Start with a research question and attributable sources
Bring an interview transcript or notes you have permission to process, the customer segment and the question you want to understand. Preserve enough context to distinguish a participant's statement from an interviewer's suggestion.
A set of interviews can contain several users from the same account. Count that deliberately. Do not let repeated sentences or several people from one company turn into an unsupported claim about market demand.
From one conversation to a focused research plan
Keep the extraction and the interpretation distinct. A source-backed observation can support several explanations. An AI-generated theme is a candidate to check against the selected sources, not an automatically accepted customer truth.
- Set the objective or prepare an interview guide before the conversation.
- Ingest the interview and review evidence attribution.
- Select the conversations or evidence records for cross-interview synthesis.
- Explore jobs, pains, customer language or a hypothesis using the selected evidence.
- Review contradictions, missing evidence and a proposed plan for the next interviews.
What a reusable observation looks like
Synthetic teaching example: two separate accounts describe checking a report before sharing it. One uses an email approval; the other has no formal approver. These notes do not establish that both need the same feature.
- Observation
- Both accounts check the report before sharing.
- Source scope
- Two synthetic accounts; separate interview notes and distinct workflows.
- Contradiction
- Only one account has a named approval step.
- Candidate hypothesis
- The common problem may be confidence in the report rather than an approval feature.
- Next question
- What do you check before sharing, and what happened the last time a report was wrong?
Review the evidence before using it elsewhere
Confirm source permission, attribution, segment and time scope. Review any required permission before processing private interviews. Select what may be handed to another Room instead of treating the entire research history as its context.
The team can organize evidence and propose research steps. It cannot prove product-market fit from a few interviews, supply absent consent or decide which customer claim becomes canonical business truth. Human review and the next real conversation remain part of the work.
Access and review
Closed Beta requires an application, manual approval, invitation and verified login. Applying does not grant immediate access. Six ready-made teams, guarded Custom teams and the Apps catalog are included. No Oqera payment or subscription is required. Bring your own AI provider key and pay the provider directly. External actions require specific permission and review; unattended schedules and triggers are off.