Understanding how specifically may not be obvious. That’s why today we’re launching a series aimed at focusing on a specific business problem and diving deeper into how we’d solve it.
Today’s problem: Minimizing in-store retail product display costs for a major consumer packaged goods (CPG) brand.
CPG brand X uses retail point-of-sale (POS) data to understand not only their position in the market, but also their competitors’. However, the POS data only gives them insight into when and where their products are being scanned for purchase. This information doesn’t tell them how much visibility or footage they have or pay for in the store.
The problem here is that the brand cannot calculate how their footage/presence/number of facings in the store translates into revenue. This brand needs a way to connect POS data with the in-store insights including the total number of product facings/displays as well as the total area of display in order to calculate the value of the square footage they inhibit per store.
Just as important, they need these insights on their competitors to see how they stack up and what adjustments need to be made in order to win more business.
How We Would Solve It
Premise’s on-the-ground Contributor network in more than 115+ countries around the world essentially serves as an extension of your workforce.
In this case, CPG brand X would work with our team to create a task that we would put onto our mobile app.
We would ask Contributors to go into specific stores and take photos of products’ shelf placements, facings, product displays, etc. We would also ask our Contributors to take measurements to ensure that the brand is getting a comprehensive picture of what is happening in each individual store location.
Contributors would do the same for a select number of competitors. These photos and measurements would be used by the brand to inform them of how much footage they inhabit in different stores and how that compares to their competition.
Lastly, our Contributors would then answer a series of qualitative and quantitative questions aimed at uncovering additional insights. For example, we could ask how the brand is perceived compared to the competition, how visible a brand’s products are in-store compared to competitors, and how knowledgeable staff members are about the products.
Pairing traditional point-of-sale data with in-store insights generated by Premise Contributors would empower the brand to become more efficient when it comes to determining where they should be dedicating resources.
- The combination of Premise Contributor insights and POS data empowers the brand to be able to calculate the cost/revenue per linear foot for each store they are in and understand the ideal number of facings needed in order to drive more sales.
- For example, they would be able to determine that product X in Store 1 has 3 facings but brings in the same amount of revenue as product X in Store 2 where they pay for 10 facings.
- Moreover, they could calculate specific thresholds. For instance, if they maintain a space of at least X, they should be able to bring in Y revenue at that particular store.
- They would also know which types of facings and/or layouts results in the most sales.
- For example, stores where product X is next to bananas sell twice as much of that product compared to stores where it’s next to soft drinks.
- Finally, they would be able to calculate such values for their competitors and understand in which stores they have a unique advantage.
Ready to get started? Get in touch with us today to learn more about how Premise can provide you with Data for Every Decision™.