Hypotheses
Hypotheses are testable assumptions about user behavior, needs, or product performance that guide your research. The hypothesis tracker helps you define, prioritize, and validate hypotheses throughout your research study.
How it works
Each hypothesis includes a statement, priority level, category, target segments, expected evidence, and testing methodology. Hypotheses progress through validation statuses as research data accumulates: Untested, Testing, Supported, Refuted, or Partially Supported.
You can attach evidence clusters to hypotheses, grouping quotes and observations that support or refute each assumption. The evidence clusters include sentiment tracking (positive, negative, neutral) and confidence scores.
Hypothesis statuses
| Status | Description |
|---|---|
| Untested | No research data has been collected yet. |
| Testing | Currently being investigated through active research. |
| Supported | Evidence supports the hypothesis. |
| Refuted | Evidence contradicts the hypothesis. |
| Particially Supported | Mixed evidence; some support, some contradiction. |
Priority and categories
Hypotheses are assigned priority levels (High, Medium, Low) to focus research efforts. Categories help organize hypotheses by theme: Primary (core product assumptions), Workflow, Usability, Organizational, and Feature.
Related features
Hypotheses connect to Research Questions to establish research scope. Tasks link to hypotheses through the Coverage tab. The Synthesis tab supports evidence collection through affinity mapping. Evidence clusters can reference specific participants and sessions.