Conversion boost for Thr.nl using website personalization

We already know that offering personalized product recommendations in any online shop increases sales. Nowadays, the biggest challenge is knowing where and how to place product recommendations within the shop in order to maximize revenue. That’s where the experts from Retail Rocket come in.

Retail Rocket provides more than 1000 clients worldwide with a personalized, multi-layered service, from initial assessment right through to final implementation. And they do this while performing tests every step of the way to ensure that they get the best possible results. Nobody else in the world can do this!

Read on to discover how Retail Rocket’s growth hacking team used their expertise to help Thr.nl to optimize recommendation algorithms and block placements and significantly increase their conversion rate.

About THR

THR is a Dutch wholesaler of DIY products and professional building materials. The company was created in 2011 by a joint venture of three renowned wholesalers. Its website offers a huge range of over 80,000 products and brands. So a personalized customer experience is indispensable. THR takes a personal approach to its customers and want them to experience this in every interaction.

Product page recommendations increased conversion Thr.nl by 25.6%

Retail Rocket added real time recommendations to the product pages of Thr.nl. Users of the website were shown similar products and related products based on the product that they were viewing at that very moment.

After that, Retail Rocket growth hacking team performed an effectiveness A/B test to find out how these recommendations influenced Thr.nl’s conversion rate. To do this, the users of the product page were randomly split into five groups:

Group 1: Users who were shown similar products. These recommendations were based on product properties (price, brand, category, text description, etc.) and collaborative filtering (what other customers also viewed and/or ultimately bought, etc.). E.g.:

Group 2: Users who were shown related (or complementary) products from categories other than the category of the item currently being viewed. This is based on products database analysis and visitors’ behaviour (carts, orders). E.g.:

Group 3: Users who were shown two blocks:

• Similar products, positioned on top
• Related products from categories other than the category of the item currently being viewed, positioned right below the item’s description

E.g.:

Group 4: Users who were shown the same two blocks as in Group 3, but in the opposite order:

• Related products from categories other than the category of the item currently being viewed, positioned on top
• Similar products, positioned right below the item’s description

Group 5: Control group who didn’t see any of the recommendations.

Conversion growth and more loyal visitors

The A/B test demonstrated a 25.6% conversion growth within group 3 (users who were shown two blocks: similar products and related products from the same category as the current product) with 100% statistical significance.

Furthermore, Google Analytics showed that the product page recommendations generated more sessions, resulting in more users returning to THR’s online store. 

Additional conversion boost with category page product recommendations

Retail Rocket team added product recommendations to the category page of Thr.nl, so that users saw the most popular products from each category of the website. By using smart profiling technology, different segments of the users were showing different products.

An A/B test was conducted to find out how effectively the product recommendations block on the category page increases the conversion rate of Thr.nl. Statistically significant differences in the conversion rate were also tested by presenting three different recommendation blocks:

• Without a slider
• With a standard slider
• With a slider that scrolls automatically after 10 seconds.

Category page users were randomly divided into four groups:

• Group 1: Users who were shown a recommendations block without a slider. E.g.:
• Group 2: Users who were shown a recommendations block with a standard slider. E.g.:

• Group 3: Users who were shown a recommendations block with a slider with automatic scroll after 10 seconds. E.g.: (Same image ‘group 2’, but with automatic scroll)
• Group 4: Control group who didn’t see any of the recommendations.

Recommendations on category page boosted conversion by 8.4%

The A/B test showed that with the use of a recommendations block without a slider, the online shop achieved an 8.4% higher conversion, with a 98.6% statistical significance.

Conclusion:

Retail Rocket helped THR to set up the most efficient self-learning algorithm based on big data analysis in real time. Their unique real-time personalization technology increased THR’s conversion by 25.6% and 8.4% on the product and category pages respectively. And they did it without the need for extensive IT resources and a time-consuming implementation period. Only Retail Rocket’s growth hacking team has the knowledge, expertise and technology to offer such a comprehensive service.

Comments from THR:

“THR chose Retail Rocket at the time so that we could quickly make relevant recommendations to our customers. Through the working method of Retail Rocket, all data could be interpreted fairly quickly and accurately. This has resulted in suggestions that are relevant to our customers, which facilitated and accelerated their ordering process.”

Krista Gerhartl – Manager E-commerce

Questions?

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