Speedy, accurate & responsive user experience is key to growth of a successful Online Business. Search suggestions for seamless browsing sessions and In-session recommendation to up-sell & cross-sell are critical to keep customers engaged.
Users’ data is viewed as a sequence of macro interactions between users and product-items. Each macro interaction, in turn, includes a pattern of micro behaviours performed by the user during the shopping experience.
Combining browsing and transaction behaviour with an underlying ML layer, helps build a factory of high-accuracy, personalised recommendations.
Hybrid recommendation models use context-aware collaborative filtering; to optimally serve recommendations.
