Product Recommendations Based on Previous Purchases Drive $2 Million Jump in Sales

Client: Lighting Retailer

The Challenge

An online lighting and fan retailer was producing product recommendations on their website according to customer browsing behaviors, but they weren’t seeing a substantial return. They hoped to expand ecommerce revenue by modifying the strategy on their product recommendation sections.

The Solution

Sophelle first reviewed product recommendation performance, which revealed that the algorithm prioritizing browsing data recommendations wasn’t sufficiently converting to sales. To rectify this, we leveraged tangible transactional data such as prior purchases over the previous traditional merchandising and browsing data approach, then ran A/B tests to analyze the results. Tests revealed that targeted recommendations using concrete purchase data drove substantially higher conversion rates than browsing data.

The Result

By adjusting the algorithm to leverage transactional data, the lighting retailer saw immediate results and is anticipating an incremental $2 million lift in annual revenue.

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