Machine Learning, Deep Learning, Cloud Application
A Fortune 500 multichannel retailer undergoing digital transformation wanted to engage with its customers at the right time with a relevant messaging. It required an understanding of various customer attributes such as their industry, buying patterns, browse behaviors, social signals and so on. They needed an intelligent solution that predicts the likelihood of specific customer events and proposes the next best action.
The team developed an always-listening solution that ingested data on customer activities across interaction channels and correlated it with the historical data including site behavior. The machine learning algorithms consumed a series of captured data attributes to identify patterns and trends that were translated into actionable tasks, engagements and messaging for the sales, marketing, and site personalization.
Single to double digit incremental sales for various customer segments, reduction in cost of customer acquisition by 20%, customer retention improved by 10%.
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