Personalization has become an expectation, but many brands still struggle to make it useful. 75% of customers are more likely to buy from brands that can deliver personalized experiences, while only 45% of brands say they are successfully delivering the personalized, relevant content customers demand. The gap suggests that having customer data is not the same as understanding what should be personalized.
For Nathan Koengeter, that is where segmentation should begin. His background in market research, consumer insights, political fieldwork and analytics points toward a more useful question than simply asking who the customer is: why is the customer buying? Demographics can describe a group. Purchase motivations can explain the decision.
Similar Customers Can Be Different Buyers
Two customers can be the same age, live in the same city, earn similar incomes and purchase the same product for completely different reasons. One may prioritize price. Another may value convenience. A third may be trying to reduce risk. A fourth may be buying for quality, identity or status.
A demographic segment can put all four people in the same bucket. Nathan Koengeter’s preferred research question separates them according to the factor actually moving the purchase.
That distinction changes the business action. A price-sensitive segment may respond to a promotion. A convenience-motivated segment may care more about delivery speed or a simpler checkout. A risk-sensitive segment may need stronger guarantees or evidence. Nathan Koengeter views useful segmentation as a tool for changing strategy, not simply describing an audience.
Personalization Needs a Reason
71% of consumers expect companies to deliver personalized interactions and 76% become frustrated when that does not happen. Those expectations create pressure to segment customers in ways that are actually relevant to the experience.
Nathan Koengeter sees a limitation in personalization built mainly on surface-level attributes. A message can include the right name, age group or geography and still be irrelevant because it does not match the customer’s purpose.
Motivation-based segmentation gives personalization a reason. Nathan Koengeter would not communicate with someone buying for convenience in exactly the same way as someone buying for prestige, control or reassurance, even if the two customers look nearly identical in a CRM.
Start by Listening Before You Build the Categories
Motivations are difficult to define accurately from a conference room. Interviews, open-ended responses, observation and field research give customers room to describe tradeoffs in their own language.
Nathan Koengeter’s field-research background is useful here. Before working deeply in enterprise analytics, Koengeter spent time gathering responses directly and learning to notice recurring language, hesitation and the difference between an initial answer and the explanation that follows it.
Those qualitative signals can become hypotheses for quantitative research. Nathan Koengeter uses the two approaches as complements: qualitative work helps discover the motivational structure; quantitative work tests whether the differences are sufficiently common and stable to support a segment.
A Segment Should Explain a Business Difference
Kantar’s segmentation framework describes effective segmentation as grouping people based on what they buy, use, think and feel, with attention to needs, pain points, decision drivers and barriers to switching. That framing is close to the standard Nathan Koengeter applies: a segment should illuminate a difference that changes what the organization does.
Do the groups differ in purchase probability? Price sensitivity? Product preference? Retention? Channel choice? Response to messaging? Lifetime value? Nathan Koengeter asks these questions because a memorable segment name is not a business outcome.
If two segments behave similarly and require the same commercial response, Nathan Koengeter would question whether the distinction deserves operational attention. The strongest segmentation sits at the intersection of human explanation and measurable behavior.
Motivations Are Contextual
A customer does not carry one permanent purchase motive into every category. The same person can prioritize speed when ordering dinner, reliability when buying business software and price when booking a routine trip.
Nathan Koengeter therefore treats segmentation as something that should be revisited. Economic conditions change, products mature and competitors alter expectations. A segment that accurately explained a market two years ago may become less useful if the context around the decision moves.
Segmentation Should Explain the Purchase
Businesses already collect enormous amounts of customer information. Nathan Koengeter does not see an advantage in creating more categories simply because the data allows it. The advantage comes from identifying distinctions that explain behavior well enough to improve a decision.
For Nathan Koengeter, useful segmentation connects qualitative insight, quantitative evidence and business strategy. It starts with what people are trying to accomplish, validates whether those motivations create meaningful behavioral differences and then builds the commercial response around them.
When Nathan Koengeter frames segmentation this way, it stops being an exercise in labeling customers. It becomes a model of the decision the customer is actually making.
