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How To Use Customer Demographics To Segment Markets (Spoiler Alert: Don't!)

Feb 9, 2016 11:18:50 AM

Effective marketers aim for “the right product, price, and message for the right customer at the right time. Today, technology makes it possible for us to customize and distribute our offerings and messages to very specific, targeted audiences.

But if you don’t understand what drives customer behavior, you can’t develop the right marketing mix.

One common practice can lead marketers astray: the use of demographic variables as the primary basis for customer segmentation.

What are market segments?

Market segments are groups of customers who differ in their needs and their likely responses to marketing efforts. Within a segment, needs and benefits that customers seek are similar. Between different segments, needs differ. Firms better serve the market and make more money by recognizing these differences and leveraging multiple offerings, price points, and messages designed in response to this variance.

Demographic variables like age, income, life-stage, and education tend to be a cornerstone of market segmentation practice in most organizations. When people think “segmentation, they automatically think about groups like millennials, baby-boomers, and ‘tweens - all based on demographic distinctions.

The reason demographic variables are popular is that they are easy-to-measure, widely published, and commonly accepted in practice. Demographic groups are easy to find through various media.

As such, the terms “segment and “demographic are often used interchangeably as executives and analysts refer to “target segments as “target demographics.

But here are the problems with this practice:

Problem 1: Customers within a demographic segment can have very different needs and values

Let’s use income as an example. When we build a marketing program for say, kitchen appliances targeted to “high income consumers, we are implicitly assuming that somehow income defines what consumers need in appliances. But, outside of an ability to pay more than lower income consumers, what does income have to do with varying needs or tastes for a dishwasher? Nothing, really.

To be fair, knowing that the target market is defined by income helps you build a media plan, because you can identify the types of media to which higher income folks are commonly exposed. However, higher income itself may say very little about brand preferences, factors impacting customer choice in a category, and price sensitivity (yes, we can find highly price-sensitive consumers even in higher income groups!).

Tom Reynolds, a widely-cited scholar, entrepreneur, and advisor to a large number of firms worldwide on marketing strategy, uses the following scenario to illustrate this problem:

There are 2 men. They are the same age and graduated from the same high school. They each marry their high school sweetheart and purchase houses a block away from one another. They both work in the construction trade, making roughly the same income. Each family has two kids, a boy and a girl.

Yet one man is a democrat, the other a republican. How can this be so?

It’s easy to imagine the answer. These men differ in their values, perhaps a function of their upbringing or exposure to very different influences growing up, all despite their identical demographic profiles.

Demographics don’t predict needs and values within a particular product or service category very well. Our needs, values, and preferences are much less a function of our demographic characteristics and much more a function of individual hard-wiring and developmental influences.

To illustrate the point, consider the hottest demographic segment these days: the millennials, with birth years 1981 to 1996. This group has received considerable attention, both on their workplace and marketplace behaviors. Very broad generalizations are often made about millennials (e.g., “they value authenticity1). Some of these generalizations may be true, but they provide very little specific insight into developing new products, setting price, or building marketing communications programs.

Further, evidence is beginning to show that millennials do not differ significantly from other demographic groups in many important ways.2 Most importantly, though, is the recent finding that within this generation, there exist several sub-segments that differ dramatically in their brand awareness, purchase drivers, and attitudes.3 This makes drawing general conclusions about the aggregate purchase behavior of millennials suspect at best.

Problem #2: Failed intuitive “best guesses about preference

Without a deeper study of the meaningful “benefit segments within particular demographic groups, managers will tend to make broad intuitive generalizations in predicting the values and preferences based upon demographics (e.g., “higher income consumers are less price sensitive).

Here is a classic illustration of the risks in relying on that intuition:

Let’s say you’re the brand manager for Sparkle, a toothpaste brand distributed throughout the U.S.

With fresh demographic data about purchasers in hand (age, income, family size, education), you conclude that large families are an attractive target market. That’s your best guess and seems to make intuitive sense.

