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.

 

The Solution

 

We developed an algorithm to monitor and categorize user-persona. The initial persona was created using the historical buying trend of the user. Aiwozoโ€™s Machine Learning (ML) capability was applied 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.

The Outcomes

Enhanced search-to-buy ratio by 27%.

Increased positive customer feedback by 18%.

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Challenges Addressed

Irrelevant content
Irrelevant content
Low customer satisfaction
Customer experience
Low search-to-purchase ratio
Low search-to-purchase ratio
Less cross-sell opportunity
Less cross-sell opportunity
High time-to-purchase
Low Return on Investment
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