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Research Prioritization for a Backlog

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Decide what to study next.

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Prioritize research requests. Requests with context: [RESEARCH_REQUESTS]. Team capacity: [CAPACITY]. Upcoming product decisions and dates: [DECISIONS].

Score each request from 1 to 5 on decision impact, uncertainty (how little we know), timeliness (is a decision coming?), cost and effort (reverse scored), and reusability. Compute a weighted score with weights I can adjust (default 30, 25, 20, 15, 10), showing arithmetic. Challenge each request: what decision will change depending on the result? could existing data answer it? is a lighter method enough?

Produce a ranked table with recommended method and duration, items to decline or redirect with reasons (and a response message of 60 words), and a quarter plan fitting capacity. Add an intake form for new requests.

Provide the scoring table with arithmetic, the recommended order, and the estimated weeks of effort per request. State which requests could be answered by existing data or a quicker method, and what you would do for those.

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Weights: decision impact 30, uncertainty 25, timeliness 20, effort (reverse) 15, reuse 10.
Request A (onboarding drop-off): impact 5, uncertainty 4, timeliness 5, effort 3 (reverse 3), reuse 4. Score = 5x0.30 + 4x0.25 + 5x0.20 + 3x0.15 + 4x0.10 = 1.5 + 1.0 + 1.0 + 0.45 + 0.4 = 4.35 out of 5.
Request B (logo preference): impact 2, uncertainty 3, timeliness 2, effort 4, reuse 1 = 0.6 + 0.75 + 0.4 + 0.6 + 0.1 = 2.45.
Request C (pricing page test): 4, 4, 4, 2, 3 = 1.2 + 1.0 + 0.8 + 0.3 + 0.3 = 3.6.
Order: A, C, then B (decline: use a quick poll).
Capacity: 20 days; A 8 days, C 6, B 2: total 16.
Decline message (60 words): "Thank you; we cannot study this now. Existing data may help: here is where to look."

Illustrative only, made-up data. Your results will differ and must be reviewed.

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