Recommendation engine leverages proprietary machine learning models to recommend right offers and products to each customer based on his historical and contextual usage behavior. It can analyze customer’s purchase, revenue & usage behavior and recommends products/offers that the customer is most likely to buy/subscribe next.
Make use of standard connectors and readily access variety of enterprise as well as third party and open data to analyze and predict customer affinity for products/offers. Remotely access data directly from the existing CRM system or from Data Lake which stores raw and aggregated customer data.
Pre-built output connectors to feed offer/product recommendations directly to CVM systems or to any external database. The output of recommendation engine can also be delivered as a delimited file in any desired format.
Get an aggregated view of offer inquiries received and offer recommendations served in real-time. Also get an instant view of how offers have performed in terms of take up rate and uplift in revenue.