RICE Scoring Model: A Comprehensive Guide to Product Prioritization (+Examples)

Hello EdTech Türkiye Readers,

If you work in product management, you know how challenging it can be to decide which ideas, features, or projects should take priority.

While the product team may see a new feature as essential, the engineering team might argue it is too complex and resource-intensive. This is where prioritization frameworks like the RICE Scoring Model help teams make objective and data-driven decisions.

In this article, we’ll explore:
✅ What the RICE model is
✅ How to calculate RICE scores
✅ Real-world examples of prioritization
✅ How it applies to adult learning and education technology

What is the RICE Scoring Model?

The RICE Scoring Model is a decision-making framework designed to help product development teams rank and prioritize ideas, projects, and tasks.

RICE stands for four key factors:

• Reach – How many users will be affected?
• Impact – How significantly will this affect users and business goals?
• Confidence – How certain are we about our assumptions?
• Effort – How much time and resources will it take?

By analyzing time, effort, and impact, teams can focus on high-value, low-effort projects first.

The Origin of the RICE Model

The RICE Scoring Model was developed by Intercom, a software company specializing in customer messaging.

The team at Intercom had previously experimented with other prioritization methods like ICE, MoSCoW, and the Kano Model but found these lacking in precision. They needed a more balanced and comprehensive approach, leading to the development of the RICE framework.

Today, RICE is widely adopted by product teams for effective prioritization.

The 4 Key Factors of RICE

Each letter in RICE represents a different dimension for evaluating a project’s value:

1️⃣ Reach (How many users will be affected?)

• Definition: Measures the number of people or actions impacted within a given timeframe.
• Examples of Metrics:
  • Monthly active users (MAU)
  • Weekly transactions or conversions

✅ Example Calculation:

• A new feature is expected to be used by 1,000 users per week, with a 15% conversion rate over 12 weeks:
• Reach = 1,000 × 0.15 × 12 = 1,800 conversions

2️⃣ Impact (How much impact does this project have?)

• Definition: Assesses the effect on users and business objectives.
• Scoring Guide:
  • 3 = Massive Impact
  • 2 = High Impact
  • 1 = Medium Impact
  • 0.5 = Low Impact
  • 0.25 = Minimal Impact

✅ Example:

• A new subscription model that significantly increases revenue → Impact = 3
• A minor UX fix affecting only a few users → Impact = 0.5

3️⃣ Confidence (How sure are we about our assumptions?)

• Definition: Measures the certainty of data and estimations.
• Scoring Guide:
  • 100% = High Confidence
  • 80% = Medium Confidence
  • 50% = Low Confidence
  • Below 50% = Very Low Confidence

✅ Example:

• A feature tested in previous user feedback → Confidence = 100%
• A new market expansion with little data → Confidence = 50%

4️⃣ Effort (How much time and resources are needed?)

• Definition: The total time required to develop the feature, measured in person-months.
• Scoring Guide:
  • Lower effort = Higher priority
  • Higher effort = Lower priority

✅ Example Calculation:

• 1 week for planning + 1 week for design + 2 weeks for engineering
• Effort = 1 person-month

How to Calculate the RICE Score?

Formula:
RICE Score = (Reach × Impact × Confidence) / Effort

✅ Example Calculation:

• Reach = 1,500 users
• Impact = 2
• Confidence = 50% (0.5)
• Effort = 2 months

RICE Score = (1,500 × 2 × 0.5) / 2 = 750

A higher score means the project has a greater return on investment relative to effort.

Applying RICE to Adult Learning and EdTech Prioritization

Imagine you’re running an educational technology platform and need to decide which learning features to prioritize.

Example RICE Scoring for Education Projects

Results:

✅ Interactive Video Content (5,333 RICE Score) should be the top priority due to its high reach and impact.
✅ Personalized Learning Paths (5,250 RICE Score) may be implemented sooner since it requires less effort.
✅ AI Feedback System (4,725 RICE Score) is valuable but has a lower reach than the others.

Decision Tip:
✅ If quick wins are a priority → Personalized Learning Paths
✅ If long-term engagement is key → Interactive Video Content

Conclusion: How to Prioritize Using RICE?

The RICE Scoring Model helps teams objectively decide which projects to prioritize based on impact vs. effort.

✅ Pros of RICE:
✔ Data-driven decision-making
✔ Reduces bias in prioritization
✔ Balances effort and impact

❌ Challenges of RICE:

• Some values (impact & confidence) are subjective
• Requires time to collect accurate data

By using RICE, product and education teams can align their resources with the highest-impact initiatives.

What’s Your Opinion?

Which education or training feature would you prioritize first? What factors matter most in your decision-making process?

Share your thoughts in the comments!