In this Case Study, we will show how personalized product recommendations helped to increase their conversion rate. Retail Rocket implemented recommendations on the category and product pages and analyzed their efficiency with A/B testing.

Case 1. Efficiency analysis of product recommendations on the category page

Up to 90% of all online shoppers visit the category page, so showing product recommendations on this page is advantageous. It helps customers to navigate through the available products and find what they need with a minimum of effort.

Product recommendations were added to’s category page and an efficiency analysis was conducted by randomly splitting visitors into two groups:

1. The first group was shown the category best-sellers. This was the control group:

2. The second group was shown personalized product recommendations from the current category, based on the browsing history:


The A/B test showed the following results:

Conversion Rate change

AOV change

Revenue change

Control group

Personalized best-sellers





The A/B test demonstrated that using Retail Rocket product recommendations on the category page improved the conversion rate by 12.5%, with a statistical significance of 94.9%. Even taking into account a slight drop in average order value, revenue can be expected to increase by more than 10%.

Case 2. Efficiency analysis of product recommendations on’s product page

When on the product page, the user is much closer to making a purchase than on any other page.The recommendations should attract the users attention without distracting them.

To find the most effective configuration of recommendation blocks on’s product page, Retail Rocket performed an efficiency analysis.

All visitors were randomly divided into four groups:

1. The first group was shown similar products (based on the product properties: price, brand, category, text description, etc.)

2. The second group was shown related products (complementary items based on the products database analysis and website visitors behaviour: carts, orders).

3. The third group was simultaneously shown two blocks: similar products positioned above related products.

4. The fourth segment was also simultaneously shown two blocks:related products positioned above similar products.


The A/B test showed the following results:

Conversion Rate change AOV change Revenue change

Control group

Related products




Similar products above related products



Related products above similar products





Using a product recommendation block displaying related products in a row above similar products increased the conversation rate by 10.8%, with a statistical significance of 96%.

Even taking into account a slight drop in the average order value, Retail Rocket recommendations platform led to a revenue boost of 7.7%.

Knowing what customers are looking for and presenting it to them clearly allows an online store to meet their customers’ expectations. With Retail Rocket’s help to provide a personalized experience, stores will be able to flourish in an increasingly competitive online shopping environment.

Comment from “”

By showing our customers the relevant products that may interest them the most, we try to make the process of choosing products as convenient as possible. Personal product recommendations that we implement on the different website pages cope with this task perfectly. This helps us to increase not only the loyalty of our customers but also the average order value and the revenue of the online store. The Retail Rocket team is always ready to support our ideas and actively offers testing of various algorithms to improve the conversion rate and the financial performance.

Saveliev Nikita, director of the online store

Website personalization technology and triggered emails are now available to everyone!

Demander une démo