We ran a simple study on how people make decisions on customer-related topics. We got more than 40 responses.
Most people decide first based on the roadmap, on OKRs, and on whatever leadership has already defined. When information about the customer is missing, the answer is almost never a research study. It’s booking a 20-minute meeting, sitting next to a colleague, or asking whoever is closest to support. Structured qualitative research barely exists in the day-to-day.
That changes the question we’d been asking. It’s not “how do we convince someone to switch from the research tool they already use?”. It’s “how do we compete with improvisation and the missing habit of talking to the customer?”.
The Pix that wasn’t broken
One of the richest accounts came from a product owner who handles Pix at a payments institution. Her team surfaced the ten biggest customer complaints, and one kept coming up: “I can’t make a Pix transfer, I can’t even register a key”.
The first instinct of any executive, she said, is to assume the app is broken. But when she cross-referenced the tickets with a tool that centralizes support channels, she found something else. Roughly 80% of those customers had a fraud record somewhere, at any bank, not necessarily their own. A Central Bank rule from February this year restricts Pix for anyone with a fraud record on file, and the restriction applies across every institution.
The data solved the mystery. But the PO herself admits the data isn’t enough. “In general, it’s really hard to understand what the customer is thinking,” she said. Once the technical problem is explained, the qualitative part is still missing: how the customer reacts to finding this out, what they expect the bank to do, whether the current communication is even clear. The quantitative data answered what. Nobody had answered why.
“They think we’re a diner”
Not every answer came as a full story. One PM who’d just joined her company said she asks more senior colleagues when she lacks context about the customer. We asked whether there was any room to understand the customer before deciding, given the delivery pressure she described.
The answer was one sentence: “there isn’t, because they think we’re a diner”.
No further explanation needed. Order taken, delivered, next. It’s the culture most product companies live in, even the ones that say they put the customer at the center.
ChatGPT doesn’t replace the customer
A solo founder described another common shortcut. With no neutral customer to consult, she talks to ChatGPT and Claude, builds a matrix weighing value against development time, and moves forward with whatever comes out of that conversation. “It’s what I have and can keep up with, so that’s what I go with,” she said.
It’s not an isolated case. A larger batch of interviews showed the same pattern recurring often enough to become its own research question: what are the limits of using a generic AI to simulate what a customer would think?
Our suspicion, which we still need to validate, is that an AI with no context on your product and your customer base gives back what sounds plausible, not what the customer would actually say. It looks like research. It isn’t.
Where that leaves us
The conclusion ReveLumi itself surfaced in its own full report is that ReveLumi doesn’t compete with other research tools. It competes with the absence of research and with improvisation.
That means the right pitch isn’t “you need one more research tool”. It’s “you know talking to customers matters, but you can’t do it in a structured way”.
If that’s your day to day, it’s worth seeing what changes when the conversation with the customer happens continuously, in a structured way, without someone having to stop everything to run a formal study.