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Geodemographic Segmentation: The People Behind The Coordinates

March 7, 2018 at 9:47 AM

At Spatially, we talk a lot about location. We talk about location in terms of local advertising and where your ad spend will see the greatest return. We talk in terms of site selection and the role of location in brick-and-mortar retail. And, we talk in terms of city planning and the importance of using location intelligence to decide where to build that next park or other public good.

Yet, none of these conversations are truly about location. We’re not talking about a particular place or position, nor are we arguing that any one set of coordinates is superior to any other. We’re talking about the people behind the coordinates.

Location is a lens through which you can gain a new understanding of people. It’s a way of categorizing individuals based on where they live, where they spend their time, and how they interact with the physical world.

To truly understand this lens, however, we’ll first have to dive into a concept called geodemographic segmentation, how the notion relates to digital marketing, and a few of the ways businesses, governments, and communities are using location to better understand society.

What is geodemographic segmentation?

Geodemographic segmentation is the statistical classification of people (demographics) based on where they live (geography). The analysis relies on two primary principles:

  1. People who live next to each other are more likely to share common characteristics than two people chosen at random.
  2. Locations can be categorized by the characteristics and demographics of their residents. If they have a similar demographic makeup, multiple locations can fall into the same category even if they are separated by great distances.

Geodemography is often traced back to the work of famed London social reformer Charles Booth in the late nineteenth century. Skeptical of the existing data on poverty, Booth and a team of researchers set out to explore the role, impact, and distribution of poverty in London. The team effectively overlayed census data on top of a map of London to identify where poverty clustered. The result of this research was the first “poverty map,” a topographic visualization of poverty.

The analysis revealed that wealth clusters in specific areasthat is, immediate neighbors are likely to have similar income levels. The new data further revealed that the previous measures of poverty were severely understated and brought about a surge of social reforms, including old age pensions, free school meals, and other poor-relief policies.

The original geodemographic segmentation model: Charles Booth's poverty maps of London

Source: Charles Booth’s London

While it started as a way to look at income distribution, location has since become a lens through which we can study any element of consumer behavior or demography. Just as income tends to cluster geographically, so do our lifestyles, interests, and preferences.

Neighborhoods can be classified as predominantly homeowners or renters, blue collar or white collar, country music lovers or rock fans, young or old, white or black. It’ll rarely be a perfect classification, of course. A predominantly Democrat neighborhood is bound to have a few Republicans; however, the differences within the neighborhood are fewer than those between other neighborhoods.

Thanks to the rise of location sharing and mobile technology, we’re now even able to move beyond where someone lives to analyze their spatial behaviorsthat is, how we move and interact with the world. We can now classify people by their shopping patterns (“people who shop at Whole Foods tend to live here and work here”), interests (“people who go to museums tend to live in higher-income neighborhoods”), and lifestyles (“people who to go a gym are more likely to rent than buy”).

However you’re looking to analyze consumers, location provides a valuable lens for identifying and grouping common characteristics.


more than geofence

Think of the world as a website

If geodemographic segmentation is a difficult concept to grasp, consider something that’s likely a little more familiar: Online marketing.

Customer segmentation is widely used in the world of online marketing. By slicing and dicing specific demographics and online behaviors, digital marketers have long been able to:

  • Segment website visitors by behavior, looking at which pages they visited in order to send visitors more personalized communications and recommendations.
  • Analyze conversion and site engagement metrics across cohorts grouped by age, gender, location, acquisition date, lifetime value, and website engagement.
  • Dynamically personalize website content to send different messages to different types of visitors.

Geodemographic segmentation bridges the online and offline worlds, taking what digital marketers have been doing for years and putting that power in the hands of anyone looking at the physical world. Take a look at how these online and offline tactics compare:

Comparing geodemographic segmentation and digital marketing segmentation

Putting geodemographic segmentation into action

Today, the role of geodemographic segmentation has gone far beyond research and public policy. Marketers of every industry are realizing just how powerful of a lens location can be when it comes to understanding and engaging their customers.

Here are just a few strategies we’ve seen at Spatially:

Plumbers and other service area businesses can target key neighborhoods.

For a plumber, HVAC repair service, or other service area business (SAB), it can be a challenge to predict who will need your services. With little behavioral data to make sense of, SABs typically cast a wide net with their local advertising, targeting everyone within a certain number of miles. Of course, this also means they risk paying for a lot of clicks that won’t convert into paying customers, such as apartment renters looking for quick tips while they wait on the rental company or low-income neighborhoods that might not be able to afford a higher-grade service.

This broad approach can also get expensive fast, especially with plumbing keywords costing north of $40 a click.

Geodemographic segmentation offers SABs a way to eliminate this ad waste by targeting locations characterized by certain census data:

  • Homeownership, which can be used to exclusively target areas known for a high owner/renter ratio.
  • Household value or income, which can be used to focus costly clicks on households likely able and willing to pay more for a high-quality service.

Segmenting New York by average household income

Segmenting by household income can be a great way to filter by socioeconomic attributes.

Source: Andy Arthur

Political campaign managers can target down party lines.

Political affiliation has often been the holy grail of political advertising. If campaign managers know where their party’s voters live, they can focus their ad spend on those most likely to vote in their favoras opposed to having ads fall on deaf ears with the opposing party.

If you’re able to get your hands on voter records, you can use geodemography to identify which locations are most popular with your party and restrict your ad spend to these areas. Alternatively, you can target swing counties by looking for areas with a roughly even distribution of political affiliations.

Some campaign managers are even using spatial data to target not just where people live, but where they visit. Using this strategy, advertisers can target key voter blocs, such as churchgoers (those recently observed at a church) or blue-collar workers (those observed at a manufacturing plant or construction site).

Geodemographically segmenting the United States by 2016 presidential voter records

Segmenting by political affiliation can help politicians focus their campaigning on key swing counties and neighborhoods, highlighted here in purple.

Source: Ali Zifan, Wikipedia

Even e-commerce companies can leverage geodemographic segmentation.

While geomarketing is usually thought of in terms of brick-and-mortar or offline businesses, e-commerce websites are starting to invest more and more in offline data.

Instead of targeting nationwide to get to every possible customer, e-commerce companies are relying on geodemographic segmentation to highlight their most probable customers. Tapping into census data like income, racial composition, and family structure helps online brands pinpoint those locations that have residents who share the most in common with their ideal customer persona. This, in turn, allows them to spend much less while getting just as much, or even more, in return.

If, for example, you run an online store dedicated to new parents and know that your target market is in the mid-to-upper end of the income range, you can use geodemographic segmentation to target those locations with a high concentration of upper-income young parents. Both of these attributes are hard to pinpoint using online behaviors alone but can be readily found in location data (in this case, the census).

Try it out today

Ready to use geodemographic segmentation to better understand and communicate with your target customers? Try it out today with Managed Service and gain access to proprietary offline insights and a team of GIS analysts working to tell the story of location.

Update (4/4/18): Geodemographic segmentation is now also available in our self-serve product, Spatially Ads, under the 'Custom Audiences' targeting objective.

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Recommended Content:

How To Use Custom Audiences For Rich Demographic Targeting

The Evolution of Hyperlocal Marketing: Tapping Into Spatial Behavior

David vs. Goliath: How Small Businesses Can Use Geo-Conquesting To Undercut Competitors

Location Intelligence: A Quick Guide for Modern-Day Businesses

Right Customer, Right Place, Right Time—Put Them Together with Location-Based Advertising

How Small Businesses Can Leverage Location Intelligence

5 Ways To Grow Your Business With Location Intelligence 

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