Use this when the team has more research questions than capacity to answer them. Prevents "we should do more research" without focus. Produces a prioritized research roadmap: questions mapped to business decisions, scored on impact and uncertainty, sequenced with recommended methods.
Related skills: Complements
/assumption-map(assumptions vs. research questions -- related but distinct lenses). Upstream:/discovery-questionsgenerates questions. Downstream: prioritized questions feed into/interview-plan,/survey-design,/usability-test-plan, or/concept-test-plandepending on question type. Uses/research-repositoryto check what's already known.
Process
Step 1: Gather inputs
Ask the user to provide:
- Open research questions -- what does the team want to learn? Collect from PMs, designers, engineers, leadership. Include questions from retros, strategy reviews, customer escalations, and roadmap debates.
- Business context -- what decisions are coming up in the next 1-3 months? (Roadmap bets, pricing changes, new market entry, feature launches, platform migrations.)
- Existing knowledge -- what do you already know? (Prior research, analytics, customer feedback. Reference
/research-repositoryif one exists.) - Research capacity -- how many studies can you run per month? Who runs them? What methods are available?
- Stakeholders -- who is asking these questions, and what will they do with the answers?
Step 2: Map questions to business decisions
For each research question, identify the business decision it informs. Questions that don't connect to a decision are interesting but not actionable.
## Research Prioritization -- (Team/product, date)
### Question-to-decision map
| # | Research question | Business decision it informs | Decision timeline | Stakeholder |
|---|---|---|---|---|
| 1 | (e.g., "Do enterprise users need SSO to convert?") | (Whether to invest in SSO integration for Q3) | (Q2 planning -- 6 weeks) | (Head of Product) |
| 2 | (e.g., "Why do users drop off after onboarding?") | (Whether to redesign onboarding or focus on activation) | (Next sprint planning -- 2 weeks) | (Growth PM) |
| 3 | (e.g., "How do power users organize their projects?") | (Information architecture for v2 redesign) | (Q3 -- 3 months) | (Design lead) |
| 4 | (e.g., "What's our competitive position on pricing?") | (Pricing model change for annual planning) | (Annual planning -- 4 months) | (CEO) |
Mapping rules:
- If a question doesn't connect to a decision, ask: "If we knew the answer, what would we do differently?" If the answer is "nothing," deprioritize it.
- Multiple questions can inform the same decision. Group them.
- Decision timeline matters: research that arrives after the decision is made is wasted.
Step 3: Score impact and uncertainty
Rate each question on two axes:
### Impact x Uncertainty matrix
| # | Research question | Impact if answered | Current uncertainty | Priority score |
|---|---|---|---|---|
| 1 | (Question) | High | High | **Research now** |
| 2 | (Question) | High | Medium | **Research soon** |
| 3 | (Question) | Medium | High | **Research when capacity allows** |
| 4 | (Question) | Low | High | **Skip -- low impact** |
| 5 | (Question) | High | Low | **Skip -- already know enough** |
### Scoring definitions
**Impact if answered (what changes if we know this?):**
- **High:** Directly changes a major product or business decision. Gets mentioned in leadership discussions.
- **Medium:** Informs a feature-level decision or validates a direction. Useful but not decisive.
- **Low:** Satisfies curiosity or provides background. No specific decision at stake.
**Current uncertainty (how much do we already know?):**
- **High:** No data, conflicting signals, or complete guesswork. We're making assumptions.
- **Medium:** Some signals (support tickets, analytics, a few interviews) but not confident enough to act.
- **Low:** Strong evidence from multiple sources. We know enough to decide.
Step 4: Sequence into a research roadmap
### Research roadmap
**Now (next 2-4 weeks)**
| Question | Recommended method | Why this method | Effort | Decision it unblocks |
|---|---|---|---|---|
| (Highest priority question) | (e.g., 6 user interviews) | (Need qualitative depth on a behavioral question) | (2 weeks) | (Decision and timeline) |
| (Second priority question) | (e.g., Analytics deep-dive) | (Quantitative answer exists in data, no need for primary research) | (3 days) | (Decision and timeline) |
**Next (4-8 weeks)**
| Question | Recommended method | Why this method | Effort | Decision it unblocks |
|---|---|---|---|---|
| (Question) | (Method) | (Rationale) | (Effort) | (Decision) |
**Later (8+ weeks)**
| Question | Recommended method | Why this method | Effort | Decision it unblocks |
|---|---|---|---|---|
| (Question) | (Method) | (Rationale) | (Effort) | (Decision) |
**Parked (not pursuing now)**
| Question | Why parked |
|---|---|
| (Question) | (Low impact / already know enough / decision timeline too far out) |
Sequencing rules:
- Sequence by decision timeline, not just priority score. A medium-priority question with a 2-week decision deadline beats a high-priority question with a 3-month horizon.
