E-COMMERCE
RECOMMENDATION

Recommendation engine designed using historical user preferences and similarities

Challenge

With large number of products available, customers can get confused. We need to recognise their needs and provide them what they need

Goal

Create online recommender based on user preferences

Our solution

Ml model built on historic transaction data capable of providing real-time offerings to customers based on their preferences

Business Value

Increase of sales and revenue, increase of customer satisfaction

Category

Retail

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