Opportunity Scoring: How to Prioritize What Actually Matters

You have 47 feature requests in your backlog. Every stakeholder thinks their priority should be next. Customer feedback is pulling you in eight different directions. How do you decide what to build?

Most product teams rely on gut feel, HiPPO (Highest Paid Person's Opinion), or rough scoring matrices. But there's a better way: Opportunity Scoring, a systematic approach from the Outcome-Driven Innovation methodology.

What is Opportunity Scoring?

Opportunity Scoring is a systematic method for identifying which customer outcomes are underserved. The fundamental insight: the biggest opportunities lie where importance is high but satisfaction is low.

The algorithm is beautifully simple:

Opportunity Score = Importance + max(Importance - Satisfaction, 0)

This gives you a score from 1 to 20 for each outcome, where:

• Scores of 15+ indicate significant opportunities (underserved)
• Scores of 10-15 indicate moderate opportunities
• Scores of 5-10 indicate served outcomes
• Scores below 5 indicate overserved outcomes (you might be over-investing)

Why This Works Better Than Traditional Methods

Traditional Approach: RICE, Feature Voting, etc.

• Based on what customers ask for (solutions, not problems)
• Biased toward vocal customers
• No systematic way to identify gaps
• Difficult to compare across different types of features

Opportunity Scoring Approach:

• Based on customer outcomes (what they're trying to achieve)
• Identifies gaps between importance and satisfaction
• Comparable across all outcomes
• Data-driven and defensible

How to Implement Opportunity Scoring

Step 1: Define Customer Outcomes

Outcomes are different from features. They're the measurable results customers want to achieve.

Feature thinking: "Customers want email notifications"
Outcome thinking: "Minimize the time it takes to learn about critical feedback"

Outcomes follow this structure: [Direction] [unit of measure] [object of control]

Examples:

• Minimize the time it takes to identify at-risk customers
• Increase the confidence in prioritization decisions
• Reduce the effort required to prepare stakeholder updates
• Improve the accuracy of trend detection

Step 2: Survey Customers on Importance and Satisfaction

For each outcome, ask customers two questions:

1. Importance: "How important is it for you to [outcome]?" (1-5 scale)
2. Satisfaction: "How satisfied are you with your ability to [outcome] today?" (1-5 scale)

You need at least 30-50 responses for reliable data, though you can start with smaller samples for initial insights.

Step 3: Calculate Opportunity Scores

For each outcome:

Importance (avg across customers)
+ max(Importance - Satisfaction, 0)
= Opportunity Score

For example:

• Outcome: "Minimize time to identify trends in customer feedback"
• Importance: 4.8
• Satisfaction: 2.3
• Gap: 4.8 - 2.3 = 2.5
• Opportunity Score: 4.8 + 2.5 = 7.3

Wait, that's only a 7.3—not high priority. The math is forcing you to be honest about what really matters.

Now try this one:

• Outcome: "Increase confidence in what to build next"
• Importance: 4.9
• Satisfaction: 2.1
• Gap: 4.9 - 2.1 = 2.8
• Opportunity Score: 4.9 + 2.8 = 7.7

Hmm, still not above 10. What about this:

Using the standard 1-5 scale, the formula remains: Importance + max(Importance - Satisfaction, 0).

On a 1-5 scale:

• Outcome: "Reduce time to prepare quarterly roadmap reviews"
• Importance: 4.7
• Satisfaction: 2.0
• Opportunity: 4.7 + 2.7 = 7.4

The key insight: if nothing scores above 10, you might be measuring the wrong outcomes, or your product is already meeting the most critical needs.

Step 4: Focus Your Roadmap

Start with the highest opportunity scores:

• 15+: Major gaps, high strategic value
• 10-15: Solid opportunities worth exploring
• Below 10: Lower priority or already served

A Real Example: B2B SaaS Product Team

Let's say you're running a product feedback tool. You survey 40 product managers and find:

Your priorities are now clear:

1. Build features that increase confidence in prioritization decisions (12.5)
2. Help teams identify top themes quickly (11.5)
3. Enable trend detection (11.3)

"Preparing stakeholder updates" scored 8.8—customers care about it, but they're reasonably satisfied. Not a priority right now.

Common Questions

Q: Don't I need hundreds of survey responses?
Best practice recommends 180+ responses for statistical confidence, but you can start smaller. Even 30 responses will show you patterns. Start small, validate with more data over time.

Q: How often should I re-score?
Every 6-12 months, or after major feature releases that target high-opportunity outcomes.

Q: What if my scores are all similar?
That might mean your outcomes aren't specific enough, or you're surveying the wrong customer segment. Try breaking outcomes into more granular statements.

Q: Can I use this for B2B with small customer counts?
Yes, but weight by revenue/strategic value if needed. Five enterprise customers' opinions might matter more than thirty small accounts.

Getting Started This Week

1. List 10-15 outcomes your product helps customers achieve
2. Survey 20 customers (importance + satisfaction for each outcome)
3. Calculate opportunity scores using the formula
4. Compare to your current roadmap - are you working on the highest opportunities?

Opportunity Scoring won't make decisions for you, but it will make your decisions defensible, data-driven, and strategically sound.

Want to implement Opportunity Scoring without building spreadsheets? Vockify has the Ulwick Opportunity Scoring algorithm built-in. Define your customer outcomes, map feedback themes to each outcome, then add importance and satisfaction ratings. The system calculates opportunity scores automatically and highlights your highest-priority outcomes. No spreadsheets, no formulas—just results. Try it free for 14 days.