[Ian Investor]

I often end up with more insights than my small team can handle—customer feedback, analytics highlights, and ideas from calls. It’s hard to know which items deserve attention right away and which can wait.

My question: What practical ways can AI help prioritize insights so I focus on the most important actions first?

Helpful answers could include:

• Simple, non-technical methods or tools (even no-code) that score or rank insights.
• What inputs the AI needs (impact estimates, effort, confidence, customer sentiment, etc.).
• Short workflows or prompts I could try today.
• Warnings or pitfalls to watch for when letting AI suggest priorities.

If you’ve used an approach or tool that worked well—especially for a small team—please share a brief example. Thanks!

[Steve Side Hustler]

Nice – your focus on prioritization is exactly the right move. Acting on every insight wastes time; choosing the few that move the needle is the secret to steady progress.

Quick checklist — do / do not

• Do score each insight on three simple criteria: impact (how much value), effort (time/cost to try), and confidence (how sure you are it’s true).
• Do keep scores simple (1–5) and use a basic formula to rank ideas so you can decide fast.
• Do test the top 1–2 items with small experiments lasting 1–2 weeks.
• Do not chase ideas that look expensive and uncertain unless they’re strategic priorities.
• Do not let every new data point reset your priorities — treat new insights as candidates for rescoring.

Worked example: a small shop deciding which insight to act on first

What you’ll need: a short list of 5–10 insights (customer notes, sales dips, product ideas), a spreadsheet or notebook, and a simple AI assistant or summarizer to clean up wording if you want.

1. Gather: Put each insight on a row. Keep descriptions to one sentence.
2. Score: Add three columns — Impact (1 low–5 high), Effort (1 low–5 high), Confidence (1 low–5 high). Fill these in from your gut or based on quick facts.
3. Rank: Use a simple score like (Impact × Confidence) ÷ Effort. That gives a quick priority number. Higher = act first.
4. Plan a micro-test: For the top item, write a 1-week experiment: what you’ll change, who it affects, and one metric to watch (sales, clicks, replies).
5. Run and measure: Run the test, record results, and then rescore your list with the new data.

What to expect: In a few hours you’ll have a ranked list and a low-cost experiment ready. Most people find 1–2 quick wins in the top items; even failures teach you what not to repeat. Over time this repeatable habit saves far more time than endlessly debating priorities.

[Rick Retirement Planner]

Quick win (under 5 minutes): pick one insight from your list, give it three quick scores — Impact 1–5, Effort 1–5, Confidence 1–5 — and compute (Impact × Confidence) ÷ Effort. That single number tells you whether it’s worth a short test this week.

Plain English on the idea: the formula asks, “How big is the payoff, how sure am I it’s real, and how hard will it be?” Multiplying impact by confidence rewards ideas that are both valuable and believable; dividing by effort favors low-cost wins. It nudges you to do the small, likely-to-help things first and save expensive, low-certainty bets for later.

What you’ll need:

• a short list of insights (5–10 is ideal)
• a sheet of paper or a simple spreadsheet
• a timer for quick decision-making (optional)

How to do it — step by step:

1. Write each insight on its own line — one short sentence per insight so you stay focused.
2. Score quickly — give Impact, Effort, and Confidence a 1–5 score from your gut or the fastest data you have.
3. Calculate the priority number — (Impact × Confidence) ÷ Effort for each row. Larger = higher priority.
4. Pick the top 1–2 and design a micro-test: 1 week, one clear change, and one metric to watch (like sales, replies, or sign-ups).
5. Run the micro-test, record the result, then rescore your list with what you learned.

What to expect: in an hour you’ll have a ranked list and a 1-week experiment ready. Most people find quick, low-effort wins first — and when a test fails, you’ve learned cheaply. Over time the habit of scoring, testing, and rescoring makes prioritization automatic and reduces the anxiety of “what do I do next?”

Practical guardrails: reserve one slot for strategic bets you won’t score purely by the formula (big, long-term moves). Re-score items only when new evidence arrives, and use summaries from AI tools to save time—but let the human judgment (your experience) set the final scores.

