While some B2B business products and services can be mass marketed (e.g. office supplies, office space, accounting services), most are better served by targeting specific groups of customers, with messaging tailored toward their industry or sector-specific needs. That’s why a good market segmentation study will identify groups of people who are "most likely" to purchase or use a particular product or service, helping companies maximize sales and profitability.
Segmentation can be conducted a priori, which, in Latin means “from before,” or post hoc (“after this.”) Within the context of market research, an a priori market segmentation model is not derived from any customer data or study, but is drawn from or based upon a widely known variable or classification scheme.
Examples of a business-focused a priori segmentation study include focusing on a specific industry, job title, company size, or geographic location. To be useful, these segments should be well defined, stable, easily repeatable, and generally accessible to the researcher, and can provide basic insights into customer behavior.
Why use a priori segmentation?
A priori segmentation is based on the notion that there are certain stereotypes about different groups. For example, companies that offer small business loans likely will choose not to market their services to companies that are above a certain revenue ceiling, since these firms likely will choose alternative, less-costly or more favorable business financing products. Similarly, companies that offer business training services will usually segment the market to only focus on the job titles and industries that match up with their course offerings. It generally does not make sense to offer anti-money laundering compliance training courses to workers not involved in the handling of money as part of their job description.
The primary advantage of an a priori segmentation model is that it’s the simplest method of segmentation, and a model can be developed quickly and inexpensively. For certain products or services, it can be a cost- and time-efficient way of getting fast insights, and is particularly useful when the target product or service can be directly linked to a specific segment. Simple consumer examples include segmenting the audience for baby diapers into new parents, grandparents, and child caregivers, or targeting senior citizens when marketing reverse mortgages. While there may be exceptions to the stereotypes employed to segment the market, it’s reasonable to assume that a large percentage of each segment will exhibit similar characteristics.
Challenges with a priori segmentation
However, a priori models may only be slightly more effective than mass marketing, since the models are based on assumptions, rather than actual insights about a segment. If the underlying assumptions about the segment are not well known, misinterpreted, or if the segment is shifting or evolving, key insights likely will be missed. For example, segmenting the market for social media by age (assuming that only people under 50 use it regularly) will leave out insights from active users over that age. Furthermore, in this example the use of a hard, arbitrary variable (the 50-year-old age cutoff) also ignores the fact that this target group will shift of the demographic, but will continue to have valuable insights that should be considered.
Next week, we’ll discuss post hoc segmentation techniques, and how they can be used to uncover more specific insights within a segment, as well as ensure that unforeseen segments are properly identified.