Why Empathy is the Strategic Engine of Product Clarity
When I named my consulting practice Empath Strategies, I wasn't making a statement about kindness or user-centricity or any of the other warm, fuzzy associations that tend to cluster around the word "empathy." I was making a claim about leverage: that empathy is the strategic engine that transforms research into product clarity.
I've spent years bridging the gap between the influential power technology has and recognizing users as critical agents of it, examining how we understand algorithmic interaction and whether our theories honor people as active experts of their own experiences rather than passive subjects. Now, in my industry practice, I'm continuing that work because the gap between research and strategic action is where agency gets lost, and empathy is what bridges it.
The Leverage Problem
Researchers want leverage. We want our work to matter, to influence decisions, to actually shape what gets built. That desire isn't wrong. It's essential. Research that doesn't influence strategy is just expensive documentation.
I saw this desire (my own included) play out recently at an industry conference. Researchers were given an exercise to design their own research method, and team after team, mine included, gravitated toward products built on maximum data collection: apps that automatically strip PII from in-home observations, tools that track usage behaviors across platforms, systems designed to capture as much behavioral data as possible. We wanted longitudinal studies that could track patterns over time, reveal how behaviors evolve, show the full context of people's lives.
The logic was simple: more data equals more leverage. If we can observe people in their actual environments over weeks or months, if we can track their real behaviors across contexts, our recommendations become indisputable. We literally watched them in their homes for an extended period. How can product teams argue with that?
It made sense in the moment. But reflecting on it later, I realized we were all chasing the wrong kind of leverage. We weren't asking how to understand users more deeply. We were asking how to make our recommendations unquestionable. The goal wasn't better insight. It was armor against pushback.
And here's the thing: it doesn't work. Because trying to gain leverage through data volume (especially longitudinal data that takes months to collect) puts product teams in an impossible position. They need insights now to make decisions on tight timelines, and we're asking them to wait for comprehensive behavioral tracking that may or may not tell them what to actually build.
What Happens to Product Teams
Product teams get caught in the middle. They're handed qual researchers saying "users told us they need X" and quant analysts saying "the data shows Y" and behavioral scientists pointing to patterns that suggest Z. They receive prescriptive recommendations that don't account for technical constraints or business realities. Long lists of pain points with no clear priority. Contradictory insights with no framework for making sense of them.
So they do what anyone would do when overwhelmed with conflicting information: they pick what feels safest, what aligns with what they were already planning to build, or what the loudest voice in the room advocates for. The research gets used selectively, if at all.
This is the gap where research dies. Not because product teams don't care about users, but because research hasn't done the interpretive work required to become strategy.
Empathy as Real Leverage
This is where empathy becomes actual leverage. Not the kind that comes from indisputable data, but the kind that comes from doing the interpretive work that product teams desperately need.
Empathy is the framework that synthesizes contradictory insights into strategy. It asks: What are people trying to accomplish? Where is their agency being supported or undermined? What does this pattern mean in the context of their actual lives?
These aren't research questions. They're strategic questions. And they transform how you interpret everything you learn.
Consider a common scenario: your behavioral data shows users consistently abandoning a feature at a specific point in the flow.
Without agency-centered empathy, the move is obvious: users are confused, so remove the friction. Teams jump to familiar solutions. Add a tooltip explaining what to do, consolidate screens to reduce clicks, move the feature higher in the navigation so it's more visible, insert an onboarding popup that walks users through the steps, or redesign the interface to make the action more prominent. These are all variations on the same assumption: users want to complete this flow, they just need help getting through it.
With empathy, you ask different questions: What goal were they trying to accomplish when they entered this flow? Did we design something that works against their actual intent? Are they abandoning because we're forcing them down a path they don't want, or because we're not giving them what they need to proceed on their own path? Maybe they're leaving because they got what they needed already. Maybe they're leaving because they realized this feature doesn't actually solve their problem. Maybe they never wanted to be in this flow in the first place. We just assumed they did.
Same data. Completely different strategic implications. The first approach optimizes for our feature. The second approach asks whether our feature deserves to exist in its current form at all.
This is how empathy creates leverage: it turns user statements into goals and contexts, not feature requests. It turns behavioral patterns into insights about agency, where it's being supported and where it's being undermined. It turns contradictions between what people say and what they do into strategic choices about whose needs you're serving, when, and why.
Most importantly, it does this work quickly. You don't need months of longitudinal data to ask whether your design respects user agency. You need the interpretive discipline to make that the question.
From Insight to Product Clarity
Product clarity isn't about having more data. It's about knowing what to build, what not to build, and having conviction in the hard trade-offs between them.
Empathy gets you there, and not just empathy for users. Empathy as a strategic engine extends to stakeholders too. It means asking the right questions upfront: What are the business constraints? What are the technical limitations? What trade-offs are we willing to make? What does success look like for the business AND for users?
When you understand these constraints from the start, your research doesn't produce recommendations that get blocked by "that takes up too much ad space" or "we can't build that with our current architecture." Instead, you're doing the interpretive work to find the overlap. The space where user needs and business realities align, where solving for agency also solves for outcomes.
This is the leverage researchers actually need: turning research into strategy that product teams can act on. Strategy that accounts for trade-offs, connects user needs to business outcomes, and can withstand scrutiny from both sides.
That kind of leverage doesn't come from watching users in their homes for months. It comes from the interpretive discipline to ask: What are people trying to accomplish? Where does their agency align with what we can actually build? What does this mean strategically?
The Practice
Empathy as a strategic engine isn't about running more user interviews or adding a "user perspective" slide to your deck. It's about building agency-consciousness into every interpretive move you make.
That means:
Understanding business constraints and technical realities upfront, not after recommendations are written
Asking what users are trying to accomplish, not just what they say they want
Recognizing when behavioral data reveals an unmet need versus when it reveals your product working against someone's goals
Questioning whose convenience your "frictionless" experience really serves
Distinguishing between solving problems for users and extracting data from users
Finding the overlap where user agency and business outcomes reinforce each other
I've spent my career bridging the gap between technology's influential power and users' critical agency. In academic spaces, that meant examining how we theorize algorithmic interaction. In industry practice, it means ensuring research translates into strategy that preserves and honors that agency while being implementable within real constraints.
When you approach research and strategy from that foundation, the clarity follows. Not because empathy makes decisions easier, but because it ensures you're making decisions about the right things. Decisions that can withstand scrutiny from user needs, business realities, and technical feasibility.
That's leverage. That's strategy. That's what empathy does.
Empath Strategies works with organizations to transform research into product clarity by centering user agency in strategic decision-making. If you're sitting on research that hasn't translated into action, or building products that aren't landing the way you expected, let's talk.