You and your team gather around the conference table to hypothesize about the primary driver of toothpaste sales for large families. The general consensus is that – because of the volume of toothpaste consumed over the course of a year – large families are very price-sensitive, driven by low price as well as price promotions. Therefore, the team travels down a path of building an aggressive price promotion program to increase demand among large families.

An Alternative: Rather than starting with demographics, you might have alternatively started by considering the benefits that different consumers might seek. That is, instead of asking “what demographic segments look attractive and what are their needs? you might have begun by asking “What’s important to consumers in toothpaste consumption? Do different groups of consumers differ on the benefits they seek?

In almost every imaginable market, the answer is a definitive YES.

In fact, in this actual case, the team discovered four primary benefit segments of toothpaste customers:

  • Sensory: Seek great flavor and an interesting product appearance
  • Sociables: Seek bright white teeth
  • Worriers: Seek to prevent tooth decay
  • Independents: Want low prices

Let’s say we did this segmentation analysis and showed It to your team. They would likely say “that’s fine, but all it tells us is that our price sensitive large families are in the independents segment.

And... they would be wrong! As it turns out, in this case study, it was the decay prevention segment (the Worriers) that contained a “disproportionately large number of families with children. This segment likely included a lot of parents who were concerned about the dental health of their children and the large dental bills that would likely follow if they did not try to prevent tooth decay.

In this case, segmenting by “benefits sought rather than household size would lead to a very different marketing program for the brand.

Worriers not only represent significant volume potential (given the incidence of large families), but are also likely willing to pay for health benefits today to save on much more expensive dental bills (and cavity filling trauma!) tomorrow.
Therefore, a focus on health and cavity prevention in product development and communications targeted to the Worriers would likely be far more effective than creating a bargain-basement brand based upon intuitive speculation about the price sensitivity of large families.

Demographics describe but don’t predict

Rather than being the primary basis for segmentation, demographics should instead be used to describe benefit segments after they have been identified. In this sense, demographic variables are used to locate and connect with particular benefit segments, rather than being used as a weak foundation for identifying differences in customer needs, leading to speculative (risky!) marketing actions.

In conclusion, probably the best summary statement about the limitations of demographic variables as segmentation variables was offered by Russell Haley when he was VP and Research Director of a leading advertising agency in New York City:

"Unfortunately, a number of recent studies have shown that demographic variables ... are, in general, poor predictors of behavior and, consequently, less than optimum bases for segmentation strategies."4

Amazingly, Haley’s observation was offered almost 50 years ago, in what became a seminal Journal of Marketing paper on market segmentation practice.

So, give Haley the credit for this wisdom, but the point is still very relevant. Use the insight by putting demographics in their proper place: after benefit segments have been identified.


  1. Schawbel, Dan (2015), "10 New Findings About The Millennial Consumer," Forbes (January 20),
  2. Liesman, Steve (2015), "Millennials not so different when it comes to work: Survey," CNBC
    Special Report, November 3,
  3. Interbrand Design Forum (2015), "A New Perspective on Millennials: Segmenting a Generation for Actionable Insights for Consumer Goods Companies and Retailers," January, white paper co-sponsored by Oracle.
  4. Haley, Russel (1968), “Benefit Segmentation: A Decision-Oriented Research Tool, Journal of Marketing, 32 (July), 30-35.

Topics: General

Joe Urbany
Written by Joe Urbany

Cofounder of Vennli and Professor at the University of Notre Dame

Joe is a core marketing faculty member in Notre Dame’s MBA program and past Associate Dean of the Mendoza College of Business with numerous publication credits related to customer decision making and growth strategy.

In 2010, Joe Urbany co-wrote a book entitled Grow by Focusing on What Matters: Competitive Strategy in 3-circles. The premise of the book is that growth and competitive advantage are about effective positioning. The model facilitates speed of understanding and action by focusing strategic attention on what impacts customer decisions. It has been applied in over 800+ MBA projects at Notre Dame. Co-founded in 2013 by Joe, Vennli is based on this proven model. Vennli brings the model to life through the use of collaborative technology and providing a platform that makes an already faster and more intuitive process even more accelerated and streamlined.

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