Small samples deserve modest conclusions

A new proposal format wins three projects in a row. It is tempting to declare it the reason. Yet the buyers may have been stronger fits, the prices lower or the salesperson more experienced. With a small sample, coincidence can look like a method.

Report the actual counts. "Three wins from five proposals" is more informative than a percentage presented without a denominator. Include the types of opportunities and the observation period so readers can judge context.

Do not dismiss small samples entirely. Detailed case observations can reveal friction, misunderstandings and plausible mechanisms. They are useful for improving a process and deciding what to investigate next. They are weaker evidence for a general claim about conversion lift.

Look for disconfirming cases. When did the new approach fail? What was different? A method that works only with existing clients may still be valuable, but it should not be marketed as an answer to cold acquisition.

Keep the test running long enough to observe downstream effects where practical. Faster agreement may come with more scope disputes. More meetings may come with lower fit. The first favourable metric is rarely the whole story.

Use language that matches the evidence: "promising in this setting", "worth a larger test" or "did not resolve the issue". Modest conclusions are commercially useful because they preserve the distinction between an observation and a dependable operating rule.