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Case Study: AI Product Recommendations in the Domowanie Furniture Store

Case Study: AI Product Recommendations in the Domowanie Furniture Store

Avatar Zuzanna Pajorska
26 March 2021
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Case Study Recommendation System in Furniture Store

The online furniture store Domowanie.pl decided to implement a product recommendation engine in February 2021. As in the ByLola store, the installation was seamless and quick - it was enough to paste a line of Javascript code on the store's website without the need to involve a technical person.

The analysis of key metrics for the store after a month of using Recostream showed that the share of AI recommendations in sales has significantly increased, and the value of the shopping cart is greater than before the implementation of intelligent product recommendations.



Online furniture Store recommendations results

About the Store

Domowanie.pl is an online furniture store offering furniture of the best and most popular Polish brands. Among thousands of products, domowanie.pl offers all the necessary elements of an interior design for your dream living room, children's room, office, dining room or bedroom. Thanks to many years of experience in furniture sales, we offer our customers the best proven solutions and new collections of furniture at competitive prices.

  • Platform: PrestaShop
  • Number of Products: approx. 6 000
  • Store Address: www.domowanie.pl
  • Deployment Configuration: February 2021

About Recostream

We have been developing an AI recommendation system that allows you to increase sales by 5-10%, while allowing store customers to find products that interest them faster and more accurately. Placing recommendations is possible in a few minutes without the participation of programmers, and their effectiveness is optimized by artificial intelligence algorithms and machine learning based on the actual customer behavior.

Take Advantage of the 30-day Trial Period

Purpose of the Implementation

Before integrating the Recostream engine with the store, we established 5 main implementation goals:

  • Increase in the value of the shopping cart
  • Reduction of shopping cart abandonment
  • Improvement of the CTR ratio
  • Increase in conversion
  • Recovery of conversions on pages of unavailable products

The Results

The analysis of the store's metrics after 30 days showed an improvement in key indicators. We analyzed independent results based on store statistics collected in Google Analytics Enhanced Ecommerce. After the free trial period, the conversion and click-through rates in the store were as follows:

Results of recommendations system implementation in Online Sore

Tools Used

To meet the customer's goal and expectations, we decided to implement several types of recommendations in four places in the Domowanie.pl store due to the fact that the profitability of recommendations depends on the location on the store's website.

Most Profitable Recommendation Locations in the Domowanie Store:

  • Product Page
  • Pop-Up After Adding to Cart
  • Shopping Cart Page
  • Home Page

Implemented Solutions

The AI / ML Recostream recommendation engine offers 8 types of recommendations, which differ in the way of filtering data about products and user behavior on the website. Together with the owner of the Domowanie.pl store, we decided to introduce 6 recommendation models in order to maximize profits.

6 implemented models in various store locations:

  • Most Similar in Category (AI Maximized Conversion)
  • Others Also Viewed in Store (AI Maximized Conversion)
  • Recently Visited in Store
  • Most Viewed in Category
  • Others Also Added to Cart in Store
  • Bestsellers in Store
product recommendation system
Recommendation Model: Others Also Viewed in Store


product recommendation system
Recommendation Model: Rule-Driven Recommendations in the Pop-up After Adding the Product to the Cart


product recommendation system
Recommendation Model: Bestsellers in Store

Installation Process

  1. Registration on the recostream.com website, where the email address and the URL of the store were provided.
  2. Lines of JavaScript code have been pasted into the shop's website. It took 3 minutes without any programmer assistance.
  3. The Recostream team made a configuration of the appearance and adapted it to the design of the store.
  4. The AI recommendation engine was launched in one business day.
  5. Trial period started: 30 days.
  6. The results were integrated with the Google Analytics account for independent and objective performance evaluation.
  7. Ongoing contact with the customer service manager was maintained.



The Client About Us

Recostream allows us to boost the chances of increasing the value of the shopping cart, which, considering a high cost of acquiring a customer, is a very important aspect.

We operate in a very competitive industry online and in our case the client rarely decides to buy only one product. Shopping carts often contain complete sets of products, therefore the key aspect for us is to show customers these products on the shopping journey, which can potentially also be added by them.

Based on the results, we can see that the use of Recostream effectively contributes to accomplishing this goal.

Bartosz Żebryk
The Owner of the Store

We would like to invite you to take advantage of the 30-day trial period

Register and install the AI / ML recommendation engine in 3 minutes without the help of an IT specialist. We will take care of the rest.

If you have any questions, please contact team@recostream.com

You can read more about how the recommendation engine works on our blog.

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