The ecommerce optimization industry is built on a premise: your site has problems, and testing variations will fix them. Run experiments, find winners, implement changes, repeat.
It’s a compelling model. It feels scientific. It produces measurable results. And it often misses the point entirely.
The Optimization Trap
Optimization starts with an assumption: this thing we’re testing is the thing that matters. The headline needs to be better. The button needs to be more prominent. The form needs fewer fields.
But what if the headline isn’t the problem? What if visitors understand your offer perfectly well and just don’t want it? What if the button is fine but nobody trusts your site enough to click it?
Optimization without understanding is like adjusting the rearview mirror while driving toward a cliff.
Testing Isn’t Learning
There’s a difference between learning and testing. Testing tells you which variation performed better. Learning tells you why.
You can test a hundred headlines and find a winner without understanding anything about your customers. That winner might lift conversion by 5%. But if you understood why your customers hesitate, you might discover that the real issue isn’t the headline at all—and addressing it could lift conversion by 50%.
The Questions That Matter
Before testing anything, ask:
What do customers believe when they arrive? About their problem, about potential solutions, about your brand. Understanding their beliefs reveals what you need to change.
Where does confidence break down? At what point in the journey do people hesitate or leave? What question haven’t you answered? What fear haven’t you addressed?
What do customers actually need to know? Not what you want to tell them—what they need to believe to move forward.
Research Over Testing
The answers to these questions don’t come from A/B tests. They come from research:
Customer interviews. Actual conversations with people who bought and people who didn’t. Why did they choose you? Why did they hesitate?
Session recordings. Watching how people actually navigate your site reveals friction points that metrics can’t.
Support analysis. What questions do people ask? What concerns come up repeatedly? These are clues to missing trust or unclear messaging.
Post-purchase surveys. What almost stopped them from buying? What would have made the decision easier?
Understanding First, Then Optimizing
Once you understand the real barriers, optimization becomes meaningful. You’re no longer guessing which headline might work—you’re addressing the specific concern that prevents people from moving forward.
This approach is slower at the start. It requires genuine curiosity about your customers, not just data about their clicks. But it produces fundamentally different results.
The Deeper Issue
Most ecommerce brands don’t have an optimization problem. They have an understanding problem. They don’t know—really know—who their customers are, what they believe, and what it takes to build genuine confidence.
Optimization is comfortable because it lets you stay at arm’s length from these questions. Run tests, read results, make changes. No uncomfortable conversations required.
But the brands that break through do the uncomfortable work. They understand first. Then, and only then, they optimize.