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A system that learns from your customers' behaviour and your catalogue to suggest the next product, article or service each person is most likely to want.
It is trained on your data, not a generic model, so the suggestions reflect how your customers actually buy.
Behaviour, transactions and product data drawn from your systems.
Preferences and correlations found across customers and items.
Collaborative and content-based filtering trained on that data.
Recommendations served in real time, based on what the customer is doing now.
Every click and purchase feeds back into the model.
Matched to the touchpoint, not one widget everywhere.
Suggestions from browsing and purchase history, on product pages and in the cart.
Articles, videos and courses that keep people reading and watching.
Relevant upgrades and add-ons matched to each customer's usage.
Connections to relevant people and communities by interest.
Nearby businesses, events and services.
Suggestions shaped by time of day and season.
Relevant cross-sells raise what each customer spends.
Customers find what they want faster, and come back.
Personalisation at scale with no one curating lists by hand.
A clear view of preferences and trends in real time.
Tell us where you are stuck. We come back with a plan, a timeline and a number, with no obligation.