Skip to content
ProductivityAdvanced

Weighted Decision Matrix for a Tough Choice

Compare options against criteria you care about, with weights, scores, and a stress test of the result before you decide.

Share on X (opens in a new tab)Share on LinkedIn (opens in a new tab)

Make it yours

Fill in each variable and watch the prompt update. Anything still in {{braces}} needs your input before you use it.

Fill in the blanks

0 of 4 filled

The decision you're facing.

The options (2–4 works best).

What matters, with rough importance.

Details about each option.

Live previewUnfilled
Help me make a decision using a weighted decision matrix. Act as a neutral, clear-thinking advisor — your job is to structure my thinking, not to decide for me.

Decision: {{decision}}
Options: {{options}}
What matters to me (criteria), with rough importance: {{criteria}}
Relevant facts and constraints: {{facts}}

Steps:
1. Confirm the criteria and convert my importance levels into weights that add up to 100%. If an obvious criterion seems missing, suggest it but don't add it without flagging.
2. Score each option 1–5 on each criterion, with a one-line justification based on my facts. Mark any score that's a guess because I didn't give enough information.
3. Show a table with weighted totals.
4. Stress test: Would the winner change if the top-weighted criterion's weight shifted by 10 points? What single assumption, if wrong, would flip the result?
5. End with 2 questions I should answer for myself before deciding.

Remember: the numbers support my judgment; they don't replace it.
Open in Playground

Example

Example input

Filled prompt
Help me make a decision using a weighted decision matrix. Act as a neutral, clear-thinking advisor — your job is to structure my thinking, not to decide for me.

Decision: Which apartment to rent for the next year
Options: Apartment A (downtown), Apartment B (suburb), Apartment C (near my office)
What matters to me (criteria), with rough importance: monthly cost (high), commute time (high), space (medium), neighborhood feel (medium), natural light (low)
Relevant facts and constraints: A: $1,800/mo, 25-min commute, 1 bedroom, lively area with cafés, great light. B: $1,400/mo, 50-min commute, 2 bedrooms, quiet, average light. C: $1,650/mo, 10-min walk to work, 1 small bedroom, mostly offices, little light. My budget max is $1,700.

Steps:
1. Confirm the criteria and convert my importance levels into weights that add up to 100%. If an obvious criterion seems missing, suggest it but don't add it without flagging.
2. Score each option 1–5 on each criterion, with a one-line justification based on my facts. Mark any score that's a guess because I didn't give enough information.
3. Show a table with weighted totals.
4. Stress test: Would the winner change if the top-weighted criterion's weight shifted by 10 points? What single assumption, if wrong, would flip the result?
5. End with 2 questions I should answer for myself before deciding.

Remember: the numbers support my judgment; they don't replace it.

Example output

Illustrative example response — written by Promptly, not generated live

1. Weights: Cost 30% · Commute 30% · Space 15% · Neighborhood 15% · Light 10%. Possibly missing: your budget is $1,700, so A is over budget — treat that as a dealbreaker or a criterion?

2–3. Scores and totals

Criterion (weight)ABC
Cost (30%)2 — over budget5 — cheapest3 — within budget
Commute (30%)3 — 25 min1 — 50 min5 — 10-min walk
Space (15%)35 — 2 bedrooms2 — small
Neighborhood (15%)53 (guess)2
Light (10%)531
Weighted total3.203.303.10

4. Stress test: The scores are very close. If commute rises to 40% and cost drops to 20%, B falls to 2.90 while A and C tie at 3.30. The key assumption: can you tolerate a 50-minute commute every day? If not, B is out.

5. Ask yourself

  • How would I feel about each commute in the middle of winter?
  • Is going over budget for A ever acceptable, or is $1,700 a hard limit?

Why it works

A weighted matrix turns a gut-wrenching choice into explicit trade-offs. The prompt asks the model to justify each score from your facts and mark guesses, so you can see exactly where the numbers are solid and where they're shaky.

The stress test is the most valuable part: close totals are a sign that one assumption matters more than the math, and naming it helps you focus. Framing the AI as a neutral advisor keeps the final decision where it belongs — with you. Double-check the arithmetic, as models can make calculation errors.

Techniques used