eCommerce is estimated to account for 20% of global retail sales by the end of 2022 (Statista). As the importance of this segment is increasing, we...
Case Study: How Dasha.ro improved its conversion rate with personalized product recommendations
1. Focusing on the conversion rate
In 2021 the Romanian online apparel retailer, Dasha.ro, realized it was high time it gained a competitive advantage by offering a more personalized shopping experience to its visitors. Dasha.ro has over one million sessions per month and is one of the important players in its sector.
The management’s objective was to record more sales and higher-value carts without increasing the marketing budget. The solution consisted in having a recommendation engine that could fuel growth by driving longer visits, more clicks, and ultimately more sales.
“A product recommendation tool has the capability to increase the conversion rate and improve sales performance, through up-selling (encouraging customers to purchase a comparable higher-end product) and cross-selling (offering customers products that are compatible or complementary to the ones they intend to purchase). Such additions can make a big difference for an online retailer.”
Vlad Marincas, CEO Aqurate
2. From theory to practice
For Aqurate to help the online store achieve these results, it needed to collect the sales and website clicks data, and input them into its cutting-edge recommendation engine, based on collaborative filtering. To facilitate the data gathering, Aqurate offers 1-click seamless integrations for a range of data sources.
Collaborative filtering is contingent on analyzing and interpreting large volumes of customer behavior data (buying, clicking, adding to cart, etc.). It compares similar actions of different potential customers and predicts what a particular user is interested in.
The most relevant items for users are visible on the website through two native widgets, one showcasing substitute products and the other widget showing bundled items for better cross-sell results. Once the personalized recommendations are computed, the items are sent via API to be displayed in widgets. They can also reach customers through other channels like Email, Apps, Popups, etc.
3. From ideas to results
To correctly assess the impact of Aqurate Personalize, an A/B test ran for multiple weeks, evenly splitting traffic between the original version of the website, and the version containing the new product recommendations. After looking at 1.2 million sessions, Aqurate showed a 25% higher conversion rate for the sessions where users interacted with recommendations. For Dasha.ro this translates into significantly higher revenue, and a decrease in the time spent setting manual recommendations for each product.