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. Aiwozo’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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