- Batch related questions into a single study when possible. (e.g., interview questions about onboarding and activation can be covered in the same sessions.)
- The "Now" bucket should contain no more than 2-3 studies. If it has more, you haven't prioritized hard enough.
- "Parked" is not "rejected." It means "not now." Review parked questions quarterly.
Step 5: Review and validate
Ask the user:
- Are the impact ratings honest? (Teams often rate everything as "high impact" to justify research they want to do.)
- Are decision timelines real? (If the decision will happen regardless of research, the research doesn't matter.)
- Is the "Now" bucket achievable with current capacity? (2-3 studies max in a 2-4 week window for most teams.)
- Who will communicate the roadmap to stakeholders? (Stakeholders who submitted questions need to know what's being prioritized and what's parked.)
- When will you re-prioritize? (Monthly is typical. Research questions evolve as decisions get made.)
Output location
Present the research roadmap as formatted text in the conversation. The user copies it into their team planning documents and shares with stakeholders.
Example Output
Input
- Open research questions: 9 questions collected from the team at Fieldstone, a B2B construction project management platform (~$18M ARR, 400 enterprise customers): (1) Why do site supervisors stop using the daily log feature after week 3? (2) Would subcontractors pay for their own Fieldstone accounts? (3) Do general contractors want Gantt-style scheduling or is the current card view enough? (4) How do users feel about the new mobile redesign? (5) What would make customers willing to pay for a premium tier? (6) How do competitors handle document versioning? (7) Why did 3 enterprise accounts churn in Q1? (8) Are users finding the RFI tracking module on their own, or only via support? (9) What does a "successful project closeout" look like from the GC's perspective?
- Business context: Three decisions in the next 90 days: (A) Whether to build a subcontractor seat model for Q3 roadmap — decision in 5 weeks at board review; (B) Whether to redesign the scheduling module or invest elsewhere — decision in 8 weeks at Q3 planning; (C) Whether to launch a premium tier at Fieldstone's annual customer summit — decision in 11 weeks
- Existing knowledge: Analytics show 62% drop in daily log usage by day 21; Q1 churn post-mortems completed with partial notes from 2 of 3 accounts; no prior research on subcontractor willingness to pay; NPS = 34, mobile redesign feedback sparse (12 app store reviews)
- Research capacity: One UX researcher (Priya), 2 studies per month max; PM (Derek) can run lightweight analytics pulls; no external recruiting budget — must use existing customer panel
Output
Research Prioritization — Fieldstone Platform, May 2025
Question-to-decision map
| # | Research question | Business decision it informs | Decision timeline | Stakeholder |
|---|---|---|---|---|
| 1 | Why do site supervisors stop using the daily log after week 3? | Whether to redesign onboarding/activation or deprioritize daily log | Q3 planning — 8 weeks | Derek (PM) |
| 2 | Would subcontractors pay for their own Fieldstone accounts? | Whether to build a subcontractor seat model for Q3 roadmap | Board review — 5 weeks | CEO / Board |
| 3 | Do GCs want Gantt scheduling or is card view enough? | Whether to invest in scheduling module redesign | Q3 planning — 8 weeks | Derek (PM) |
| 4 | How do users feel about the new mobile redesign? | Whether to iterate on mobile before broader rollout | Ongoing / no hard deadline | Design lead |
| 5 | What would make customers pay for a premium tier? | Premium tier pricing and feature bundling for customer summit | Summit — 11 weeks | CEO / Revenue |
| 6 | How do competitors handle document versioning? | Informs doc versioning roadmap debate | No active decision | Derek (PM) |
| 7 | Why did 3 enterprise accounts churn in Q1? | Retention playbook and whether churn was product vs. relationship | Immediate — CS needs now | CS lead |
| 8 | Are users discovering the RFI module without support? | Whether to invest in in-app discoverability or leave as-is | Q3 planning — 8 weeks | Derek (PM) |
| 9 | What does "successful project closeout" look like for GCs? | Potential closeout feature set for H2 | H2 planning — 4+ months | Design lead |
Note on Q7: Post-mortems exist for 2 of 3 churned accounts. The remaining account and pattern synthesis can be completed internally by CS — this does not need a formal research study.
