Segmentation Models Are Outdated

The 2016 United States presidential election is undoubtedly the biggest and most public error in segmentation patterns in recent memory. Most models not only predicted Hillary Clinton’s victory with a cool advantage but also ignored the demographic, racial, and geographic segments that predicted a different outcome and triggered Donald Trump’s victory.

Taking this error as an example and taking into account the obsolete common method of assessment in which segmentation models seem to exist, we must recognize that segmentation models must evolve.

Especially for companies, evolution can lead to more effective marketing strategies and more successful marketing results in our increasingly dynamic market.

Why target models can use an update

Since the 1980s, companies have spent a lot of time and effort carefully segmenting audiences based on demographics and creating characters for marketing teams. For some reason, however, these methods are increasingly irrelevant.

  • First, there is no longer a competitive advantage in traditional segmentation. Each company engages in recent base, frequency, and currency (RFM) segmentation using the same combination of demographic or behavioral overlap.
  • Second leads change faster than static models. Many segmentation models with static design or, at best, updated only a few times a year, do not prevent the rapid change in consumer behavior, especially in fast-moving markets such as technology and retail.
  • Third, the predictive power of the models does not mean that the investment is really recovered. Traditional segmentation approaches have been developed for media buying and are not very effective in an increasingly responsive one-on-one world.

Predicting consumer habits by focusing on identifiers such as demographics is an inappropriate name. Previously successful marketing campaigns based on these techniques are now also facing difficulties.

For example, Tesco was a pioneer in combining the RFM target with the one-to-one scale target in the 1990s through its Clubcard program. The program was aggressively digital at the time, rewarding customers for healthy eating and loyalty. But as the model no longer offers a competitive advantage, Tesco’s loyalty base of 20 million members is not growing today.

Benefits of transition to segmentation based on needs

Many marketers start with demographic attention because it is readily available. But America is expected to be a minority nation in 2040. As multicultural and multigenerational family structures continue to grow and diversify, it will be even more difficult to fit consumers into a demographic group.

Thus, digital behavior, technology adoption, political affiliation, and social goals are consistently stronger indicators of buying habits than more traditional segments. The transition from marketing efforts to this needs-based segmentation approach, therefore, offers several benefits:

  • A better understanding of changes in real-time in the needs of the target audience. Because needs-based segmentation models are more dynamic and flexible, they help teams maximize the impact of their messages.
  • Extensive messages and possible points of contact. Instead of isolating a buyer in a segment or offering him a selected and relevant offer only for that segment, teams can target a single lead with multiple needs through messages that meet each specific need.
  • Best time to advertise. By improving the time and context of a campaign by understanding the state of emergency, teams can explain how the concept of the message is changing dramatically. For example, a breakfast break is different from a weekend for shopping. Consumers participate in each activity with peculiarities and specific objectives, but efforts that are similarly directed under the umbrella of “food shopping” are losing their nuances.
  • Greater management efficiency. Traditional segmentation is quickly complicated in many dimensions with hundreds of microsegments. Using demand-based segmentation reduces complexity and can even lead to cost savings by simplifying operations.