Hidden Nuggets in Local Address Data for Retail Decisions

It’s no secret that the past few years have been extremely challenging for inventory managers. In 2021 and early 2022, brands faced widespread inventory shortages, while the latter half of 2022 and 2023 saw massive excess inventory levels (as much as $740 billion in unsold goods) as brands worked to counteract the previous year’s shortages and consumers felt the financial pressures of inflation. Finding the right balance is always a challenge. However, there are critical data points that many brands overlook in the context of inventory management – address data.

“Location, location, location” is a frequently used term in real estate conversations to assess the value of homes. But the same can apply to retailers looking to make the most out of their stocking decisions. Address data can play a big role in helping cut down on excess and out-of-stock inventory for markets.

Brick-and-mortar retailers often analyze regional consumer demographics to determine what products to stock in a particular store. Some demographics they consider include age groups, gender, ethnicity, and education levels.

However, savvy retailers also find nuggets of information to help drive stocking decisions based on address data within the market itself. Understanding what this data has to offer is an untapped way to success.

What type of address data should brands be looking at?

Retailers often judge the potential of a market based on the quantity of people in proximity to a store location. However, address data can share more than how densely populated an area is. Here are 4 data points retailers can reference to improve retail stocking decisions:

• Unit/Home Type:  One such overlooked opportunity is what can be learned by knowing if an address has multiple subunits. Take for example, multi-tenant housing. If you have a store that sells snow shovels, even if you’ve analyzed snow patterns, it may not be enough to properly know how many snow shovels to stock. If the store is surrounded by home addresses with subunits (such as apartments), where the people who live there aren’t responsible for shoveling snow, no matter how many people live there, demand will be lower. The same can hold true for home addresses that are part of a homeowners association (HOA). The HOA is responsible for snow removal, not the homeowners. As such, the homeowners won’t be interested in purchasing snow shovels. Additionally, unit/home type data can help prevent stagnant inventory and can help you find new popular items. An area with many multi-unit addresses means a lot of your potential customers live in homes with limited floor space and will value compact and multi-use products like sofa beds, collapsible kitchen furniture, all-in-one exercise equipment, or under-bed storage.
• Building Age: Another example of where address data can help brick-and-mortar retailers in stocking decisions is the age of the homes surrounding the location. Understanding the age of those homes can help determine which items are most likely to be needed by the homeowners. For example, by stocking more vintage-compatible repair and home restoration products, retailers can increase sales in areas where older homes are the norm. Stocking the same items in an area with a majority of newer homes would leave your inventory collecting dust, but stocking your store with smart devices and security gadgets would boost sales because of the young families and technophiles that new construction tends to attract.
• Home Value: Another valuable data point for retailers to reference is the value of local homes. Measuring the assessed property value and sale price can act as additional economic indicators of neighborhoods and could correlate with demand for premium brands or luxury items. More modest areas might find value products more attractive.
• Owner Occupancy Status: Being able to collect data on the owner occupancy status for homes in an area helps retailers balance inventory purchases catering to homeowners and renters appropriately. Renters may prefer portable appliances and temporary non-damaging solutions like tension rods for curtains, smart lightbulbs and plugs, and command strips for hanging items without damaging the wall. Homeowners would be more interested in built-in shelving, installed smart devices like switches and outlets, and home improvement tools. Having a ratio of inventory that matches an area’s homeownership profile reduces wasted floor space and serves customers better.

With hundreds of property data points available, ranging from the attic’s area to whether a home has a wine cellar, addresses can unlock a wealth of information. It’s up to savvy brick-and-mortar retailers to explore which address data to use to significantly impact their stocking decisions.