Types of Segmentation
Episode 03
Market Segmentation: Episode 03 Transcript
Hello, I’m Beth Horn, Head of the Advanced Analytics Group here at Decision Analyst. And today we’re going to being discussing types of consumer segmentation.
So, historically attitudinal segmentation (which is putting consumers into groups based on their values and beliefs) and needs-based segmentation (putting consumers into groups by the types of problems they are trying to solve) have been the go-to work-horses, if you will, of segmentation. But they have limitations, especially in terms of targeting, (which is the ability for companies to locate and message to particular segments).
So, other segmentation types have evolved, such as location-based segments. This type of segmentation is based on the premise that people who live in the same neighborhood, share more similarities to one another than people who live in other neighborhoods. So, this is the idea of “birds of a feather flock together.” People who live near one another usually have similar incomes and family backgrounds and they also have a similar product and lifestyle preferences.
There are location-based segments, or also called clusters that can be purchased from various companies and appended to a segmentation data-set to enrich it. Companies can use these datasets and these data clusters to identify target segments and send direct mail that is specifically crafted to appeal to each target segment.
Another type of segmentation is transaction-based segmentation, and this is using actual purchase behavior usually collected through loyalty databases, or if you are fortunate enough to work for a company that gathers online information. This type of data is used to inform an existing segmentation. You can also add attitudes and needs to this.
Another type of segmentation is called demand segmentation. This considers different types of needs with different types of usage occasions. This type of segmentation acknowledges the fact that humans have multiple needs, multiple times of the day, and use multiple products and services to fulfill those needs. Companies are using demand segmentation to understand how their product portfolios fit into consumers’ lives.
The last type of segmentation I will discuss is microsegmentation. So this technique requires thousands of respondents in order to find small, niche groups that contain consumers who are highly similar to one another. An example microsegment might be females aged 18 to 24, who participate in outdoor activities 2 to 4 times per week, and follow a vegan diet and lifestyle. This segment might only be 1% to 2% of any country’s population, but their spending power in the all-natural, outdoor-athletic category may be quite high. This makes this microsegment particularly valuable for a company that produces such products and I expect we will see more microsegmentations in the near future.
So, thanks for watching and please join us for our next installment, Qualitative Exploration.
Presenter
Elizabeth Horn
Senior VP, Advanced Analytics
Beth has provided expertise and high-end analytics for Decision Analyst for over 25 years. She is responsible for design, analyses, and insights derived from discrete choice models; MaxDiff analysis; volumetric forecasting; predictive modeling; GIS analysis; and market segmentation. She regularly consults with clients regarding best practices in research methodology. Beth earned a Ph.D. and a Master of Science in Experimental Psychology with emphasis on psychological principles, research methods, and statistics from Texas Christian University in Fort Worth, TX.
