The client is a leading supplier and retailer of vitamin, protein, sports and herbal supplements in the USA both online and in retail outlets.
Tenzai deployed the Purpose Driven AI approach to develop a machine-learning based recommendation engine for the client.
Data from multiple sources like CRM, clickstream data, browsing behavior, past purchases was integrated to create multidimensional microsegments based on demographics, purchase and browsing behaviour. Based on the microsegments different customer genome profiles were defined.
An ensemble of techniques like collaborative filtering, matrix factorization and clustering were used to develop the recommendation engine.
The solution was able to choose the optimal algorithm for each customer based on the context, microsegment and data availability.
The solution has an interface for business users to incorporate business goals and priorities. They could assign priorities and weights to different products based on business objectives.
The multiple solutions were then deployed in docker on the cloud.