For more than half a century, demographics has been the primary method used by those in marketing and advertising to define populations of consumers.
More recently, thanks to interest tracking from social networks, behavioral data from search outlets, and lifecycle forecasting, there are more robust methods for describing potential customers.
The post-WWII rise of mass-produced consumer goods also brought about the rise of mass-market advertising. During the 1950s and 1960s, television was the medium of choice to deliver the greatest number of eyeballs for advertisers.
Marketers needed a way to quickly identify groups of prospects, so they sorted people according to when they were born. Thus, the 78 million people born in the generation following WWII were called “Baby Boomers.” Naming the succeeding generations was reduced to a mere single letter of the alphabet.
|Name of Generation||Number of years in generation|
|Baby Boomers (1946 – 1964)||18|
|Generation X (1965 – 1980)||15|
|Generation Y (1981 – 1994)||14|
|Generation Z (1995 – 2005)||10|
The Formula Is No Longer Effective
But now, in the 21st Century, that classification scheme has fallen apart. The year that someone was born is of little use when it comes to predicting how likely he or she is to buy a product.
The rate of change is accelerating. Generations have been getting shorter and smaller. Fewer unifying characteristics exist among each group. Fragmentation is the norm.
With the meteoric rise of the social web, people are able to self-select into groups so specialized, so disjointed, and so fleeting, that no single, sweeping approach can be successful at forecast marketing performance.
Adding more demographic information to the mix is not enough to make a meaningful difference.
The Birth of Psychographic Profiling
Psychographics take into account the mental model of the consumer in the context of a customer lifecycle.
An example of this can be seen in Amazon.com’s innovative “recommended products” and “users like me also bought” customized content. Its algorithms are able to instantly assess purchase history and patterns to predict what customers might be interested in buying.
Here’s how a psychographic profile might look different from a traditional marketing profile target for a childcare provider:
Age: 25 – 34
Household Income: $70K+
First child between 5 and 9 months
Spend $1,500/mo online
Live 1,000+ miles from parents and in-laws
Lives within 3 miles of store location
Psychographics provides more useful information about a target audience. Social profile data, behavioral data and customer lifecycle data are being combined and compared to identify people who are most likely to buy.
Social Profile Data
Profile data from social networks are gleaned from all the fields users grant permission for marketers to access. These bits of more personal information are used to create a closer relationship with a customer.
Fields are set up to encourage the user to share information such as relationship status, alma mater, interests and occupation. Sophisticated data management tools give research companies the opportunity to deliver packages of like-minded consumers to marketers.
Social profile data is the key that unlocks psychographic insights. The level of detail provided by social data, when compared to standard demographics, is the difference between performing surgery with a scalpel or a butter knife.
Retargeting advertising messages is an accepted practice among marketers. Ads that follow users from site to site are commonplace. Ad networks quickly incorporated the ability to place cookies in users’ browsers and display specific ads to them any time they visit a site that belongs to a particular network.
Perhaps a more subtle, yet effective system of ad targeting will structured to tell the customer a story over time, triggered by specific behavior. In the future, ad networks and clickstream data aggregators will form partnerships that monitor and guide a customer forward, step by step, toward the purchase event.
Site content and product recommendations will be shaped by clickstream analysis. The ability to personalize the content directed to specific visitors based on their behavior is here. The end result is an engagement experience that mimics the relationship between a thoughtful and proactive store owner and a longterm customer.
Customer Lifecycle Data
Significant indicator purchases, such as buying diapers for the first time, identify a customer entering a new lifecycle. Other indicators, like shipping address changes, substantial purchases of furniture, and patterns of purchases of higher-value goods can be a sign of the start of a new customer mentality or lifecycle phase.
Because many lifecycle patterns are predictable, marketers are able to compare the behaviors of identified groups with those of a group in an earlier stage in the cycle. Each group will receive messaging tailored to its emotional and logical motivators.
With the old model which relied on demographics alone, specific groups would not be addressed by content that has been fine-tuned. With psychographic data, far fewer impressions are wasted.
Paradigm shifts have changed the course of marketing before. In the 1960s, advertisers who aligned themselves with the power of television and demographic data built category-leading brands. Those who were unwilling to utilize TV were left behind.
The internet and digital technology offers a similar opportunity: take advantage of the capabilities afforded by psychographics and the new media or risk being left out.