Stop Removing Friction. It’s Your Best User Research Tool

What 10 years of trust-based platforms and one zero-to-one product unlocked about intent qualification along with the mechanism most marketing and growth teams are missing.

I’ve spent over a decade working inside trust-based technology platforms. Consumer products where a stranger getting into your car, opening their home to you, or meeting you alone in a foreign city were the entire value proposition. Platforms which operated across 20+ markets or even across several continents, with millions of users. In every case, the hardest GTM problem across markets wasn’t usually acquisition. It was an intent qualification.

And every time, the industry kept solving it the same way: acquire broadly, qualify later.

Of course, that approach made absolute sense when digital trust was intact. But unfortunately, it is not the same anymore. The Thales 2025 Digital Trust Index, which ran a survey among over 14,000 consumers across 14 countries, found that not one sector earned above 50% trust approval – and 88% of consumers now say it’s harder to tell what’s real online than it was a year ago. For different P2P platforms, safety apps, fintech, healthcare – any product where the core value proposition involves a stranger – this isn’t a background trend but a clear conversion problem.

Low-intent users are cheaper than ever to acquire. But harder than ever to distinguish from high-intent ones.

But there’s something very counterintuitive: the same Thales research found that 64% of consumers say their confidence in a brand would significantly increase if it adopted advanced verification. Sounds not obvious, right? So, basically, consumers aren’t rejecting friction. They’re rejecting products that don’t earn trust.

At one platform I worked at that reached millions of users across over 20 markets, I spent years watching how trust mechanics work at scale, and it was fascinating. There was one strong pattern that kept appearing from one market to another: the products that grew most sustainably weren’t the ones that removed every barrier. They were the ones that made the right barrier feel necessary. When I started working with another trust product years later, I wanted to test whether that pattern held from zero, in a product where trust was the entire value proposition from day one. Building a trust-first consumer app for solo travelers was that test essentially – and what I found confirmed what a decade at scale had suggested: the industry has been solving the intent qualification problem backwards.

The orthodoxy

Every growth playbook suggests the same approach to follow: remove friction at every step, then shorten onboarding and finally get users to the “aha moment” fast, because every additional step loses people.

For most consumer products, this is absolutely correct and the right thing to do.

But applying the same logic to highly trust-dependent products leads to a failure mode: you fill your funnel with low-intent users, burn CAC acquiring them, then spend months trying to re-qualify them through engagement mechanics – chasing a signal you could have captured at the door.

What the data showed

Building a trust-first app for solo travelers, I made a deliberate decision that actually contradicted common growth advice: mandatory face and government ID verification before any user could match, chat, or access core features. Not optional or paywalled but mandatory for every user landed in the app.

The expected outcome was a significant drop-off at the very beginning of the funnel but the data said otherwise.

• 65% install-to-signup CVR – definitely above category average with zero brand recognition and minimal paid budget across the first six months
• 27% voluntary face verification – more than one in four users willingly passed a hard identity gate – that’s great result
• CPL outperforming landing page by 40% – across 576K total reach

But the most important data point was the onboarding survey – not the dashboard itself. When the user registered their profile in the app, they were asked to complete a quick survey. Users who completed verification said some version of the same thing: I want to travel with someone or I don’t want to travel alone. On the other hand, users who dropped off at verification at some point, said something very different: I’m just exploring.

So, there’s the same funnel, the same friction point but absolutely different intent. In the end, what it means is that no targeting algorithm surfaced as well as no survey question forced it. The verification wall revealed it before I spent a single dollar trying to activate or retain them. And that was the biggest win of the first growth stage.

The mechanism: Friction Inversion

This is what I call friction inversion and it directly challenges how trust-dependent products should think about funnel strategy. The standard model usually looks like there’s a low barrier to enter, and users that quality go through the downstream behaviour. When the friction inversion model has a low barrier to discover but a high barrier to belong. And using that barrier as your earliest intent signal is something that changes the entire perception of growth.

In markets where trust is the core value proposition, a deliberately placed friction point at activation works as I call a passive intent qualifier. Essentially, it does all the segmentation work at the earliest stage possible, it’s definitely more cheaply, and more honestly than any other active mechanism. In this case, users are selected based on their genuine motivation and not on how well the re-engagement sequence is built.

As a result, the users who push through the wall tell you who they are and why they are here.

When to apply it

Three conditions make Friction Inversion the right call:

• Trust is the core value proposition – not a supporting feature. If your product involves strangers interacting in a context of personal or financial risk, verification friction isn’t a barrier to value. It is the value.
• Your user is making a high-stakes decision – solo travel, lending, healthcare, shared housing. Users who are genuinely committed expect to prove themselves. They’re often more suspicious of products that don’t ask.
• Your early intent signal is noisy – if you can’t tell within the first week whether a user will convert, a friction gate will clean that signal faster than any behavioural model.

If all three are true: don’t optimize the friction away. Deploy it deliberately.

Growth orthodoxy says get users in fast, qualify them later. For trust-dependent products, that sequence is the problem.

The verification wall I expected to be a conversion liability turned out to be the clearest product-market fit signal I had. The users who pushed through knew exactly why they were there. The users who didn’t told me something equally valuable: they weren’t ready.

Stop removing friction from the places where it’s doing the most important work. In trust-first markets, it’s the most honest research tool you have.