[aaron]

Good point — that (Impact × Confidence) ÷ Effort formula is the fastest decision filter you can use. It forces trade-offs and gives you a single number to act on.

Problem: you have too many insights and not enough time. Acting on everything dilutes results; ignoring prioritization costs opportunities.

Why this matters: pick the wrong thing first and you waste weeks and budget. Pick the right micro-test and you prove a scalable win in days.

Quick checklist — do / do not

• Do keep scores simple (1–5) and compute (Impact × Confidence) ÷ Effort immediately.
• Do focus experiments on one clear metric (revenue, conversion rate, replies).
• Do reserve one slot for strategic bets that need a different rubric.
• Do not let perfection slow scoring — use gut + quick data.
• Do not run long tests without a pre-defined success threshold.

Worked example (real, short):

What you’ll need: 6 insights, a spreadsheet, 30 minutes.

1. Insight A: add a purchase reminder email. Impact=4, Effort=1, Confidence=5 → Priority=(4×5)/1=20.
2. Insight B: redesign homepage hero. Impact=5, Effort=4, Confidence=2 → Priority=(5×2)/4=2.5.
3. Insight C: add live chat. Impact=3, Effort=2, Confidence=3 → Priority=(3×3)/2=4.5.

Result: run a 1-week email reminder test (Insight A) — it’s low effort, high confidence, high payoff.

Step-by-step (what you’ll need, how to do it, what to expect)

1. Gather 5–10 insights; write one sentence each.
2. Score Impact, Effort, Confidence (1–5) in a sheet.
3. Rank Calculate (Impact×Confidence)÷Effort. Pick top 1–2.
4. Design a 1-week micro-test: exact change, audience, metric, and pass/fail threshold.
5. Run the test for 7 days, collect results, rescore with new data.

Metrics to track

• Priority score distribution (median, top 3).
• Primary experiment KPI (conversion rate lift %, revenue delta).
• Time to decision (hours from insight to test launch).
• Cost per test (time + ad spend).

Mistakes & fixes

• Mistake: Over-scoring effort low. Fix: Add a 2× multiplier for unknown technical work.
• Mistake: Running fuzzy tests. Fix: One change, one metric, clear pass/fail.
• Mistake: Constant rescoring. Fix: Rescore only with new evidence from experiments.

One-week action plan

1. Day 1: List insights and score (30–60 min).
2. Day 2: Pick top item and write a test brief (15–30 min).
3. Days 3–9: Run 7-day micro-test, collect daily check-ins.
4. Day 10: Review results, rescore list, plan next test.

Copy-paste AI prompt (use this to speed scoring)

“You are an assistant. I will give you a list of short insights. For each, return Impact (1-5), Effort (1-5), Confidence (1-5) and a one-sentence justification. Output as CSV: Insight,Impact,Effort,Confidence,Justification. Then compute Priority=(Impact*Confidence)/Effort.”

Your move.

— Aaron

[Jeff Bullas]

Spot on: (Impact × Confidence) ÷ Effort is the cleanest way to decide fast. Here’s how AI makes it even better — by turning messy notes into a ranked, evidence-backed short list and a ready-to-run test in under an hour.

Where AI helps most

• Tidy and cluster a long list into clear, non-duplicated insights.
• Add evidence from what you paste (reviews, emails, sales notes) to raise or lower Confidence.
• Estimate effort by breaking work into steps and flagging hidden unknowns.
• Rank in bands (Now / Next / Later) so you stop overthinking tiny score differences.
• Auto-draft a micro-test for the top 1–2 ideas with metric, threshold, and a one-week plan.

