Customer research guide

Opportunity Scoring for Product Decisions

Opportunity scoring helps a team find needs customers consider important but poorly satisfied. It ranks outcomes to investigate, not features to build automatically.

About this guide

Prepared by LearnLive with AI assistance, then checked against the sources listed below. Published July 22, 2026.

Short answer

Ask customers to rate how important an outcome is and how satisfied they are with current solutions. A common score is Importance + max(Importance - Satisfaction, 0). High scores point to important, underserved needs that deserve further discovery.

  • Survey desired outcomes, not reactions to a feature pitch.
  • Analyze meaningful customer segments separately before averaging results.
  • Use a high score to direct discovery, then test whether a solution changes behavior.

Measure importance and satisfaction separately

Importance asks how much the customer cares about achieving an outcome. Satisfaction asks how well current approaches help them achieve it. The gap matters because a highly important outcome may already be served well, while a low-satisfaction outcome may not matter enough to justify investment.

Keep the outcome statement independent of a proposed feature. Instead of asking whether customers want an AI summary button, ask how important it is to capture decisions after a meeting and how satisfied they are with their current process.

Relay opportunity scores on a 1-to-10 scale
Customer outcomeImportanceSatisfactionScore
Find an old decision quickly9414
Change workspace colors324
Invite a teammate securely879

Turn a score into a discovery question

Relay's strongest opportunity is finding an old decision quickly. That does not prove search is the answer. The team should observe how people currently retrieve decisions, identify where the process fails, and compare smaller solution ideas before committing to a large feature.

Segment results when needs differ. An administrator and a daily project contributor may give the same outcome very different importance ratings. A single blended average can hide both groups.

Common mistakes

  • Asking customers to rate a feature instead of the outcome they need.
  • Combining distinct customer segments before checking their differences.
  • Treating small score differences as precise when the sample is limited.
  • Jumping from a high opportunity score to one preferred solution.

Check your understanding

An outcome has importance 8 and satisfaction 5. What is its score using Importance + max(Importance - Satisfaction, 0)?

11, because 8 + max(8 - 5, 0) = 11.

Sources

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