The Average Customer Is a Lie You Can’t Afford

There’s an old line about the statistician who drowned crossing a river that was, on average, three feet deep. 

It’s a joke. It’s also the most expensive mistake in commercial strategy, and we make it constantly. We take a population of wildly different human beings, average them into a single figure — “the HCP,” “the patient,” “the customer” — and then build a strategy for a person who does not exist and never did. 

The average customer is a lie. A useful-sounding, data-backed, utterly fictional lie. And in a market where growth is getting harder, it’s a lie you can no longer afford. 

Why Does Building Strategy Around “The Average Customer” Fail? 

The brand plan speaks to “the physician.” The campaign addresses “the patient.” The forecast models “the market.” And performance is flat, because the strategy is aimed at an average that behaves like no real person in the population. The high-value skeptic and the low-value enthusiast cancel into a bland midpoint, and the plan speaks fluently to nobody. 

So the team commissions a segmentation. Good instinct — and too often gets back the wrong kind: seven tidy segments sorted by specialty, volume, and demographics. Clean. Data-rich. And nearly useless, because it tells you what people are, not how they decide or whether they’ll move. 

Behavioral healthcare research backs this pattern up directly: analysis of what actually differentiates HCP and patient response finds that attitudinal segmentation — sorted by beliefs and behavioral bias, with demographic and prescribing data layered on afterward — consistently outperforms segmentation that starts from demographics alone.¹ Sorting by who people are gets the order backward. 

Why Is Sorting a Population Different From Prioritizing It? 

A segmentation is a data exercise until insight makes it a decision. Sorting the population is the easy, mechanical part — Better Data doing its job. The part that matters, the part that changes what you do Monday, is knowing which segment holds the growth, what belief or bias or readiness sets them apart, how you find them in the real world, and what you do differently when you do. 

That’s not in the demographics. It’s in the behavior — the attitudes, the cognitive biases, the readiness to change. 

Why Isn’t Unmet Need the Same as Readiness to Change? 

And unmet need is not the same as readiness. The person with the greatest need may not be the person most prepared to consider something new; they may require trust-building, different support, or a different sequence of information before a clinical message can even be heard. 

A commercially useful segmentation therefore has to arrive with activation built in: whom to prioritize, what each group needs to understand, where they seek information, how communications should be sequenced, and which support experience fits their real-world behavior. 

A segmentation without that activation layer tends not to survive contact with the field at all. Broader research on why segmentation projects fail points to the same failure mode across industries: even a well-built segmentation is close to worthless if it can’t be operationalized — mapped to real outreach, owned by the teams executing against it, and tied to what reps and campaigns actually do differently for each group.² 

How Does the Insight Equation Apply to Segmentation? 

Whom to prioritize is the decision. A segmentation without that insight is a filing system. Data multiplied by near-zero insight collapses to seven boxes and no priorities. 

Why Does a Segmentation Need to Be Revisited Instead of Treated as a One-Time Deliverable? 

And readiness moves. The segment that’s persuadable this quarter may harden the next, as competitors and guidelines and habit do their work. A segmentation frozen in a slide two years ago is describing a population that has already changed. Whom to prioritize is a live question, not a one-time deliverable. 

What Should Commercial Teams Ask Instead of Building for the Average? 

So stop building for the average. 

That customer drowned in a river of their own making. Ask instead: which real, specific, behaviorally distinct group holds our growth — and what do we do differently to win them? 

That’s the segmentation my team at Shapiro+Raj builds as a life sciences insights consultancy. Not boxes. Priorities — grounded in how people actually decide, not what they happen to be. 

The average is comfortable. It’s also fiction. And you cannot win a real market with a strategy built for a person who isn’t in it. 

¹ Healthcare Research Worldwide, “Segmentation in the Pharma Industry: How to Create Resilient Strategies,” Quirks.

² Greenbook, “Why Most Market Segmentations Fail — And How to Make Yours Work.”