Most go-to-market data has three predictable blind spots: it observes the wrong time, studies the wrong sample, or describes customers in the wrong language. Each one produces a confident, internally consistent picture with the causal information removed — which is why teams can run diligent win/loss reviews, watch health scores weekly, and hold quarterly messaging workshops while the same problems recur.
None of these are failures of effort. They are failures of instrument.
Usage data precedes the cancellation, not the decision — and the decision is the only thing you could have influenced. By the time an account looks at risk, you are confirming a verdict rather than forecasting one.
Win/loss interviews buyers who crossed the decision threshold. Everyone who never crossed it is absent. That is selection bias in the ordinary sense, and it removes the largest outcome category from the study of outcomes.
Positioning frameworks tell you what to decide, not what customers say — and the questions about buyers get answered in a workshop. The output is accurate and unrecognisable: buyers cannot see themselves in language they never use.
Each blind spot substitutes something observable for something causal. Usage stands in for intent. Deciders stand in for the market. Internal consensus stands in for customer vocabulary. In every case the substitute is easier to collect, arrives in a dashboard, and quietly answers a different question than the one being asked.
The correction is the same in all three: talk to people, at the right moment, including the ones who did not buy, and record what they actually said. That is unglamorous and it is why the gaps persist.
Each article ends at an instrument. The churn guide reconstructs when a decision was really made. The no-decision guide covers the population that never appears in win/loss. The core jobs guide is built to be run across all four buyer roles and to capture exact phrasing.
All six guides — including switching, adoption and expansion — are published in full at customercentricllc.com/guides, free to use and cite.
Reaching the right people — including non-buyers and churned accounts — and coding what they say into something you can act on is where most self-run studies stall.
AI-moderated interviews when you need reach across a larger sample. 1:1 expert interviews when you need the deepest read on a small number of people. Fully managed from recruitment through findings, or hybrid — working alongside your team, running interviews jointly and presenting together.
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