In May 2011, DM Magazine featured a Q&A with Jan Kestle, the founder and president of Environics Analytics. The topic was geodemography and how this marketing science which had been around for 40 years continued to be relevant in an era of big data, rapid digital transformation and (supposedly) one-to-one marketing.
Ten years on, and with significantly more technology and data proliferation, geodemography is arguably more relevant than ever. While some may consider the practice old fashioned and even proclaim it dead, we can only respond by saying “Geodemography is dead. Long live geodemography!”
In its most basic form, geodemography is the study of people based on where they live. Linking elements of demography, geography and sociology, geodemographic data and systems estimate (through models) the most probable characteristics of people based on the pooled profile of all people living in a small geographic area — often a neighbourhood — near a particular address. This approach provides a reliable, statistically valid and practical way to understand which consumers live where, and how they live, behave, shop and think.
Originally developed in the 1970s, geodemography helps marketers, insights managers and business strategists in all industry sectors answer some fundamental questions:
For all its advantages, geodemography has — particularly in recent years — suffered from a case of ageism and considered by some to be ‘old school’. In an era of artificial intelligence, algorithms, and access to slick platforms and consumers’ digital ‘breadcrumbs’, modelled neighbourhood-level data may not hold the same appeal as ‘real’ individual-level data.
But the fact is, this is a misguided notion. Geodemographic data and systems are more relevant than ever. Here’s what they can do:
Not every business, NFP organization or government agency has unit record customer data. While large retailers, financial institutions and charities keep track of customers and donors, there are still a large number of businesses that do not collect or have access to even the basic consumer information. Census-based demographic data that is corrected, enhanced, national in scope and projected to the postal code is an easy and reliable way to understand customers in fundamental terms such as age, sex, income, education and more.
For businesses that have customer data, their databases are likely incomplete, or not as complete as they could be. Even financial institutions, who have fairly comprehensive financial profiles of their customers, often lack insight on consumption behaviours, media preferences and consumer attitudes. Geodemographic-based data overlays can enrich transactional databases and provide valuable, actionable consumer profiles.
By their very nature, geodemographic-based data are privacy compliant. While based on actual data that are statistically accurate and a representative sample (e.g. StatCan data), they are then modelled to a small area geography such as a postal code. They are not individual-level data but provide a granular level of insight that helps organizations understand consumer profiles at the neighbourhood level.
When trying to calculate penetration, share and the size of incremental market opportunities, organizations cannot rely on their own customer data alone — they need external data to provide the ‘universe’ or denominator against which they can benchmark their customers. National geodemographic-based databases provide that benchmark and the ability to index customer profiles against the general population.
Canada has a trove of rich survey data available from reliable national sample surveys (from government, marketing and media entities) on spending, media preference, technology adoption, leisure activities, tourism and many other aspects of day-to-day living. But these survey-based variables only become usable for trade area analysis and local marketing when they are properly linked to geodemographic-based segments. This allows an analyst to combine the survey-based measure by segment for a behaviour like “go to the movies”, for example, with information on which segments live around a particular location to determine the viability of a new cinema.
Mining your in-house database can help you identify potential cross-sell, up-sell and retention strategies for your current customers. However, geodemography is the easiest way to profile your best customers in your existing file across a comprehensive range of attributes and then quantify and locate prospects with a similar profile in the broader market. The more attributes you can use for profiling, the more options you can open up for finding those attributes in the marketplace.
Many organizations have an internal customer segmentation system based on their own available data. While potentially useful within the confines of their own organization, these segments are often hard to link to external data, limited in their descriptive profiles and challenging to seamlessly activate in media channels. On the other hand, a geodemographic-based segmentation system such as PRIZM is distinct and easy to understand, can be mapped to every postal code across Canada, links to thousands of other disparate behavioural, financial, psychographic and demographic variables, and as a result, can explain and accurately predict consumer behaviour.
Geodemography allows for the harnessing of a broad spectrum of data to generate insights, but more importantly, to provide insights that are actionable. While other data sources can provide snippets of consumer insight and point-in-time views on behaviours, only geodemography can effectively link the customer, product and brand profiles to use cases such as site selection, local marketing (including traditional and digital channels), customer services, merchandising, category management and media planning and execution.
Marketers looking to target customers across digital channels can (and should) harness geodemographic segments as part of their marketing mix. Not only can these segments be targeted based on a comprehensive range of behavioural attributes and media preferences, they can also be engaged more effectively by leveraging psychographic insights into relevant messaging and creative. And given that geodemographic segments (and defined targetable audiences) are available at the postal code level, the pending disappearance of third-party cookies becomes irrelevant.
Because marketers can tie geodemographic segments back to the ground (stores, postal codes, markets, etc.), to purchase channels and to their own transactional data, the impact of marketing campaigns or other internal initiatives, such as customer service or product changes, can easily be measured and modified on an ongoing basis.
Some predicted in the late 1990s that the move to CRM systems, one-to-one marketing and household level models would mean the end of geodemographic-based data and systems. More recently, others have suggested a similar demise with the proliferation of big data and advances in machine learning and AI. Neither has turned out to be true…and with good reason.
Geodemography has a long history with proven value across all sectors: banks and insurance companies use it to develop products, services and messages that increase client retention through cross-selling and up-selling; retailers use it to identify underserved markets and areas where operations should be combined or curtailed; fundraisers use it to focus on potential donors that are likely to have the highest response to their direct marketing campaigns; and governments use geodemography to ensure that the right services are available in the appropriate areas. There’s no question — geodemographic-based data and segmentation systems are alive and thriving.
A version of this article was originally shared in the June 2021 issue of DM Magazine.
Evan Wood is EVP and Chief Strategy Officer of Environics Analytics, Canada’s leading data analytics and marketing services company. He also leads EA’s Financial Services practice group.