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Enhanced customer loyalty with the help of personalized experiences

The Process

The client is a leading retail company. The current project was to personalize the product display for repeat customers to the e-commerce site. In the As-Is process, when a buyer logged into the website, they would only see a static page that was common for every customer. The search results for a customer was also based on product availability and sales; there was no personalization based on demographic or user-persona.

Our Solution

We developed an algorithm to monitor and categorize user-persona. The initial persona was created using the historical buying trend of the user. We used Machine Learning (ML) for the algorithm to adapt and add to the created persona continuously, as the customer kept purchasing from the e-commerce site. The intend was to create a personalized experience for each customer. This solution also reduced the time and effort spent by a customer while searching for products to their liking. Matched with the latest trends, the Artificial Intelligence (AI) model was able to create a seamless experience, which is equivalent to a personal shopping assistant in a physical store.

Challenges Addressed

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Irrelevant content           
Low customer satisfaction
Low search-to-purchase ratio
Less cross-sell opportunity
High time-to-purchase

The Outcomes

27 %

Enhancement in search-to-buy ratio.

18 %

Increase in positive customer feedback.

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