There was news this week you may not have noticed: the 2020 census data is in. Aside from it being used as a political blame game, this data is very useful- especially to retailers. We have been incorporating demographics into our analytic repertoire for many years.
Demographic data provides retailers, manufacturers, brands and distributors the ability to more efficiently allocate specific products to specific stores based on the population that resides around that store. Unlike transactional data it does not raise any privacy concerns because it is not based on any individual’s specific information.
The benefits of integrating demographics with POS came early in ERS’ history. A client who manufactures high end utility bedding with a high price tag was trying to convince a mass retailer that they could sell the product in a select group of stores. Acknowledging it was not right for all doors, they challenged us to find a way to make a compelling case to the retailer. We reviewed the sales history from other retailers, and we noticed that the top selling stores were all located in wealthy communities. It was a hunch that we needed to prove out with facts. We went to the Census Bureau and looked at the median income for the communities where those stores were located. All of them had higher income and education levels compared to the US average. The opposite was also true- stores located in communities with lower income levels did not sell the product as well. The next step was to look at all the store locations for the mass chain and see how many were in high income areas. We matched the demographics on the zip code for each store. That was it- we could show that even though the majority of the mass chain’s stores were in rural, average income communities, there were around 200 in high income areas like Boca Raton, FL. and San Diego, CA. By pinpointing the specific set of stores, they agreed to a test, which eventually expanded into a $40,000,000/year program. The buyer told us that we removed a huge element in the decision-making process: risk.
Brands and licensors have long used demographics to help launch products and cater to specific markets. There are hundreds of demographic traits that can be useful in assortment planning and allocation. Age, gender, ethnicity, housing statistics and more are broken down into micro segments (ex., boys age 4-7) for more specific targeting. Another example is a client in the tooth cleaning business that asked us if there were specific areas in the country with a high percentage of divorced women in their 50’s in their population (it was creepy then, it’s creepy now). They were more interested in determining where to place media buys than store placement, but it eventually led to allocation at drug store chains and their thousands of locations.
Removing risk from the equation provides the perfect trifecta of retail performance- higher sales, lower markdowns, and faster inventory turnover.
Integrating demographics with POS in your data warehouse can be daunting. It requires advanced database and spreadsheet skills along with a knowledge of how to make the data actionable. Unless you want to take 10 years off your life, I suggest you subscribe to a solution that does it for you. We offer a great one in our Best Practices planning toolkit. If you are interested in learning how you can take advantage of demographics contact us.