Demographic segmentation strategy is based on the assumption that a specific group – based on age, gender, etc. – is the primary consumer of your product or service. Regardless of the validity of this assumption, it does not often provide insight on why this demographic segment selects the product in question or how they use it. For that reason segmenting a market by demographics has very limited utility. It has become so popular only because no better intelligence about customers was available at the time it was introduced.
Today, a much better approach to market segmentation is available. Grouping potential customers according to the expectations they would have from a proposed product is much more useful. This outside-in approach is similar to the “persona” concept often used by product managers, but uses actual market intelligence instead of imaginary characters.
The first step is identification of “the job-to-be-done” by the proposed product to be “hired” by the customers.
The second step is identification of the products/services the customers use today to do that “job”. This list will likely include products/services that you would not normally consider your competition, but customers may.
The third step is aggregation and analysis of a statistically representative set of “stories” describing the experience of customers who have used currently marketed products/services to do that job. I use the word “stories” deliberately to describe unsolicited and unstructured descriptions of the experiences in the customer’s own words. Any use of survey or focus group methods will “color” the output with a 3rd party bias. The best content is customer biased only.
The result will expose the attributes of the experience that are most important from the customers’ perspective. It will also provide an assessment of how well each attribute met the expectations of these customers. Focus on the attributes with low scores may provide important insight for designing a product that is very likely to take this market segment by storm.
Click here to request a copy of the Mining Social Media to Boost Segmentation paper published by QUIRK’S Marketing Research Review.
If demographic data is pertinent for your product, you can compile it’s distribution by an attribute to improve your chances for success even further. As the GPS
technology taught us: The multiplicity of signal sources results in better decision quality.