You can build it in a weekend. Can you sell it?

Win-loss analysis is a set of structured interviews with buyers who recently chose you, chose a competitor, or chose nobody at all. It surfaces why a deal actually moved, which is rarely the reason logged in the CRM. For SaaS teams the most common finding is that the deal was lost to inertia: the buyer kept the spreadsheet or the manual workaround, because nobody had built them an internal case for changing.

Most early churn is an activation problem rather than a product problem. The user cancels because they never reached the moment the product proved its value, and the cancellation reason they type into the box is almost never the real one. Diagnosing it means interviewing the people who left, stalled or never activated: what they expected, what the first session actually gave them, and what they went back to. A funnel chart shows where they dropped. Only they can tell you why.

Willingness-to-pay research puts two survey instruments in front of in-market buyers. Van Westendorp maps the range between too cheap to trust and too expensive to consider. Gabor-Granger builds a demand curve across specific price points, so revenue can be modeled instead of guessed. Both run alongside the question SaaS teams skip most often: which value metric buyers accept being charged on, whether that is seats, usage, or an outcome.

Freemium, free trial and reverse trial each filter a different buyer, and the right one depends on how fast your product proves value and what a non-paying user costs you to serve. Research settles it by testing intent at your real price under each model, with your real buyers, instead of importing a conversion benchmark from a company whose cost to serve looks nothing like yours.

An Ideal Customer Profile holds up when it is built from buyers who converted and buyers who didn't, not from a persona workshop. That means interviewing across both groups, isolating what the converters had in common (the trigger, who controlled the budget, the manual workaround they were already paying for in time), then testing whether those traits predict intent in a larger sample. The output is a screening rule sales and marketing can both use.

A repeatable go-to-market motion is one where the same buyer, the same trigger and the same pitch win again and again, without the founder in the room. Research finds it by interviewing three groups: customers who bought and stayed, deals you lost or that stalled, and new buyers who match your ICP but have never heard of you. Comparing them shows who owns the problem, which event makes it urgent, which first offer is easiest to buy, and which channel reaches them. That is what the Go-to-Market Fit study delivers.

Happy customers with silent outbound usually means the product works but the targeting, the timing or the offer does not. The list may be the wrong role, the message may land before the problem hurts, or the offer may be too broad to buy in one step. Customer data alone can't tell those apart, because it only shows who said yes. Interviewing lost deals, stalled deals and cold buyers next to your best customers is what separates a list problem from a message problem from a market problem.

The buyer, problem and trigger to go after first are the ones your best customers share and your lost deals lack. Interviews isolate them: who started the search, what happened the week before, who signed, and what they used before you. When the same pattern shows up across customers and is missing in the deals that died, that is your first segment. When it doesn't, the research says so, before you scale outbound on a guess.

Pre-launch is the ideal moment for customer validation research. Validation is cheapest before the build, when changing your mind costs a conversation instead of a quarter of engineering. Teams that arrive after launch usually pay twice: once for the wrong build, and once for the research that would have prevented it.

Recruiting hard-to-reach B2B audiences is standard work for us: clinicians, IT directors, procurement leads, compliance officers, specialist trades. Tell us who the buyer is and what has to be true for someone to qualify, and we'll tell you honestly, before you commit to anything, whether we can reach them and how.

Yes. GCR researches buyers in the US and across Latin America, and expansion between them in both directions. Our clients are based in the US and UK, and we've delivered research for Netflix, Spotify, Amazon, Betfair, Abbott and Merck. We recruit and interview US buyers in English, digitally, and run fieldwork in Spanish across Latin America from our base in Medellín, Colombia.

Demand in a new country is validated by interviewing buyers and channel partners there before you sign the local entity, apply for a license or hire a country manager. The study tests whether the local buyer, buying committee, incumbent alternative and price anchors match your home market, and what has to change if they don't. The output is a go, adapt or wait verdict per country. We run it between the US and Latin America in both directions, in English and Spanish.

No. GCR does not use synthetic respondents, AI-generated panels or simulated buyers. AI speeds up our analysis: transcription, coding, finding patterns across hundreds of open ends. It never replaces a person. Every data point in your study comes from a real, screened human who agreed to be interviewed. A model trained on the internet can tell you what people have said before. It cannot tell you what your buyers would pay.

Three things, on every package: findings tied to the decision you brought us, the raw material behind them (transcripts, data tables, recordings), and a live working session where we walk your team through what to do next. The deliverable is the decision, not the deck.

Turnaround depends on the package and on how fast your specific audience can be recruited, because a niche B2B buyer takes longer to reach than a general consumer sample. You get an exact date before you commit, not after. We field in parallel where possible, and we don't take a project we can't deliver on the date we promised.

Then we tell you plainly, with the evidence behind it. A clear no is the most valuable outcome we can sell you: it costs one study instead of a year of engineering, and the same interviews that produced it usually point at the adjacent problem that is worth building for instead.