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In marketing -- whether consumer packaged goods, technology, media, or our world of healthcare -- categorizing customers can be a double-edged sword. Categories or segments help us organize complexity, but they can also erase nuance. The difference between those two outcomes often comes down to how much effort and care we (as insights and commercial professionals) invest into seeing people as they truly are.
I was reminded of this lesson last year when my younger daughter’s school introduced “affinity groups,” designed to bring together students of similar ethnic backgrounds for dialogue and support.
My daughter, who is half Filipino and half white, was placed in the “Asian” group alongside classmates of Japanese, Chinese, and Korean descent. While well-intentioned, the grouping quickly highlighted the limits of broad labels. The kids in her affinity group struggled to find common ground. Their cultures, languages, and family stories were vastly different, yet reduced to a single shared identity: “Asian.”
At a dinner we hosted for the class parents -- most of whom were also raising children of mixed-ethnicity backgrounds -- the consensus was clear: the categories didn’t reflect reality. A “Latino” group, for instance, lumped together children of Mexican and Peruvian heritage, despite their distinct experiences. Meanwhile, I discovered that Caucasians like myself in my daughter's class are labeled under the moniker “white non-racist ally,” a phrase that sounded like it had leapt from the pages of Orwell.
The deeper issue was not nomenclature alone, but what happens when institutions prioritize convenience over specificity. In trying to create, celebrate and cultivate belonging, the school inadvertently alienated the very children it sought to include. And many of the parents too. None of the kids seemed to enjoy or get much from the affinity group meet ups.
The same pitfall exists in our industry. In pharma and biotech, patient segmentation often defaults to broad ethnic categories: “Asian,” “Latino,” “African-American.” These buckets may be tidy for a spreadsheet, but they are misleading when it comes to lived experience.
Consider South Asians. As highlighted in a recent and very insightful MM+M opinion piece (https://www.mmm-online.com/opinion/when-asian-isnt-specific-enough-the-hidden-costs-of-oversimplifying-in-pharma-marketing/), they face higher risks for Type 2 diabetes and heart disease, often at lower BMIs than other populations. Yet when South Asians are aggregated into the “Asian” category, these patterns vanish beneath East Asian averages. The result? Recruitment gaps in clinical trials, missed opportunities for early screening, and educational campaigns that fail to resonate.
From a behavioral science perspective, this is a textbook case of miscategorization bias: assuming similarity within a group that is far more heterogeneous than our categories suggest. The hidden cost isn’t just data imprecision. It’s alienation.
When patients see themselves only partially reflected -- or worse, not at all -- in the way we communicate, they disengage. Marketing designed for “all Asians” risks speaking to none of them. The same holds true for assumptions around language proficiency, digital access, or health literacy. The gaps we leave unaddressed are exactly where disparities deepen.
So how do we move beyond broad brush strokes? Precision in understanding people requires more than finer segmentation; it requires a shift in mindset. Here are three starting points:
1. Disaggregate the data. Go deeper than census categories. Look at subgroups within ethnic labels and identify meaningful distinctions in health outcomes, behaviors, and barriers to access. South Asian versus East Asian is one example, but there are countless others -- Caribbean versus African, Mexican versus Central American, Filipino versus Japanese.
2. Listen locally. Community-based organizations often have a far sharper and more authentic read on cultural nuance than national surveys ever will. Partnering with trusted voices not only surfaces insights, it also builds credibility that no campaign alone can buy.
3. Tailor execution, not just insights. It’s not enough to know that language or cultural stigma might be barriers; campaigns must be designed with those realities in mind. That may mean multilingual content, gender-sensitive messaging, or simply choosing different channels of communication. Precision in execution signals respect as much as precision in data.
Some may wonder whether this level of specificity is feasible at scale. But in today’s digital and omnichannel environment, particularly given the rise of tech-enabled targeting and AI-driven content creation, the barriers are more mindset than mechanics. What once was impractical is now within reach.
The upside is compelling. When people feel seen and respected, they are more likely to engage, adhere to treatment, and participate in research. In other words, nuance is not just about equity; it’s about impact.
The lesson I took from my daughter’s experience is simple: when we reduce people to convenient boxes, we may gain efficiency, but we risk losing trust. In healthcare, that loss can translate into delayed diagnoses, underrepresentation in research, and poorer adherence to treatment.
The opportunity before us is to apply the same rigor to understanding people as we do to understanding molecules. Precision in medicine has transformed outcomes. Precision in people can transform engagement.
For commercial and insights leaders, that begins with a choice: to see individuals not as members of a category, but as members of a community. That’s how we build connection, foster trust, and ultimately deliver on the promise of more equitable healthcare
