How to Enter New Markets and Improve Product Development With Store Level Data

Product development is a long process that begins with an idea and doesn’t end even when you’ve gone to market. Reevaluating and improving upon your product line is part of the long, important process of product development—and data makes that process more efficient.

Let’s say your products are in Tom’s Market in 100 locations across 20 cities, and you’re moving 1,000 cases per month. That tells you how many customers you have with this retailer but it doesn’t tell you anything more about the customer or give you the groundwork to build on that success.

Your shoppers differ based on location and personal demographics, even within a single retailer. SPINS’ Store Level Data (SLD) provides metrics that you can dive into and also layer on other relevant data so you can begin to understand who is buying your products and what they’re looking for.

With SLD, you can look at store-specific performance, which is helpful in many ways, especially when analyzing distribution and velocity. However, you can also gain other insights by grouping store data together at the city and state levels.

For example, if you’re still looking at the 1,000 cases you sell per month in Tom’s Market’s 100 locations, you don’t expect to find 100 cases sold at each store. Some stores will sell more, others will sell less. If you then look at the sales totals for the 20 cities you’re in, you’re going to see similar highs and lows. Austin’s 6 stores might look very different from Seattle’s 10 stores but somewhat similar to Miami’s 9 stores. This begins to reveal regional differences that could be traced to factors such as weather, competing retailers, and more. Those are findings you get from simply looking at SLD’s city or state data, but you don’t have to stop there.

SLD provides many valuable insights on its own, but you can maximize its value if you combine it with your SPINS market-level data to overlay competitor information or SPINS Consumer Panel data.

Whether you’re looking at a single store or a region, you can add consumer behavior trends and purchase drivers to build a comprehensive shopper profile. These additional insights give you a sense of what is motivating consumers, why they’re choosing your products or someone else’s.  Or analyze your SLD and market-level data to see how you’re performing at the product level. For example, if your product lineup has 3 flavors, you can dig into how each flavor is performing by location. The top flavor might not be the same as in Seattle and Miami. This is when you’ll begin to find patterns that reveal not just how your product is performing overall but how the variations within are performing from store to store.

Now you know where you perform best and who your most loyal shoppers are, and that means you have a good idea of where you’re likely to repeat that success. Look for similar markets where the shoppers fit your ideal profile and aim to expand distribution there, both within your current retailers or as you begin to look for additional ones. Store Level Data lets you turn your micro findings into macro results.

Jim has 30+ years of CPG industry experience beginning on the client-side (Kraft Foods, Marketing/Sales/Category Management) before crossing over to the “dark side” of information services (Spectra, IBM, IRI, Acxiom).  His specific expertise in store-level data spans Spectra (store trade areas, profiling & targeting) to most recent sales and offering development at store-product-day provider RSi (now part of IRI).

Working with the SPINS retailer relationships team, Jim is building the next generation of applications across an expanded channel/network capability and working with existing clients to further harness the power of SLD for the benefit of manufacturers and retailers alike.