Discover how location intelligence can reveal the demographic, psychographic, behavioral, and geosocial characteristics of your target audience.
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Audience segmentation is the process of dividing a target audience or market into distinct groups, or segments, based on specific characteristics. Instead of fruitlessly trying to appeal to everyone, audience segmentation lets marketers, retailers, product developers, policy makers, and others define the specific segments of people they wish to reach and cater to the actual needs and preferences of these groups. This allows retail stakeholders and other professionals to deliver tailored messaging and offerings to their target audiences, providing better value and increased customer satisfaction.
Audience segmentation lets you answer questions like:
Audiences can be segmented in many different ways, depending on the purpose of the analysis. Each segmentation method uses distinct kinds of data and criteria which can often be combined to achieve even more granular insights.
Some of the most common methods for audience segmentation include:
While each type of segmentation relies on different inputs, they all share one thing in common – the need for accurate and up-to-date data. So where can marketers, retailers, and other stakeholders see the demographic, psychographic, behavioral, and geosocial identifiers of their consumer base?
When it comes to the online world, it’s relatively easy to track people’s behavior – and a myriad of tools offer insight into the online habits and preferences of the actual visitors to specific websites (think Google Analytics and Facebook advertising solutions). These tools allow marketers and other professionals to find audiences that meet highly specific criteria – such as users searching for a particular product or people that share an interest or passion for a particular subject.
Figuring out who goes where offline can be a lot more challenging. In the past, professionals had to rely on relatively imprecise methods like focus groups to understand the behavior and characteristics of visitors to physical venues. But today, advanced location intelligence tools that leverage foot traffic data make it possible to gain the same kind of visibility into offline consumer behavior that has long been taken for granted on the web. And by layering foot traffic data with demographic, psychographic, and geosocial datasets, marketers, retailers, and others can create laser-focused audience segments for their offline offerings.
Foot traffic data also makes it possible to identify a chain or venue’s captured and potential markets, allowing analysts to see which audience segments are over- or under-represented within its visitor base.
A chain or venue’s potential market refers generally to the people that reside in its trade area. This metric is derived by determining the business’ True Trade Area – i.e. the geographical region from which it actually draws its customers – and then weighting each census block group (CBG) in the trade area according to the size of its population. A business’ captured market, on the other hand, represents the population that actually visits the business in practice. Captured market is obtained by weighting each CBG according to its share of visits to the chain or venue in question.
Comparing a business’ potential and captured markets can reveal the extent to which it is succeeding at attracting different groups of customers. It can also uncover hidden opportunities for new markets waiting to be capitalized on.
The importance of offline audience segmentation – and the advantages of using foot traffic data to analyze captured and potential markets – can be illustrated with a few concrete examples.
Audience segmentation lets marketers craft cost-effective promotions that speak to their target audiences and drive conversion.
Imagine you run a bakery. You’ve decided to jump on the experiential retail bandwagon and are planning a series of promotional events where customers can learn how to whip up the perfect buttercream frosting and decorate their own cupcakes. But should you target the event at families with young children, or at college-age singles? What about senior citizens? And are there enough vegans or gluten avoiders among your potential customers to justify a night dedicated to people with special dietary constraints?
Using foot traffic analytics, you can determine your store’s True Trade Area – i.e. the specific zip codes and CBGs that your customers actually come from. And then, by overlaying psychographic and demographic datasets on top of the foot traffic data, you can analyze the characteristics and habits of your potential market – i.e. the population that lives in your trade area – and plan your event accordingly. Segmenting your audience also allows you to advertise your event more effectively, targeting the zip codes most likely to convert.
Audience segmentation that compares a store’s captured market to its potential one (see above) can also inform merchandising decisions.
Say, for example, that you own a grocery store. The potential market of the store’s trade area includes a relatively large share of fitness fans compared to the statewide average, but its captured market does not. This means that although lots of fitness fans live in your store’s general trade area, not so many actually visit your store. The gap between the location’s potential and captured markets suggests that fitness fans aren’t drawn to the grocery store’s current offerings. This may indicate an opportunity to create targeted promotions for the store’s fitness-oriented products, or to stock more merchandise likely to attract this segment.
On the flip side, if your store’s captured market has a larger share of fitness fans than its potential market, you may choose to double down on this demographic, broadening your selection of health-conscious- snacks, protein powders, and other items that fitness aficionados tend to purchase.
Now imagine that you own a small chain of apparel stores and are looking to expand into new markets. You are considering spots in several different shopping centers and need to determine which is the best fit.
By analyzing foot traffic to your individual venues, you can determine the demographic, psychographic, and behavioral characteristics of your existing customer base and seek out centers that draw similar audiences. If your chain offers high-end designer clothing, for example, you may prefer a center with a wealthy customer base (such shoppers belonging to Spatial.ai’s geosocial #MidasMight segment, which encompasses extremely wealthy families living in large estate homes). But if your merchandise is off-price apparel geared for Gen Zers, you may be better off in a mall that draws customers that post about #Adulting.
CRE (commercial real estate) professionals can also utilize audience segmentation to select locations for new retail developments, optimize tenant mix in shopping centers and other commercial properties, and more.
Suppose you manage an outdoor shopping center that is experiencing declining revenue. A thorough audience segmentation analysis can help you determine whether your current tenant mix still meets the evolving needs of the local community, or whether it’s time to change things up. For example, if the segmentation reveals a growing interest in health and wellness among the population of the center’s trade area, you might decide to replace a vacant electronics store with a yoga studio, or an underperforming restaurant with a juice bar.
Segmenting your customers based on cross-shopping behaviors can also help you optimize your offerings and attract the right tenants. Say, for example, that your current anchor tenant isn’t doing well, and you want to convince a local Apple Store to relocate to your center. If cross-shopping data shows that the Apple Store’s visitors also tend to shop at chains currently located in your center, this information can be used to make a strong case that your center would indeed be a good fit. Comparing the data to cross-shopping between the Apple Store and chains at other malls can also be leveraged to highlight your center’s relative advantages.
Placer.ai’s user-friendly location intelligence platform provides you with all the tools you need to easily conduct thorough audience segmentation. The foundation of Placer’s platform is highly accurate and anonymized foot traffic data which reveals where people go in the physical world. Placer makes it easy for customers to leverage this data to determine the True Trade Area of any specific commercial location or broader geographic region and analyze its captured and potential markets. Placer’s Data Marketplace includes an extensive selection of demographic, psychographic, geosocial, and other datasets that can be seamlessly integrated with the foot traffic data to yield instant, actionable audience segmentation insights. Some of the many datasets available in Placer’s Marketplace include:
To make effective, data-driven decisions, professionals across industries need granular, accurate insight into the actual characteristics and habits of the audiences they are trying to reach. By combining foot traffic data with a variety of other data sources, advanced location analytics platforms like Placer.ai take the guesswork out of consumer research and make it easier than ever to understand who offline consumers are and what they’re looking for.
