Home Case studies Designing the homes of Black Red White’s customers

Designing the homes of Black Red White’s customers

Black Red White has been actively present on the market for 25 years now and has been constantly offering a comprehensive selection of furniture and home design articles. The company has also successfully developed an online sales channel – the www.brw.com.pl store is currently reporting over 2 million entries monthly. The brand has decided to start using cutting edge solutions that allow for earlier product search methods and make the purchasing process more efficient.

Black Red White sales target:

  • presenting a personalised offer
  • allowing the customers to find a product as fast as possible
  • offering product recommendations and encouraging customers to buy more

How does the QuarticOn recommendation system work?

QuarticOn is a professional system that creates personalised recommendations. Based on advanced AI self-learning algorithms, it presents a different version of the shop to every individual user. The version is in line with the preferences of users and offers products that match their expectations.

QuarticOn:

  • analyses the interactions between every unique user and the shop – simultaneously, it finds new product relations and behavioural patterns
  • collects and processes behavioural data
  • builds a knowledge base about the needs and preferences of every user
  • displays in real time an individually prepared offer for every unique user

Recommendation strategies in Black Red White

The www.brw.com.pl shop has implemented over 10 recommendation widgets that, depending on their position, have boosted the conversion rate and the size of the cart.

Personalised recommendations – a growth in sales figures of 8% per month.

A customer who visits a shop has a defined need that will be fulfilled by a particular product. The first actions taken by the user are analysed by the recommendation mechanism which then learns the expectations of the customers through their further activities. In turn, it can respond with a Recommended for you personalised recommendation list.

In the case of Black Red White the widgets have been placed in the home page, the category pages, the zero search and empty cart pages.

Recommendations based on the experience of other users – 5% increase in sales.

Customers who are browsing through the shop can see the recommendations that have been created based on the experiences of other users. The Products you might find interesting recommendations are based on the actions of previous customers, who, apart from the currently displayed product, have also considered other items in the shop. The recommended products are sorted by an indicator that gauges the chance of purchasing those items, which means that the search for similar products is greatly reduced.

Cross-selling – 1 in 8 customers clicks a recommendation pop-up, with every 10th making a purchase.

The recommendation algorithm analyses which additional products have a chance to become interesting for customers and displays them in a preconceived order (the ones with the highest chance of being bought are presented on the left) – all of this is based on other items the users have seen, placed in their cart, or on the experiences of others. The Other customers who purchased this item also bought recommendation displays supplementary products. In practice, a customer who wants to buy a bed will also see a mattress, or a bedding drawer. Pop-ups which are displayed just after a customer has added item(s) to the cart page, are proven to be very successful, as the user is very focused on the purchasing process at that every moment, with the recommended products only intensifying the impulse.

Results

CTR has reached the level of 12% and conversion has reached the level of 10%.

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