What types of personalized product recommendations in the food industry allow you to show the user more interesting products based on their segment?
Suggesting to the customer the product most akin to his or her tastes and interests, at the time when, he or she is most likely to buy it: this is the secret of a successful strategy.
With Blendee, personalized customer experiences can be created through sophisticated tracking systems and the contribution of artificial intelligence.
The platform provides multiple algorithms on which to personalize the user’s shopping experience by proposing products and offers tailored product Recommendations and thus customize one’s marketing strategy.
Eataly, a leading brand in the sale and distribution of Italian excellence from small and medium-sized producers, has chosen to personalize the shopping experience within its shops using different types of product recommendations:
1. RECOMMENDED PRODUCTS ON THE HOME PAGE
2. RECOMMENDED PRODUCTS ON THE PRODUCT PAGE
3. RECOMMENDED PRODUCTS IN THE CATEGORY PAGE
1. PRODUCTS RECOMMENDED ON THE HOME PAGE
Two different types of Product Recommendation were included within the Home Pages of the different shops dedicated to home shopping. For the “Chosen for You” block, the “Personalized recommendations by sales“algorithm was selected, which suggests products based on the experiences of users with recent purchase history similar to that of the user who is browsing. For the “Most Sold” block, “Trending products” was selected as the algorithm, which shows the list of the most popular products in a catalog based on the amount of views and clicks.
2. PRODUCTS RECOMMENDED ON THE PRODUCT PAGE
In the product tab, with the goal of increasing the value of the user’s shopping cart by stimulating the addition of more products, a Product Recommendation block was inserted that suggests, through the “FrequentlyBoughtTogether“algorithm, products that are often bought together with the product referenced on the current page.
3. PRODUCTS RECOMMENDED ON THE CATEGORY PAGE
In the Eataly.it shop, Product Recommendation was instead chosen to be placed within the main category and subcategory pages. In this case, thealgorithm identified was “Personalized Trending Recommendation,” which shows a mix between the most popular products and products based on the user’s recent browsing history.
Thanks to Blendee’s contribution, Eataly, was able to exploit information about users’ purchasing behavior in order to propose products in line with their tastes and needs. Marketing personalization strategies were thus materialized within all online shops to show users potentially more interesting products based on their segment.
Article excerpted from the ebook Case Study Eataly. Personalization and Omnichannel Customer Experience: the case study of success in the Food sector.
