When users act differently than expected
05. Jun 2026
Everything actually looked good. The user flows seemed logical, the most important functions were visibly positioned and the entire process made sense from a product perspective. Nevertheless, questions remained unanswered. Why were certain functions hardly used? Why did users drop out at certain points? Or how would they deal with a new feature that wasn't even live yet?
Reading time: 3 minutes
What we see again and again in user studies - and why the real insights lie between the data
Suddenly, it became clear just how differently people perceive digital products. Navigation elements—which were actually intended to provide guidance—barely mattered to them. Instead of the intended user journey, entirely different paths through the application emerged. These revealed where uncertainties arose and expectations were not met.
We encounter situations like this in user studies more often than many would expect. Not because users operate applications “incorrectly,” but because they use digital products based on their own expectations and experiences. That’s exactly where the most exciting insights emerge.
Why the look before the click is crucial
Many teams today operate in a data-driven way. Analytics, KPIs, and A/B tests provide valuable answers to important questions:
- Where do users drop off?
- Which features are being used?
- Which version performs better?
What we observe in projects, however, is that the truly interesting questions begin exactly where traditional data ends.
A dashboard may show that users drop off at a certain point, but it rarely reveals why they do so.
The decisive moment often occurs even before the actual click: a quick glance at an element, a hesitation, a moment of uncertainty, or a search for orientation. It is precisely these seemingly minor situations that determine whether a process feels intuitive—or not.
People see things - and still don't use them
There’s a situation we encounter time and again in tests: Users do notice elements, but they evaluate them differently than originally assumed.
Buttons, navigation elements, or content are certainly noticed, but they do not always lead to the expected action.
We regularly observe this seemingly contradictory behavior in user studies.
This is because perception does not automatically lead to interaction.
An element can be visible without users considering it relevant. Navigation elements are noticed but not always used as a guide. And this is precisely where we’re no longer talking about visibility or placement, but rather about expectations and mental models.
Eye tracking does not simply show eye movements - but thought processes
That’s why we use eye tracking. It helps reveal where perception and behavior diverge. This raises questions that were previously missing:
- Why was something noticed but ignored?
- Why does uncertainty arise at this exact point?
- Why doesn’t a user journey work the way it was originally intended?
The actual insights don’t come from eye-tracking data alone, but from combining observed behavior with qualitative follow-up questions.
After all, users don’t always say everything. At the same time, they find it difficult to explain their own behavior.
Conclusion: Good user experience rarely comes from assumptions
This is exactly where user research comes in. It helps reveal underlying causes, understand connections, and view products from the perspective of the people who actually use them.
Eye tracking can provide additional insights and highlight areas where users encounter difficulties. This method is particularly valuable when combined with qualitative methods, as it allows for a better understanding of why people act in a certain way.
