A Recommendation Engine inspires online shoppers with relevant recommendations along the digital customer journey. For this, the click and purchase behavior of each shop visitor is recorded in a knowledge base and processed to a history. With a self-learning technology, each online shopper will be presented with customized products. The Recommendation Engine thereby stimulates the imagination of the online shoppers and enables them to recognize the product’s advantages. The transported emotions, lead to purchase impulses, which fill the shopping cart. That’s what epoq™ Inspire offers you.
If the visitor has already been to the shop, their clicking and purchasing history is used to make relevant recommendations.
Like men’s fashion – a luxury male outfitter offers his customers alternatives and knows which ties go best with which shirt.
Generate personalized buying impulses, and offer good advice on matching outfits at the same time.
Linke books, films and music – Harry Potter fans don’t just buy one book, but a second one too or maybe a Blu-ray, etc.
Such targeted recommendations can be made right on the product detail page to encourage browsing. These are based on visitor behavior and customer history.
Like the drugstore area – if a user is interested in a shampoo for greasy hair, they are very probably a good candidate for other products in the range for their particular hair type.
Najoba.de is able to offer personally-tailored recommendations to its customers according to hair and skin types, using individually programmed rules.
It is about matching visitors’ and customers’ taste with relevant recommendations and thereby creating need. This is achieved by:
We take on all the requirements as well as the specialist and industry knowledge of a shopkeeper and provide a tailor-made recommendation engine.
In order to set up the Recommendation Engine, we first need your product catalog in XML or CSV format. We give you the tracking code for the connection to our platform, which you integrate into the shop.
Tracking Code & Code snippet
You add our tracking code to your online shop to connect to our platform as well as a code snippet as placeholder for the frontend.
The relevant recommendations are configured in your test system until the optimal result is achieved.
After a short learning phase, the relevant recommendations are displayed in the shop.
We test the recommendations, adjust the rules to the desired strategy and provide training for the login.
Fully automated personalization in the online store results to more sales. This increased at Sister Surprise the desired KPIs. Case Study download now.