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Digital Birds of a Feather: The Value of Demographic and Psychographic Validation

Written on
Mar 27, 2014 
Author
Ray Kingman  |

ADOTAS – A great deal of technology and personal energy continues to be expended trying to identify online audiences on a one-to-one basis.  Entire industries have been built around inferring interests, intentions and behaviors from digital footprints.  All this comes from the belief that one-to-one tracking and the collection of digital evidence will enable marketers to identify customers and prospects with more accuracy and greater reach.  But so far the results have been disappointing – often difficult to measure and financially disappointing – especially when compared with traditional marketing techniques.

For all of the algorithmic funnel analysis and efforts to track and retarget, online marketers too often overlook some very simple and proven approaches that will identify and reach more of the exact customers their businesses depend on.

Think about your community, your neighborhood and your street. Are the people around you fairly similar to you in age? Ethnicity? Income? Political views? Chances are the answer is yes. Sociologists call this the “rule of affinity” and it boils down to the idea that people tend to live around people like themselves – sometimes intentionally, sometimes due to economic self-selection.

Data scientists and marketers have acknowledged this pattern for a long time. The Census collects, aggregates and reports population data at a neighborhood level because of the proven statistical similarities. Database marketers almost always segment or cluster prospective customers by location and demographics.  Retail trade-area marketers often target campaigns at a neighborhood level to maximize coverage and accuracy. For years they have been doing a great job of zeroing in on customers based on their proximity to the store and their demographic attributes and affiliations.

In the digital world this neighborhood-level marketing model never seemed to take hold. One-to-one behavioral/intent targeting technology always held so much more promise that marketers turned their backs on this tried-and-true technique.

The first priority should be to know your customers. Most can describe their customers on multiple levels such as lifestyle, buying habits and propensity to spend. However, from a digital perspective, the drive to validate a one-to-one relationship with each prospect means that targeting has more-or-less become a process of elimination; like sifting through a massive online haystack to find the right needle.

If you know all kinds of details about your customers, why look for them individually in haystacks? Why not see if you can identify clusters of customers all at once? With demographic and psychographic validation you can create a very clear customer profile. If you have an accurate customer profile, you can also identify the neighborhoods where those people live, even in the digital world.

The current approach to digital advertising depends on cookies (or other identifiers) on browsers to help target their customers and prospects. These identifiers are becoming less and less effective every day. On desktops they are deleted. People opt-out or apply Do Not Track.  They don’t even work on the majority of mobile devices.  On top of that, multiple cookies can point to the same person. At the end of the day, only about one-third of online consumers can be accurately reached using what is still considered the standard in digital targeting.

A location-based approach is completely different. If a neighborhood is a 90-percent match for your audience, why not reach out to everyone in that neighborhood? The ability to match physical addresses through a range of IP addresses exists. Being able to identify and target an audience based on all the variables that can are associated with a neighborhood or a business is a far richer and more statistically accurate approach than inferences based on one or two attributes a single cookie can deliver.  While the targeting isn’t one-to-one, as a marketer concerned about reaching 100% of the target audience as well as accuracy, neighborhood targeting just makes sense.

It makes even more sense if you are able to target that audience again and again without duplicating the onboarding process.  It allows you to find qualified new neighborhoods that you would never have considered through typical online targeting. With better targeting in place many digital campaigns could be far more effective than they are today.

Let’s break this down:

  • Know your audience – where they live or work — and you’ll know much more about them than you do today.
  • Identify all attributes that make them your customers – their lifestyle, demographics, ownership, preferences, etc. – without preconceptions or inferred assumptions.
  • Locate customers in the physical world and gain more insights into who they are.
  • Find similar audiences everywhere that they exist – with a robust profile you can accurately match known customers with prospects that look just like them.
  • Map those neighborhood locations to the digital world using IP addresses.
  • Run full-strength digital campaigns that connect validated CRM level audience insights with your digital campaigns by matching the offline and online worlds.

And your final step: Be amazed at the difference in results.  No matter how technologically sophisticated the current platforms are, there is something to be said for applying time tested marketing techniques to your digital campaigns.





Ray Kingman has been at Semcasting, Inc. since its inception, leading the company in the development and commercialization of its automated targeting and data offerings. As an experienced innovator in content management, analytics and data visualization fields, Ray directs the day-to-day operations of Semcasting, Inc.

Before coming to Semcasting, Inc., Ray served as the CEO of LightSpeed Software, a content management solution built through the acquisition and integration of multiple providers in the search, analytics, content management, authoring and portal platform spaces. Prior to LightSpeed, Ray was the founder and president of a division of Thomson Reuters, where he focused on providing syndicated web content solutions to self-directed investors and retail brokerage firms. Ray Kingman was also the founder and president of DeltaPoint, Inc., a developer of analytics and data visualization products, and led the firm from its inception to its initial public offering.

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