RICE vs ICE: Which Prioritization Framework Should You Use?

Choosing the right prioritization framework can make or break your product development process. Two of the most popular methods—RICE and ICE—share similar DNA but serve different purposes.

In this guide, I'll break down both frameworks and help you decide which one fits your team best.

Quick Comparison

What is RICE?

RICE is a prioritization framework developed by Intercom's product team. It evaluates features based on four factors:

• Reach – How many users will this affect in a given time period?

• Impact – How much will this move the needle on your goals?

• Confidence – How certain are you about your estimates?

• Effort – How much time/resources will this take?

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

The key differentiator is the Reach factor, which quantifies how many people a feature will actually impact. This makes RICE particularly useful when you have solid user data.

What is ICE?

ICE was created by Sean Ellis, the growth hacking pioneer. It's a simpler framework with three factors:

• Impact – How much does this help achieve your goals?

• Confidence – How sure are you this will work?

• Ease – How easy is it to implement? (inverse of effort)

Formula: ICE Score = Impact × Confidence × Ease

ICE was designed for rapid experimentation. When you're running lots of growth experiments, you need to prioritize quickly without getting bogged down in data collection.

The Key Difference: Reach

The fundamental difference between RICE and ICE is the Reach factor.

Why Reach Matters

Consider two features:

• Feature A: Improves checkout flow (affects 100% of customers)

• Feature B: Adds export to CSV (affects 5% of customers)

With ICE, if both features have similar Impact and Ease scores, they might rank equally. But with RICE, Feature A would score much higher because it reaches more users.

When Reach Changes Everything

Reach becomes critical when:

• You have a large, diverse user base

• Different features serve different user segments

• You're building a consumer product with varying user behaviors

• You have good analytics data on user numbers

When Reach Doesn't Matter

Reach is less important when:

• All features affect the same user group

• You're building for a small, homogeneous audience

• You're running quick experiments

• You don't have reliable user data yet

RICE vs ICE: Pros and Cons

RICE Pros

• More accurate for products with large, segmented user bases

• Forces you to think about actual user impact

• Better for data-driven organizations

• Helps avoid building features for vocal minorities

RICE Cons

• Requires reliable reach data

• More time-consuming to calculate

• Can be overkill for small teams or early-stage products

• Reach estimates can be difficult to determine

ICE Pros

• Quick and easy to use

• Great for rapid experimentation

• Requires minimal data

• Easy to get team buy-in

• Perfect for growth hacking sprints

ICE Cons

• Doesn't account for user reach

• May lead to building features for small user segments

• Less precise than RICE

• All factors weighted equally

When to Use RICE

Choose RICE when:

1. You have user data – You can estimate how many users will be affected

2. You're building a consumer product – Where different features serve different user segments

3. You have time for analysis – Your planning cycles allow for deeper evaluation

4. Reach varies significantly – Some features affect thousands, others affect dozens

5. You're making strategic decisions – Major features that will shape your roadmap

When to Use ICE

Choose ICE when:

1. You're moving fast – Running weekly or bi-weekly experiments

2. You lack user data – You're early-stage or don't have good analytics

3. All users are similar – Your features affect the same user base equally

4. You're doing growth experiments – Testing many small hypotheses

5. You need quick decisions – No time for detailed analysis

Can You Use Both?

Absolutely. Many teams use both frameworks for different purposes:

• RICE for roadmap planning – Quarterly or monthly feature prioritization

• ICE for experiments – Weekly growth experiments and quick wins

This hybrid approach gives you the best of both worlds: strategic rigor for big decisions and speed for tactical experiments.

Making the Switch

Moving from ICE to RICE

If you're currently using ICE and want more precision:

1. Start tracking reach data for your features

2. Build a baseline of user metrics

3. Run RICE alongside ICE for a quarter

4. Compare results and refine your estimates

Moving from RICE to ICE

If RICE feels too heavy for your needs:

1. Drop the Reach factor

2. Convert Effort to Ease (invert the scale)

3. Simplify your scoring scales

4. Speed up your prioritization meetings

Tools for Both Frameworks

We offer free calculators and templates for both frameworks:

RICE Resources:

• RICE Calculator

• RICE Excel Template

• RICE Google Sheets Template

• Apply RICE in ProductLift

ICE Resources:

• ICE Calculator

• ICE Excel Template

• Apply ICE in ProductLift

The Bottom Line

Both RICE and ICE are solid frameworks. The right choice depends on your context:

• Choose RICE if you have user data and want more precision

• Choose ICE if you need speed and simplicity

The best framework is the one your team will actually use consistently. Start simple with ICE, and graduate to RICE when you have the data and need for it.

Ready to put these frameworks into practice? Try ProductLift's prioritization feature to score, rank, and roadmap your features—whether you prefer RICE, ICE, or any other framework.