It is no secret that most new products taken to market do not perform to management expectations. While there may be a myriad of reasons to explain the high rate of failure, I would like to focus on the fundamental inadequacy of commonly used market segmentation methods. Don Peppers wrote that,
“Many, if not most, corporate CRM efforts have floundered or failed because they were oriented exclusively around segmenting customers by their value to the company – diamond, platinum, gold, whatever. But if you want to be smart about your customers, then you have to know how customers differ from each other in terms of what they need from you, not just what you want from them.”
Following this line of logic, most product developers fail because they segment their customers by their demographic characteristics (age, gender, education, income, etc.) rather than their needs. The assumption these marketers make is that similar demographic segment would have similar needs. The introduction of customer “personas” allows marketers to assign a proposed product’s functions and features to specific customer groups within the demographic segments. Subsequently, all these assumptions are validated by surveying consumers, who belong to the chosen segments and correspond to a “persona” as defined by product developers.
I see three fundamental flaws in the described methodology:
- Multiple layers of assumptions are constructed before the validation of an entire construct;
- The validation methods are highly subjective and often produce low integrity results;
- The method uses an inside-out view of potential customers.
These flaws lead to the introduction of products that are very difficult for consumers to differentiate, and as the result lead to lower profit margins.
The advent of The Social Customer provides product developers with an alternative segmentation method – an approach that at once zeroes in on a market segment composed of customers (not consumers) who have purchased existing products that the planned product intends to challenge. In particular, it analyzes actual customer experience with those existing products. The relative frequency with which customers mention certain attributes tend to indicate those attributes’ importance to the customers. On the other hand, customers’ satisfaction or dissatisfaction with a product in terms of those attributes tends to denote particular strengths or deficiencies. Accordingly, those white spaces where existing products are unable to meet key customer expectations present potentially lucrative opportunities for new product differentiation.
This outside-in approach may be reminiscent of ethnographic market research, but instead of actual observation of customers it relies on analysis of online customer reviews to generate much more statistically representative results much faster.