Artificial Intelligence for personalisation.
Algorithms that think growth.
Content-Based
Recommend items based on the current items being viewed, dynamically. Increase the visibility of items within the same scope and let your users explore more on what they are currently browsing.
Collaborative-Based
Take your recommendations a step ahead. Utilise the wisdom of the crowd and predict what your users may find interesting. Recommend items that your users find novel, creative, yet captivating.
Hybrid-Filtering
Create different versions of algorithms of your choice. Mix and match different Machine Learning algorithms to produce a unique experience for every user that presents your knowledge of them.
Engagement-Powered
We all view things that we may find not interesting, it's part of our digital behaviour to explore. Go beyond the clicks and pageviews and utilise engagement as a core metric in your Artificial Intelligence.
Context-Aware
Be smart. Understand the context, and infuse context dimensions in your algorithms. Geolocation, time of day, day of the week, user profile, profit margins, priority, and more.
