User Feedback vs. Behavior Data: Why They Rarely Conflict

When teams run interviews or surveys, one question tends to come up more than any other:

“What would you change about the site?”

The problem is that the question rarely gets to the root of what’s preventing conversions. 

Most answers focus on surface-level preferences, wishlist features, or general usability feedback. None of which reliably signals what causes users to hesitate or abandon their purchase.

To uncover true conversion blockers, your research process needs to dig deeper. That means focusing less on opinions and more on identifying the exact points where users lose clarity, confidence, or momentum in the buying journey.

Over the past few years, we’ve developed a structured way to identify these friction points. A repeatable framework that helps reveal the hidden barriers standing between interest and action.

In this email, we’ll cover:

• The research techniques that surface conversion-blocking friction
  

• How to structure interviews to uncover both psychological and practical hesitation
  

• A way to reconcile user feedback with behavioral data, even when they seem to conflict
  

• How to ask questions that get to the truth of the buying decision
  

• And why asking “why” repeatedly often leads to the insight that moves the needle

Use frameworks built to uncover friction, not preferences

Effective research starts with structure.

The Revenue Friction Roadmap, originally developed as part of our Usability Scorecard methodology, provides a consistent way to isolate the moments in a buyer’s journey where clarity drops, hesitation creeps in, or momentum stalls.

Rather than collecting general feedback or feature suggestions, we focus on evaluating user experience at a task level across specific page types like the homepage, category, PDP, cart, and checkout.

The Usability Scorecard uses a 1–4 effort scale to assess how easy or hard each step in the journey feels to a user. Any task that isn’t marked “very easy” (a score of 1) becomes a trigger to investigate further. That’s where the real insights come from.

This structured approach helps us:

• Identify where users lose confidence or clarity within the flow
  

• Pinpoint friction created by layout, content, or hierarchy on high-intent pages like PDPs and carts
  

• Collect behavior-prioritized feedback, rather than opinions or vague likes/dislikes
  

The result is a research output that aligns directly with experimentation. It generates a hypothesis backlog grounded in actual user difficulty.

Structure research to pinpoint both hesitation and friction

Good research doesn’t just collect feedback. It organizes it around the parts of the journey that matter most for conversion.

That’s why every research session we run is structured around key page types: homepage, category, PDP, cart, and checkout. We ask users to rate how easy or hard it was to complete specific actions on each page using a 1 to 4 scale.

• A score of 1 means “very easy.”
  

• Anything else prompts a simple follow-up: “Why?”
  

• From there, we drill down to understand what caused friction.

This simple scoring model uncovers two core things:

• Practical blockers, like unclear sizing, missing shipping info, or complex layouts
  

• Psychological hesitation, like fear of choosing the wrong product or uncertainty about value
  

When users hesitate, it’s rarely because something is outright broken. It’s usually because something feels unclear or risky. This framework reveals those moments with consistency.

Understand the relationship between feedback and behavior

It’s common to worry that user feedback might contradict what behavioral data shows. But in practice, when you look deeper, that tension usually resolves.

• Behavioral data shows what users do
  

• Feedback reveals why they do it
  

At face value, these can seem misaligned. 

A user might bounce from a PDP in ten seconds, while telling you in an interview that the page “looked fine.” But when you probe further, you often find the disconnect: the product felt unclear, the specs didn’t match their needs, or something felt missing.

Users don’t always verbalize their actual objections, but they reveal them through inconsistency. Your job is to interpret both data sets (not as opposing inputs) but as two layers of the same story.

The classic product insight still holds:

“If I had asked people what they wanted, they would’ve said a faster horse.”

The goal is to listen between the lines and identify what problem they’re trying to solve.

Design Interviews That Surface Friction And Feedback

The most valuable answers rarely come from direct prompts. They come from open space.

When you want to understand why someone didn’t convert, your questions should be:

• Open-ended
  

• Vague enough to let users frame their own experience
  

• Free of implied suggestions or language that biases the response

Then, you stop talking. Let them fill the silence. Don’t finish their sentences. Don’t reword their answer. Just listen.

When a user gives a surface-level answer, go deeper. Use follow-up prompts like:

• “Why did you give it the score you did?”
  

• “Why was that what you expected?”
  

• “Why did you find that difficult?”
  

• “Why did that information matter?”
  

We often use the Toyota 7 Whys method. Asking “why” repeatedly uncovers the real motivation or hesitation underneath the first response. 

This approach works not only for user interviews but also for internal decisions and strategy development.

Closing Thoughts

Every insight is an invitation to go deeper. When users hesitate, the answers are often just beneath the surface. Hidden in the pauses, the phrasing, the moments they stumble.

Research that reveals friction is rarely flashy. It’s methodical, it’s structured, and it builds the foundation for decisions that move the needle.

Keep your process focused, your questions open, and your ears sharp.

Looking forward,

Brian

P.S. Ready to grow revenue without having to grow traffic? Let’s talk.