Geodemography can improve finding and contacting customers
By Danny Heuman
In an increasingly data-driven world, consumers leave trails of digital crumbs whenever they wander the Internet, wave their loyalty cards or charge something on credit. By collecting these data, organizations believe they will be better able to locate and reach their customers with the prospect of gaining additional sales.
It’s a sensible approach. However, these data crumbs on their own can only take you so far. Data can tell you where your consumers have been or what they may have done in the past. But that information does not tell you who those people are, where they are going or what their preferences might be. While advertisers and marketers see some value in understanding where consumers were at some point in time, they are more focused on what those people might do next and where they can find others like them.
The power of geodemography
Data are a valuable resource, but they need to be actionable to offer real value to an organization. The most effective way to transform data into insight is through geodemography. Geodemography is a branch of market research that assigns the attributes of small areas like neighbourhoods to the consumers who live within them and, based on these assignments, divides the consumer marketplace into meaningful segments that are locatable and reachable. Geodemographers have been helping organizations gain consumer insights without infringing on privacy for more than 40 years, which is why this approach has not only survived the arrival of big data, it has thrived.
Geodemography looks for patterns in local communities and neighbourhoods. It straddles the traditional techniques of national sample surveys and the micro-precision promise of big data and links them together using geography as the unifying factor. It’s based on the premise that people tend to cluster in locales that share similar values, demographics, beliefs and affluence. While these local areas are not homogenous, statistically they share enough similarities that they can be treated as such.
The concept that households within neighbourhoods can be bound together by a set of shared traits is more than just a theory. The ability of geodemographers to analyze communities and break them into segments has helped countless organizations in every industry identify and engage their target markets.
As established as this field is, some companies continue to be astounded by the level of detail geodemography can provide using only a postal code. However, the results speak for themselves. Using this approach:
Heart & Stroke Lottery increased its net profit by 54%;
Mackenzie Health Foundation saw the performance of its annual direct mail and telemarketing campaign jump by 62%; and
Hydro One enjoyed a 390% higher engagement rate from their bill insert campaign.
Why geodemography works
Given the seemingly limitless supply of data that is now available, one might surmise that organizations should be able to tailor their marketing plans to individual consumers. But, in practice, targeting individual consumers is impractical and costly.
Richard Webber, one of the founders of geodemography, described why businesses are better off focusing on neighbourhoods rather than individuals.
“The more specific our targeting capabilities, the easier it is to lose sight of the contextual data that can help to explain both the social influences to which consumers are subjected and their motivations and aspirations,” he said. “If the highly specific and the contextual can be kept in balance, then it is much easier to identify the correct medium of communications as well as the message.”1
While it’s almost impossible to understand what motivates people to make a specific purchase, a data-driven profile of consumers in your target market can help you make reasonable conclusions about what those factors might be. Even without your own data, there are plenty of quality data sources available to help you get at those factors.
“Canada offers a wealth of survey data that geodemography can leverage,” explained Jan Kestle, founder, president and CEO of Environics Analytics, in The Analytics Journal. “Government and private sector organizations conduct reliable surveys on spending, media preferences, technology adoption, leisure activities, tourism and many other aspects of day-to-day living.”2
All of these data can be modelled down to the neighbourhood level, which is what makes these data actionable and measurable. In some cases, this type of standardized segmentation is all an organization needs to gain meaningful insights about their target market to make better, evidence-based decisions. This is especially true given many organizations, even today, have so little data and insight about their customers. But when paired with transaction data or infused with the richness of big data sources like mobile data, organizations can quickly, consistently and cheaply build detailed profiles of their customers without the need of costly customer surveys.
For instance, say you collected mobile data that observes a set of devices regularly showing up at fast-food restaurants. By relying on these data, one might conclude that those individuals enjoy fast food. But what happens if some of those same devices also routinely show up at high-end restaurants? Without a broader understanding of who is using those devices, there is no way to know what is driving those visits.
By using geodemography, using nothing more than a postal code to link the information together, you might learn many of those devices come from areas that consist predominately of young families, which may account for the fast food purchases. You might discover that many of the households from those same neighbourhoods also frequently entertain business clients at high-end restaurants.
Suddenly you know that the consumers you observed eating fast food are likely affluent and are more willing to spend on convenience than the typical family, which is a very different message from someone who likes fast food. The efficiency of geodemography is that it offers insights that don’t have to be directly tied to the observed behaviour. For instance, the geographical segment may reveal that the households in that area respond well to unaddressed mail. Or that they spend considerable time on Instagram and listening to Spotify, which could be vital to the success of your marketing efforts if you are investing in Twitter and radio advertising.
Privacy by design
Geodemography complements the use of client data if it is available, but another advantage that can’t be overlooked is its ability to deliver actionable insights without compromising consumer privacy. In a world where organizations are on constant guard against data breaches, personal data can become a liability.
Since geodemography doesn’t require anything other than a postal code to function, businesses can significantly reduce the amount of personally identifiable information they collect. As a result, in the case of a data breach, the greatest risk is that someone will expose a list of postal codes. There wouldn’t be enough information to know what a specific household purchased, let alone identify their address.
Given the costs involved with collecting personal information and maintaining a database, companies should embrace geodemography. Not only does it take complex data and make them easy to understand and apply, but it also does so in a cost-effective and privacy-compliant way.
For all of the data companies gather, they only provide them with a window into their customers’ interactions with them; it doesn’t offer any insight about whether those customers have the capacity to spend more or if they are also doing business with a competitor. Big data can help them get closer to the answers they were looking for, but geodemography is what makes these data actionable.
Danny Heuman is the chief analytics officer at Environics Analytics.
1 Richard Webber, “Why geodemographics is relevant in an age of Big Data,” The Analytics Journal (Fall 2016).
2 “Geodemography Q&A with Jan Kestle”, The Analytics Journal (Fall 2016).