How predictive analytics helped a national retailer optimize merchandising decisions and maximize sales impact
The Challenge
A leading national home improvement retailer could not measure the true sales impact of off-shelf product placement, such as end caps, front entrances, and seasonal displays.
Because the same SKU was identical across locations in the store, existing point-of-sale data could not determine whether placement influenced purchasing behavior. As a result, merchandising decisions were often based on instinct, trends, or competitive activity rather than measurable insight.
The Solution
The Intersect Group partnered with the client to develop predictive merchandising algorithms that measured the impact of product placement across stores.
Using historical sales, product, and location data, the team established baseline performance models and implemented integrated reporting that enabled cross-functional visibility and data-driven decision making.
The Impact
The solution transformed merchandising from intuition-based decision making into a more measurable, analytics-driven strategy.
- Improved visibility into promotional placement performance
- More strategic product placement decisions
- Optimized product selection for high-visibility locations
- Improved inventory planning through sell-through insights
- Better alignment between merchandising strategy and revenue performance