Turning user behavior into product decisions.
Psychology background. UX researcher focused on behavioral insights and decision-making. I use AI as a real part of how I work, from research synthesis to design.
A quantitative study on how price transparency at the moment of decision affects booking conversion. And why what the test reveals matters more than the percentage point itself.
On the platform we studied, virtually every user who searched for a flight reached the View Flight screen. 99.9% made it that far. The problem wasn't discovery. It was the moment they had to commit.
The two-hour window turned out to be the whole game. After that, the numbers barely moved. Time didn't help. It mostly just lost them.
The platform used a common industry pattern: show a base fare upfront, then reveal taxes, baggage fees, and surcharges step by step through checkout, sometimes only at the very end. It's called price dripping.
Research in behavioral economics (Blake, Moshary, Sweeney & Tadelis, 2018) shows that when users can't see the full cost early, they can't make a confident decision. So they delay, or they leave. The information is there. The clarity isn't.
The fix was simple. Show the full price, taxes included, right on the View Flight screen. No new screens, no flow changes. Just the number people actually need to decide.
Most A/B tests are built to confirm a direction. This one was built to locate a problem.
The interface was the problem. Price dripping created enough uncertainty to delay commitment. The fix is within the product team's control and the revenue impact is direct.
The price itself is the problem. Users already know how much flights really cost, and it's too high. No UX fix helps here. The company needs a different lever entirely, and now they know it.
Either way, the airline doesn't just get a metric. They get a diagnosis.
Primary metric: behavioral. Did users complete a booking within 120 minutes of viewing a flight? Secondary: a short questionnaire measuring perceived price transparency, to understand why behavior changed, not just that it did.
The hypothesis was two-tailed by design. We weren't trying to prove something. We were trying to find something.
Here's what it looks like in practice: the full price breakdown, right on the View Flight screen, before the user commits to anything.