Note on Q6: Competitive analysis doesn't connect to an active product decision. Parked until a doc versioning debate is formally on the roadmap.
Impact × Uncertainty matrix
| # | Research question | Impact if answered | Current uncertainty | Priority score |
|---|---|---|---|---|
| 2 | Subcontractor willingness to pay | High — directly determines whether a new revenue model enters Q3 roadmap | High — no data, pure assumption | ✅ Research now |
| 1 | Daily log drop-off after week 3 | High — 62% drop is a known metric but root cause is unknown; informs activation investment | High — analytics show the drop, not the why | ✅ Research now |
| 3 | Gantt vs. card view for scheduling | High — scheduling module is a major Q3 investment candidate | Medium — some sales call signals, no structured research | 🔜 Research soon |
| 5 | Premium tier willingness to pay | High — affects pricing strategy and summit launch narrative | Medium — directional NPS data but no pricing-specific research | 🔜 Research soon |
| 8 | RFI module discoverability | Medium — feature investment is modest; discoverability fix may be lightweight | High — support volume suggests low discovery but unconfirmed | 📅 When capacity allows |
| 4 | Mobile redesign sentiment | Medium — rollout decision is low-stakes; 12 reviews insufficient | Medium — sparse signal, but decision isn't urgent | 📅 When capacity allows |
| 7 | Q1 churn root cause | High — but 2 of 3 post-mortems exist; synthesis > new research | Low — mostly answered; needs internal synthesis, not a study | ⏭️ Skip — handle internally |
| 9 | GC project closeout definition | Medium — H2 feature set, no active decision | High — but decision is 4+ months out | 🅿️ Park — too early |
| 6 | Competitor doc versioning | Low — no active decision attached | High | 🅿️ Park — low impact |
Research roadmap
Now (next 2–4 weeks)
| Question | Recommended method | Why this method | Effort | Decision it unblocks |
|---|---|---|---|---|
| Would subcontractors pay for Fieldstone seats? (Q2) | 8 concept-test interviews with subcontractors sourced via GC customer panel | Need directional willingness-to-pay signal fast; no time for a survey build; qualitative framing of value props | 2.5 weeks (Priya leads) | Subcontractor seat model — board review in 5 weeks |
| Why do site supervisors stop using daily log after week 3? (Q1) | Analytics deep-dive + 5 targeted user interviews | Analytics (Derek, 3 days) scopes the drop-off pattern; interviews explain the behavioral why | Analytics: 3 days / Interviews: 2 weeks, can run in parallel | Activation investment decision — Q3 planning in 8 weeks |
⚠️ These two studies overlap in timing. Priya runs interviews for both concurrently using a shared screener. Derek owns the analytics pull independently.
Next (4–8 weeks)
| Question | Recommended method | Why this method | Effort | Decision it unblocks |
|---|---|---|---|---|
| Gantt vs. card view for scheduling (Q3) | Concept test + 6 GC interviews with prototype options | Need to validate direction before committing engineering; two distinct interaction models to compare | 3 weeks (Priya) | Scheduling module investment — Q3 planning |
| Premium tier willingness to pay (Q5) | 10-question survey to customer panel + 4 follow-up interviews | Survey establishes breadth across segments; interviews unpack feature value hierarchy | Survey: 1 week / Interviews: 2 weeks | Premium tier bundling — summit in 11 weeks |
Batch Q3 and Q5 interviews in the same recruiting wave where participants qualify for both — saves scheduling overhead.
Later (8+ weeks)
| Question | Recommended method | Why this method | Effort | Decision it unblocks |
|---|---|---|---|---|
| GC project closeout mental model (Q9) | Contextual inquiry / diary study with 4–6 GC project managers | Closeout is a complex, multi-week workflow — needs observational depth, not just interviews | 4 weeks | H2 feature set — planning cycle TBD |