Retail Rocket Growth Hacking helps to achieve 31.7% revenue increase

Retail Rocket Growth Hacking helps to achieve 31.7% revenue increase

In this case study we review the results after Retail Rocket implemented their unique recommendation algorithms on’s product page.

Van Asten BabySuperstore is one of the biggest Dutch retailers for parents and babies. Their brick and mortar store has more than 5,000 m² and the online shop offers a huge range of products and brands in different categories.

Visitors can easily get lost in such a vast range and need help to find the right products in the online shop. Retail Rocket provides personalized product recommendations in real-time to help visitors navigate the online shop. These recommendations automatically reflect and leverage any changes in behavior, helping’s visitors to find the products they need quickly and with very little effort. Then they will be more likely to make a purchase, resulting in a significant increase of the conversion rate.

Recommendations on the product page

The product page is a critical decision-making point for potential customers, making it exceptionally important to show each visitor the products that they are most likely to buy.

If a visitor lands on the page of a product that does not fully meet their wishes, it is useful to recommend similar products to them. By doing this, it maximises the probability that visitors will find the products that they are looking for. Recommending related products can also motivate users to add complementary products to their purchase cart, resulting in an increase of the order value. The combination of these two approaches can significantly boost the growth of an online store.

Which type of product recommendations are the most effective?

Every online shop is different. So it is not always easy to find out what kind of recommendations will work the best. Therefore, performing an efficiency analysis with the Retail Rocket Growth Hacking team was the best way to identify the most effective algorithm for

The product page users were shown either related products, similar products or both related and similar products, arranged in two different orders. The conversion rate in each group was monitored and analyzed by means of an A/B test.

The online shop visitors were randomly divided into five groups:

Group 1: Visitors who were shown similar products. Similarity is based on product properties (price, brand, category, text description, etc.) and other customers behavior (what others also viewed, what others ultimately ended up buying, etc.).

Group 2: Visitors who were shown related products from categories other than the category of the current product.

Group 3: People who were shown two blocks:

⦁    Similar products, positioned on the top.

⦁    Related products from categories other than the category of the current product,  positioned right below the similar products block.

Group 4: People who were shown two blocks:

⦁    Related products from categories other than the category of the current product,  positioned below the item’s description, positioned on the top.

⦁    Similar products, positioned right below the related products block.

Group 5: Control group, who were not shown any recommendations at all.


The A/B test showed the following results:

Conversion rate AOV Revenue
Related products above similar products vs control group




31.7% Revenue boost

The product recommendations on’s product pages were a big success. Every group that was shown product recommendations was more likely to make a purchase than the control group. However, after achieving a 11.4% conversion growth with a statistical significance of 92.2%, group 3 had the most successful recommendation algorithm: “visitors who were shown related products above similar products”. Besides this,  this mechanic also led to a higher average order value, smashing the predicted results with 31.7% more sales revenue.

Retail Rocket’s efficiency analysis showed that recommending both similar and related products on their product pages would help their business grow. is already making use and taking advantage of the algorithm on their online shop and will continue to see the unique benefits in the months and years to come.

Comment from Van Asten BabySuperstore:  

Retail Rocket helped us to make our online shop more personalized and our product range more relevant to all customers.  The personalized content contributes to a shopping experience with the focus on attention for the consumer. Moreover, through A/B tests Retail Rocket demonstrated that personalized product recommendations on the product page contribute to a better converstion ratio and higher order value.

Pim Brackenie, Operational Manager at Vanastenbabysuperstore



Do you have any questions about this case? Please contact us.


Post precedente

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

Post successivo

ToolMax’s product page Growth Hacking: over 10% revenue growth

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