Founders
How to find customer interview participants for AI analytics copilots
AI analytics copilots: Recruit interviews from the proposed buying situation, not only the founder's convenient network.
Recruit interviews from the proposed buying situation, not only the founder's convenient network. A relevant participant has recent experience of the workflow and can describe it without guessing. Keep users, managers, and procurement participants distinguishable in the notes.
Start with the decision
Write a short screening question about a recent task. Use several recruiting channels and record how each person was reached. Ask permission before recording or quoting, and avoid treating one community's behavior as the whole market.
The illustrative scenario
This is an educational workbook. The company or fund and all numerical inputs below are fictional. They are not ADIN results, customer claims, market benchmarks, or a forecast.
The fictional copilot answers business questions over an approved sales dataset. Analysts validate the calculation, while managers use the result in planning. Definitions such as active customer or booked revenue can differ across teams.
A persuasive explanation can conceal the wrong denominator or date range. The reader needs the underlying calculation and data definition, not only a natural-language answer.
Turn the scenario into an evidence decision
Consider a review of AI analytics copilots in which a confident explanation arrives before the supporting records. Start with the first question in the table. Write down what an answer would change: the next interview, the experiment's scope, a request for specialist review, or a decision to wait. A question without a consequence can produce a longer document while adding little understanding.
Next, inspect the record named in the table and record its date, owner, permission boundary, and limitations. Keep approved metric definitions, query results, data freshness records, and examples where an analyst corrected the answer. Include ambiguous questions that require clarification. If the record contradicts the explanation, preserve both accounts and ask which definition, period, or workflow differs. Do not silently select the version that makes the opportunity look strongest.
Finish with a conditional statement: if the specified evidence supports the claim under these conditions, take the named next step; otherwise investigate the unresolved question. Interview counts are less useful than coverage of the decisions and constraints that matter. If all participants know the founder or use the same stack, recruit a contrasting sample before generalizing. This worked exercise is about the decision process. It does not assert that a fictional company has met a real diligence standard or that a template can authorize an investment.
| Item | Illustration |
|---|---|
| Decision question | What recent task qualifies a participant? |
| Case-specific constraint | A persuasive explanation can conceal the wrong denominator or date range. The reader needs the underlying calculation and data definition, not only a natural-language answer. |
| Record to inspect | Keep approved metric definitions, query results, data freshness records, and examples where an analyst corrected the answer. Include ambiguous questions that require clarification. |
| Comparison to preserve | Compare time to a verified, decision-ready answer with the current analyst workflow. Treat a quick answer with an unresolved definition as unfinished work. |
| Unresolved case question | Which metric definition applies? |
Use this worksheet
Answer the questions with a source, date, owner, and next action. Mark an unknown as unknown. Use public or permissioned information and involve a qualified specialist when a question requires expertise beyond the team’s competence.
- What recent task qualifies a participant?
- Which role is missing?
- How was the person recruited?
- What incentive could bias the answer?
- Which segment is absent from the sample?
Questions specific to this scenario
- Which metric definition applies?
- Can the analyst reproduce the result?
- When should the tool ask a clarification?
Keep approved metric definitions, query results, data freshness records, and examples where an analyst corrected the answer. Include ambiguous questions that require clarification.
A concrete next test
Give an analyst an ambiguous business question and the proposed answer without hiding the underlying calculation. Ask which definition and date range they would verify first. Record whether clarification changes the result before measuring the time required to use it.
Interpret the result
Interview counts are less useful than coverage of the decisions and constraints that matter. If all participants know the founder or use the same stack, recruit a contrasting sample before generalizing.
Compare time to a verified, decision-ready answer with the current analyst workflow. Treat a quick answer with an unresolved definition as unfinished work.
Sources and method
These primary resources provide background for the concepts. The fictional scenario, calculations, and worksheet are ADIN educational examples; the sources do not report or validate those invented results. Reviewed October 11, 2026.