Which Differences Make a Difference?

In our first blog in this series, we dug into the power of empathy and what happens when we view customers as people, not data points. In the second, we explored how marketers often misread customers by relying too heavily on assumptions and stereotypes. We introduced the idea of the rider and the elephant. The continuous subconscious emotional decision making of the elephant constantly in tension with the rational conscious side of the rider. This third piece builds on that foundation by asking a deeper question:

How do we find the differences that truly matter—the ones that change how we understand our customers?

Anthropologist Gregory Bateson once described information as “a difference that makes a difference.” Not all data is meaningful. Not every difference counts. But when a difference shifts our understanding, it becomes information. It becomes insight.

This idea resonates deeply in agri-marketing, especially in customer research. Because in a sector where physical variables like acreage, commodity type, or input usage dominate how we categorize farms, it’s easy to forget that the human variable—the farmer—is often the biggest driver of behavior. We have found that a human centred approach to understanding your customer can lead to those “AHA” moments. This approach includes 3 elements.

1. Start With the “Farmers, Farms, and Farming” Problem

Agri-marketers are strong at understanding farms—land size, soil type, and output. We're good at farming—practices like no-till, rotation, and harvest logistics. But the farmer—the decision-maker, the person with beliefs, history, and aspirations, often gets the least attention. It is essential that all three aspects of our customer get equal consideration.

A human-centered approach means recognizing the context of the farm and the practice of farming, but focusing on the farmer’s goals, motivations, and relationships.

In one of our studies, we found that a farmer’s alignment with rural cultural norms was a stronger predictor of management style than farm size or commodity. In our Farm Women research, the key to understanding a woman’s experience on the farm wasn’t the operation type—it was her relationship to rural culture and how that shaped her role and identity.

These are the kinds of differences that make a difference. They aren’t always visible in spreadsheets. But they reshape how we think—and how we market.

2. Frame the Research Problem Through a Human Lens

Farmers are humans first, farmers second. So many of the things we want to understand (how people perceive brands, learn about products, and make decisions, etc.) are fundamentally human questions. And they benefit from what behavioral economics, psychology, and B2B research have already taught us.

One lesson from these fields? What seems irrational on the surface is often completely rational in the customer’s mind.

That’s why we often start with qualitative research—open conversations that uncover how people think, talk, and make trade-offs. It’s also how we learn the language our customers use, which can dramatically change how we communicate.

Take this example: A client once told us that “independence” mattered equally to all farmers, based on survey results. But our qualitative interviews revealed that farmers defined “independence” in five distinct ways. When we tested those definitions in a follow-up survey, real differences emerged between segments—insights the original research completely missed.

3. Frame the Data Analysis Around Insight, Not Assumption

Qualitative research is powerful for revealing hypotheses, but it’s only part of the picture. In our Farm Women study, we formed a strong hypothesis: that women raised in rural communities would view farm-related barriers differently than those who weren’t. This idea didn’t come from a demographic table, it came from repeated stories we heard in interviews.

One respondent put it clearly: “It doesn’t matter to me that I didn’t grow up on a farm—but I know it matters to others.”

This is a perfect example of what Daniel Kahneman described when he said, “The human mind is a machine for jumping to conclusions.” What feels true often becomes a shared truth—even if it’s unspoken.

To validate this, in addition to cross tabulation, we used additional layers in our quantitative approach:

• Principal Component Analysis identified common themes beneath responses.

• Cluster Analysis grouped women by shared attitudes and challenges—not by farm size or crop type.

• Discriminant Analysis revealed how these groups related to one another, building a fuller picture of how women experience their roles on the farm.

The result? We uncovered five distinct models of farm women’s experiences—each one grounded in evidence, not stereotype.

The Insight That Matters Most

Any research respondent—farmer or otherwise—is influenced by cognitive biases: memory errors, social norms, aspirational thinking. That’s why human-centered research requires more care in study design. In the Farm Women study, we adjusted terminology, question order, and language to reduce bias and capture more honest responses.

We also leaned heavily on open-ended questions, letting participants speak in their own words—because that’s where the “differences that make a difference” often emerge.

Bottom Line: Human Insight is Your Competitive Edge

In a fast-evolving ag industry, where farmers face complex, high-stakes decisions every day, marketers who understand the human side will have the advantage.

Yes, data matters. But data without empathy, without context, without human insight is just noise.

The future of agri-marketing won’t be defined by how much information we gather, but by our ability to recognize the differences that make a difference.

Let’s Talk
If you’d like to chat about how this approach might help your next research initiative, I’d love to hear from you. Drop me a line at maurice.allin@centricengine.com.

And stay tuned for the final blog in this series, where we’ll explore why the most effective marketing speaks to both logic and emotion—and what we really mean by the idea of emotion - it might no be what you think!