You've launched your SaaS, set up your customer feedback boards, and now the requests are pouring in. Sales wants one thing, Marketing wants another, and your loudest customer is threatening to churn if you don't build their pet feature.
How do you decide what to build next?
Enter the RICE framework for prioritization — a scoring system designed by Intercom to help product teams make objective, data-driven decisions instead of relying on gut feelings.
What is the RICE Framework?
RICE is an acronym for the four factors you use to evaluate a project or feature request: Reach, Impact, Confidence, and Effort.
By assigning a number to each of these four factors, you generate a single "RICE Score" that allows you to compare completely different types of projects against each other fairly.
The Four Components of RICE
1. Reach
How many users will this feature affect in a given time period?
Reach removes the bias of the "loudest customer." If an enterprise client demands a feature, but it only helps 5 users, the Reach is 5. If a minor UX tweak helps every single active user log in faster, the Reach might be 5,000.
- Example: 5,000 users per month
- Metric: Actual numbers (users, transactions, events)
2. Impact
If someone encounters this feature, how much will it move the needle?
Impact is hard to quantify, so the RICE framework uses a standardized multiple-choice scale:
- 3 = Massive impact (Will directly prevent churn or close new deals)
- 2 = High impact
- 1 = Medium impact
- 0.5 = Low impact
- 0.25 = Minimal impact
3. Confidence
How sure are you about your Reach and Impact estimates?
Product managers are notoriously optimistic. The Confidence score penalizes ideas that sound good but lack data.
- 100% = High confidence (You have quantitative data, like 200 upvotes on a feature request board)
- 80% = Medium confidence (You have some qualitative data from user interviews)
- 50% = Low confidence (Gut feeling or an educated guess)
Note: Anything below 50% means you need to do more research before prioritizing the feature.
4. Effort
How much time will this take from the whole team?
Effort is the denominator in the equation. It represents the total amount of time required from product, design, and engineering.
- Metric: "Person-months" (How much work one person can do in a month)
- Example: A project taking 2 engineers 2 weeks each = 1 person-month of Effort. A quick weekend fix = 0.1 Effort.
The RICE Formula
Calculating your final score is simple:
RICE Score = (Reach × Impact × Confidence) / Effort
A Real-World SaaS Example
Let's say you're debating whether to build an Intercom Integration or a Dark Mode for your SaaS app.
Option A: Intercom Integration
- Reach: 500 users (Only 10% of your user base uses Intercom)
- Impact: 3 (Massive impact — these are your enterprise users)
- Confidence: 80% (You've interviewed several of them)
- Effort: 2 person-months (Complex API work required)
- Calculation: (500 × 3 × 0.8) / 2 = 600 RICE Score
Option B: Dark Mode
- Reach: 5,000 users (100% of your user base)
- Impact: 0.5 (Low impact — it's just a visual preference)
- Confidence: 100% (You have 150 upvotes on your feedback board)
- Effort: 0.5 person-months (Just CSS changes)
- Calculation: (5000 × 0.5 × 1.0) / 0.5 = 5,000 RICE Score
Despite the Intercom integration being a "massive impact" feature, the RICE score clearly shows that spending half a month on Dark Mode delivers higher cumulative value to your user base.
3 Tips for Using RICE Successfully
1. Don't Be a Slave to the Score
RICE is a compass, not a GPS. If a feature scores low but is critical for a strategic partnership or compliance (like GDPR), build it anyway. The score is meant to start conversations, not end them.
2. Connect RICE to Your Customer Feedback
The hardest part of RICE is calculating the Confidence score. The easiest way to get 100% confidence is by hooking your prioritization framework directly to a customer feedback tool. When a feature has 300 upvotes, your Confidence score is mathematically validated.
3. Share the Results on Your Public Roadmap
Transparency builds trust. When users ask why their pet feature hasn't been built yet, showing them how you prioritize based on total user impact stops arguments in their tracks. A public roadmap gives them visibility into exactly what made the cut.
Ready to Streamline Your Prioritization?
If you're tired of guessing what to build next, feedto.me combines feedback collection, voting, and roadmapping into one platform — unlike point solutions like Canny — so you always have the data you need to calculate perfect RICE scores.