Decision Matrix Helper Prompt

What this prompt does

Most hard decisions feel hard because you're comparing apples and oranges — different options with different trade-offs across criteria that don't have equal weight. A decision matrix forces you to name what you actually care about, weight it honestly, and score each option against those criteria. The result isn't always the "right" answer, but it makes your reasoning transparent enough to spot when you're rationalizing vs. deciding.

This prompt builds the matrix, weights the criteria, and gives you a recommendation with the reasoning visible.

The prompt

Help me build a decision matrix for this decision:

**What I'm deciding:** [THE CHOICE — e.g., "which project management tool to adopt," "which of 3 job offers to take," "whether to hire a contractor or expand the team"]
**Options I'm considering:**
1. [OPTION A]
2. [OPTION B]
3. [OPTION C — add more if needed]

**What matters to me in this decision:**
- [CRITERION 1 — e.g., "cost"]
- [CRITERION 2 — e.g., "ease of use"]
- [CRITERION 3 — e.g., "integrations with existing tools"]
- [Add 2–3 more]

**Additional context:**
- [ANYTHING THAT CONSTRAINS OR SHAPES THE DECISION — budget limits, timeline, non-negotiables]
- [IF ONE CRITERION IS MORE IMPORTANT THAN OTHERS, NAME IT]

Build the matrix as:
1. Assign weights to each criterion (total = 100) — ask me to confirm or adjust the weights before scoring
2. Score each option 1–5 on each criterion
3. Calculate weighted scores
4. Show the matrix as a table
5. Give a recommendation — and name any case where a different option might be correct (if the weights shifted)

Be honest: if the matrix result contradicts what my gut says, flag that explicitly.

How to use it

1. Get the weights right first — the prompt asks you to confirm weights before scoring. This is the most important step. If "cost" gets 40% and that's actually not your real constraint, the whole matrix skews wrong.
2. Name your non-negotiables separately — a "must-have" criterion isn't a scoring criterion; it's an eliminator. Any option that fails a must-have should be dropped before the matrix runs.
3. Check if you agree with the scores — the AI assigns scores based on what you described. Review each one. Changing a score on a high-weight criterion can flip the recommendation.
4. Trust the gut disagreement flag — if the matrix says Option A but you feel Option B, that's useful data. Either your weights don't reflect your actual priorities, or the gut is wrong for identifiable reasons.

Example output

Decision: Which email marketing tool to switch to (leaving current tool that's too expensive)
Options: Mailchimp, ConvertKit, Beehiiv
Criteria: Cost, deliverability, automation features, ease of use, newsletter-first features

Proposed weights (confirm before I score):

• Cost: 30%
• Deliverability: 25%
• Automation features: 20%
• Ease of use: 15%
• Newsletter-first features: 10%

Assuming confirmed:

Weighted scores:

• Mailchimp: 3.05
• ConvertKit: 4.15
• Beehiiv: 3.85

Recommendation: ConvertKit, with ConvertKit ahead primarily on automation (20% weight) and deliverability (25%).

However: If your list is under 1,000 subscribers and you don't need complex automations, Beehiiv scores higher on cost + ease + newsletter features. The matrix rewards automation at 20%; if that's not your real use case, reconsider the weight.

Gut check: If you find yourself wanting to pick Beehiiv even with ConvertKit winning, it might mean newsletter-specific features deserve more than 10% of the weight.

Variations

Real estate offer comparison

"I have 2 offers on a property. Compare them on: net price after concessions, likelihood of closing (based on financing type), timeline, contingencies, and any unusual terms."

Hiring decision

"I'm choosing between 3 final candidates for [ROLE]. Criteria: technical skill, culture fit, growth potential, availability, and cost. Help me build a scorecard."

Common pitfalls

• Don't: Trust a matrix where you set the weights after seeing which option you want to win. That's reverse-engineering a justification, not making a decision.
• Try instead: Set the weights before you know how the scoring will fall, then commit to the result.

Who uses this prompt

• Small business owners: Tool selection, vendor decisions, hiring
• Managers: Project prioritization, resource allocation, team structure decisions
• Real estate agents: Comparing offers for clients, evaluating investment properties
• Freelancers: Client selection, pricing strategy, business model choices