Provide relevant content and make your sites smarter.
When using our recommendation engine, ecommerce sites see an increase in revenue
Using deep learning, our recommendation engine understands what visitors need.
Specialise recommendations per industry and maximise efficiency. Using a knowledge graph, we can further specialise the recommendations by industry and no longer stay a generic recommendation system. The engine utilises user-generated data including text descriptions and images for precise recommendations of fast-changing content. It then finds the best fit per individual user by matching the attributes of the user and offering.
Recommendations come with explainability built in, so users can understand why items are recommended to them. This way, UX becomes better, and the engagement becomes smoother.
One of our clients wanted to increase the CTR and conversion rate of their customers’ sites. We solved this problem by providing them with a recommendation engine based on deep learning and graph data science.
Our solution achieved an average of 40% increased CTR by personalising the in site content and providing relevant recommendations tailored to each user’s preferences. The result was more engagement by users and in the case of ecommerce an increase in basket size and/or conversion rates with personalised product suggestions.
The integration was quick and easy for products, content and search, through the use of a simple API.
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