Stand-in skills
Product Discovery
Product Discovery lets an AI Stand-in recognize a relevant research opportunity, ask the visitor for explicit consent, and conduct an adaptive interview without replacing the visitor’s original request. Grounded findings are saved with transcript evidence and a built-in Product Discovery label.
- Availability
- The conversation skill is available on all plans; AI digest reports and longer searchable history require Pro or Business
- Configured in
- Dashboard → AI Stand-ins → select a Stand-in → Skills → Product Discovery
- Category
- Stand-in skills
- Reference status
- Current
Configure the research contract
| Setting | Purpose |
|---|---|
| Who should the Stand-in interview? | Candidate criteria describing the workflows, pains, evaluations, or buying processes that make discovery relevant. |
| Research goal | The evidence the organization wants to learn from willing visitors. |
| Research questions | Up to three current questions, each up to 240 characters, used to associate captured evidence with a specific learning need. |
| Guardrails | Situations, question styles, or topics the Stand-in must avoid. |
| Interview depth | Light uses a few quick facts, Adaptive continues while engagement remains useful, and Deep permits more follow-ups with willing participants. |
| Notify on first match | Alerts the Stand-in owner when the first grounded Product Discovery result is captured in that conversation. |
Consent and answer-first behavior
A matching candidate is not automatically an interview. The Stand-in first provides substantive help for the visitor’s actual question. If a distinct discovery opportunity remains, its first discovery question must be a short, explicit permission request.
No workflow, team, incident, impact, or fit question is allowed before that consent. A decline, frustration, support need, pricing or demo request, handoff request, rushed tone, or clear end stops or prevents discovery according to the saved guardrails.
Adaptive interview behavior
- Questions adapt to what the visitor has already said instead of reading a rigid survey verbatim.
- The configured research questions are priorities when relevant, not a requirement to ask all three in every chat.
- The depth choice sets an effective question budget: Light defaults to 3, Adaptive to 5, and Deep to 8, within the supported range of 1 through 8.
- The Stand-in returns to helping and stops when the visitor disengages or a guardrail applies.
- The feature avoids hypothetical willingness-to-pay and leading solution-validation questions as evidence of real behavior.
Labels, findings, and evidence
When the Stand-in captures a grounded discovery result, Stand applies the built-in Product Discovery label and retains a finding tied to the supporting conversation evidence and, when applicable, the configured research question.
- The built-in label appears in live monitoring, History filters, and relevant digest analysis.
- It does not consume the Pro or Business active custom-signal quota.
- AI digest reporting can synthesize findings across conversations on Pro and Business and should report insufficient evidence when the period does not support a conclusion.
- The transcript remains the evidence source; a synthesized finding is not a substitute for the visitor’s actual words.
Validation and boundaries
- Candidate criteria, research goal, and guardrails are each limited to 2,000 characters.
- At most three non-empty research questions can be saved, and each is limited to 240 characters.
- Notifications occur on the first grounded Product Discovery match rather than every later message in the interview.
- The feature does not guarantee representative research, statistical significance, or factual correctness of visitor claims.
- Retention and plan rules determine how long the underlying conversations remain searchable.
Example
The screen below shows the feature in its normal Stand context. Labels and surrounding controls may vary with account state and plan.
