De-risk a product before the first line of code
Find who to sell to before writing the first line of code.
The context
MarQdesk is an institutional-intelligence platform on binary macro events: central bank decisions, macro releases, geopolitics. The kind of product that demands months of development and real conviction before launching. Before committing that budget, only one question really mattered: who actually hurts today, and how to sell to them. Everything else, the architecture, the models, the screens, was worth nothing until that answer was solid.
A positioning entirely repivoted before the first line of code. The core pain identified, the target profile narrowed to three conditions, an early-adopter segment uncovered, a defensible differentiating angle, and a ready-to-use sales kit: channels, objections, words to use. Where most products discover their real market after six months of build and a first commercial failure, this one found it before writing its first file.
The problem
Building on assumptions is the most expensive way to be wrong. The starting hypothesis was clear and plausible: the client is the decision-maker who must act on a macro event without a research desk behind them. Plausible doesn't mean true. A credible intuition that steers six months of build is still a bet, not a strategy. And the usual way to check it, interviewing five hand-picked people, mostly gives the answers you want to hear. It needed a far broader, unfiltered read of the market.
How it works
A qualitative-listening setup at scale, to go find practitioners' words where they're candid, not where they're solicited. Rather than a handful of interviews, several hundred real conversations captured and structured, then analyzed systematically to surface recurrences, not anecdotes. The goal wasn't to collect opinions, but to bring up patterns clear enough to decide on a product and a message.
Practitioners in finance, treasury, risk and procurement openly discuss their decisions on Reddit and specialized communities, often more frankly than in a sales interview. That's where I went to listen. I captured and structured these hundreds of conversations, then analyzed them to isolate the real pain, the real profile, the channels that convert and the exact vocabulary used by people in the field. The work isn't to have an opinion, but to let the field speak and make it readable.
The analysis overturned the starting hypothesis and produced a complete action plan.
The findings
- The real pain isn't accuracy, it's defensibility. Practitioners aren't primarily looking to be right, they're looking to justify their decision when the market proves them wrong. That single insight pivoted the product, from a forecasting tool to a tool that makes the decision defensible.
- The right profile isn't the deskless decision-maker in general, but the intersection of three conditions: direct P&L exposure, timing constrained by an event, and an obligation to be accountable. This filter eliminates most of the prospects that seemed relevant.
- An unexpected early adopter emerged: the rigorous, isolated practitioner, looking less for one more number than for a credible external source to cite in support of their judgment.
- A structural differentiator imposed itself, defensible by design and hard to copy without rebuilding everything behind it.
- As a bonus, a map of the channels that actually convert, the list of recurring objections with their answers, and the precise practitioner vocabulary to reuse as-is in the messaging.
What it proves
I don't build a product on a hunch. I go find the qualitative signal where it lives, I structure it, and I extract product decisions and sales angles that hold. That's exactly what I can do to de-risk a product or a positioning before spending the build budget: replace the bet with a read of the field.