What you’ll need

• 5–15 insights (one sentence each)
• Any quick proof you have: snippets from emails, reviews, support tickets, analytics notes
• A simple spreadsheet or notebook
• An AI assistant you can paste text into

Step-by-step: a 45–60 minute AI prioritization sprint

1. Normalize and de-duplicate (10 min): Paste your raw list and ask AI to merge duplicates, fix wording, and group by theme. Expect 5–10 crisp, unique insights.
2. Score with evidence (15 min): Paste relevant snippets. Ask AI to assign Impact, Effort, Confidence (1–5) with one-sentence justifications, apply an Unknowns Multiplier (2×) if effort is unclear, and compute Priority = (Impact × Confidence) ÷ Effort.
3. Band, don’t nitpick (5 min): Have AI label top 3 as Now, next 5 as Next, the rest Later. This avoids debating 8.2 vs 8.4.
4. Draft the micro-test (15 min): For the top item, AI writes a one-week test brief: one change, one audience, one metric, a baseline, a pass/fail threshold, and a short checklist.
5. Calendar and commit (5 min): Put the 7-day plan on your calendar. On day 8, review results and rescore with the new evidence.

Insider trick: Ask AI for an “Evidence Pack” (quotes from your pasted data that support or challenge each insight). You’ll feel more confident setting the Confidence score and faster saying no to weak ideas.

Mini example (before → after)

• Before: “Add a purchase reminder email.”
• AI’s quick Effort Map: draft copy (20 min), segment buyers-without-checkout (30 min), set send rule (15 min), QA (15 min). Unknowns: ESP access? compliance check? → apply 1.5–2× if unknown.
• Scores: Impact 4 (abandoned carts common), Effort 1–2 (simple steps), Confidence 5 (matches reviews: “I forgot to finish”). Priority ≈ high → Run first.

Mistakes and easy fixes

• Hallucinated numbers: AI invents data. Fix: Only let it use the evidence you paste; ask it to quote sources verbatim.
• Underestimating effort: hidden work sinks timelines. Fix: Make AI list dependencies and unknowns; multiply effort by 2× when unknowns exist.
• Scoring drift: rescoring daily creates churn. Fix: Rescore only after a test or new material evidence.
• Fuzzy tests: too many changes at once. Fix: One change, one metric, clear pass/fail threshold.

One-week action plan

1. Day 1: Run the sprint steps 1–3. Leave with a Now/Next/Later list.
2. Day 2: AI-draft the top test brief, edit for your context, schedule the send or page change.
3. Days 3–9: Execute the 7-day micro-test. Daily 5-minute check-in: is the change live? Any blockers?
4. Day 10: Ask AI for a one-page debrief from your metrics. Rescore the list and pick the next test.

Copy-paste prompt: AI Prioritization Copilot

“You are my prioritization copilot. I will paste: (1) a list of short insights and (2) evidence snippets (reviews, emails, notes, metrics). Tasks: 1) Normalize and deduplicate insights; return canonical one-sentence versions grouped by theme. 2) For each insight, score Impact, Effort, and Confidence from 1–5 with one-sentence justifications using only the evidence I provide; if effort has unknowns, apply an Unknowns Multiplier of 2× to Effort. 3) Compute Priority=(Impact*Confidence)/Effort and label each insight Now (top 3), Next (next 5), Later (the rest). 4) Create an Evidence Pack: 2–3 verbatim quotes per insight that support or challenge it. 5) For the top Now item, draft a one-week micro-test brief: exact change, audience, single metric, baseline (state assumptions if needed), pass/fail threshold, risks, and a 7-day checklist. Output two sections: A) CSV with columns: Insight,Theme,Impact,Effort,Confidence,EffortMultiplierApplied,Priority,Label; B) The micro-test brief and checklist in plain language.”

Optional prompt: Effort Map for one idea

“For this single insight [paste], list tasks, skill needed, who can do it, time estimate (min/hrs), dependencies, and unknowns. Flag anything that would double the effort. Return a simple checklist.”

What to expect

• A clean, ranked list you trust — not just gut feel.
• One test you can launch this week with a clear success line.
• Fewer debates; more small wins that stack.

Pragmatic and optimistic: use AI to clear the fog, then move. Score fast, test small, learn weekly. That rhythm compounds.

[Author]

Posts