Menu
Many brands sell their products through third-party retailers to better understand their consumer profile and how visibility affects sales.
A global beauty brand sells products on over 50 third-party retailers. Their largest retailer represents a significant amount of their revenue and they would like to know how to optimize this relationship. Their goal is to increase sales on this retailer’s site and gain a data driven understanding of how visibility affects their sales.
We used hand-collected visibility data and weekly sales reports from the retailer. After pre-processing the data and compiling the sales reports. We built two models: a predictive model to forecast sales and an optimizer model to reveal the most significant visibility values. Constrained optimization provided a data-driven perspective on the consumer profile, the optimal timing and content of promotions, the visibility values required to maximize sales and the most relevant pages.
We found that if the retailer would add an additional product of the brand’s to two particular category pages, sales were projected to increase by 25% YoY. The sales forecast model operated at a 94% accuracy level. These insights revealed the consumer profile, best time of year for marketing, most relevant pages and the exact visibility values that would maximize sales.