They need to have the opportunity to zoom in to read the fine print and get the information they want from a package. When testing for a package change, they may not recognize the product and need to see it from all angles to understand what it is. They must be able to move through the aisle and actually pick up the items to examine them. Is the stimulus representative of the marketplace? The key here is the ability of the respondent to behave as they would in a real brick and mortar store. Doing this same design across multiple retailers’ planograms makes a study even more robust in understanding if there are differences across retailers or channels. The only change is the packaging itself, while all other variables remain the same. When testing in 3D virtual stores, it is easy to isolate the packaging change you are testing. Because there are a variety of behaviors and approaches that need to be captured, it’s most important to get accurate sales behavior by allowing them to shop a category as they normally would. People don’t shop in 2D they approach an aisle at indirect angles, and rarely stand directly in front of the shelf. Is the exercise representative of the dynamics being assessed? Any approach that doesn’t attempt to understand the impact the package will have on sales is missing the point of making a packaging change altogether. Important questions arise when it comes to choosing a successful study approach: Update Your Research Approach with 3D Planogram Software.What Makes a Successful Study Approach?.Here we look at the challenges of 2D planogram research, and why 3D digital twin technology helps solve these common problems. 3D shopping exercises get results predictive of in-market results, even when using only one planogram, despite the retail execution problems and variety of planograms used in the real world. But a well-designed study would account for the major differences in principles that are applied to categories to get the best outcome.Īn approach that consistently tests with 90% or greater accuracy when compared with in-market results would achieve that goal. Therefore, it’s not possible to capture all the possible configurations of each iteration of the retail merchandising tool. The ways planograms are laid out vary from retailer to retailer, and within each retailer. While they may think the issue lies with the POG (planogram) itself, it’s actually the test shopper experience that is the underlying problem, not the planogram chosen.

The problem is that many shopper insights and category management teams are still relying on static 2D planogram tests with attitudinal measures of intent- to-buy. What makes planogram research successful? Brands and retailers are looking for reliable, projectible data to give credence to their decisions when it comes to shelf and package testing.

Planogram planogram in retail example