Utilizing Upselling ML Models for Ad Merchants to Optimize the Budget and increase Revenue
The client wanted to predict the upselling trends leveraging peer behavior data of the individual merchants. In order to increase the spend budget of those merchants on the platform that would maintain a permissible return on ad spend (ROAS) which will in turn help our client achieve increased revenue.
The client is a global technology giant that operates through a mobile app. With a presence in over 900 metropolitan areas worldwide, the client has revolutionized the transportation industry, providing convenient and affordable alternatives to traditional taxis. The client is also actively expanding into other logistics areas.
- Increase Ad Revenue: To enhance ad revenue on the client’s ads platform by predicting the upselling trends using the peer behavior data among the individual merchants.
- Propose Enhanced Spend Budget: To propose an enhanced spending budget that balanced maximizing ad revenue and maintaining a permissible return on ad spend (ROAS), resulting in increased profitability and success on their ads platform.