RICE Prioritization: Reach, Impact, Confidence, Effort With Examples

By Tara Minh · Updated Oct 10, 2026

RICE prioritization is a scoring model that ranks projects by four factors: Reach (how many people it touches), Impact (how much it moves each of them), Confidence (how sure you are of those estimates), and Effort (how much team time it costs). You multiply the first three, divide by Effort, and build the highest scores first.

Key Facts

• RICE was introduced by Sean McBride in a January 2018 post on the Intercom blog, written for product managers choosing between competing projects.
• Intercom's Impact scale has five values: 3 (massive), 2 (high), 1 (medium), 0.5 (low), and 0.25 (minimal).
• Intercom's Confidence scale has three tiers: 100% (high), 80% (medium), and 50% (low). Anything below 50% is described in the post as a "total moonshot."
• Effort is counted in person-months, meaning the work one team member can do in a month.
• The score is read as total impact per unit of time worked.

What is RICE prioritization?

Every team has more ideas than capacity. The hard part isn't generating options, it's choosing between a pet project from a senior stakeholder, a small fix customers keep asking for, and a big bet nobody has validated. Gut feel loses those arguments to whoever speaks loudest.

RICE gives the conversation a shared structure. Each project gets scored on the same four factors, so you compare like with like. The name is the acronym:

• Reach: how many people or events the project affects in a set time period.
• Impact: how much it changes things for each person it reaches.
• Confidence: how much evidence backs your Reach and Impact estimates.
• Effort: how much total team time it takes.

In the original post, Sean McBride describes the four factors and the scales his team uses. This page uses those scales exactly as Intercom states them, then shows how to adapt the model to work outside of product teams.

The RICE formula

The formula divides the benefits by the cost:

RICE score = (Reach x Impact x Confidence) / Effort

Reach, Impact and Confidence sit on top because they multiply together to estimate value. Effort sits underneath because every extra person-month of work dilutes that value. The result is, in Intercom's framing, the total impact per time worked. A higher number means more return for each month your team spends.

Reach

Pick one time period and one unit, then use them for every project on the list. Intercom's example question is how many customers a project will affect in a single quarter. The unit can be customers per quarter, transactions per month, or tickets per week. What matters is consistency.

Estimate Reach from real numbers when you can: analytics, CRM counts, support ticket volume. If a signup step is seen by 500 customers a month and 30% of them choose a given option, a project touching that option reaches 150 customers a month, or 450 over a quarter.

Impact

Impact measures the effect on each person reached, not on the business overall. Intercom asks how much a project will move a goal (for example, conversion rate) when a customer encounters it. Because that's hard to measure precisely, Intercom uses a multiple-choice scale:

Pick the one goal you care about this cycle (activation, retention, revenue) and score every project against it. If different projects target different goals, the scores stop being comparable.

Confidence

Confidence is the honesty check. It discounts projects where you're guessing. Intercom's scale:

Intercom calls anything under 50% a "total moonshot." Confidence is also where the model protects you from your own enthusiasm. A flashy idea with a 50% rating loses half its score immediately.

Effort

Effort is total team time across everyone involved (product, design, engineering, and anyone else who touches the work), counted in person-months. Intercom uses whole numbers, with 0.5 for work that takes well under a month. Don't chase false precision here. If your team already sizes work with story points or T-shirt sizing, convert those into person-months once and reuse the mapping.

RICE worked example

The numbers below are illustrative, invented to show the mechanics. They aren't benchmarks. Imagine a small product team choosing among four projects for next quarter. Reach is customers per quarter, and Impact and Confidence use Intercom's scales.

Here's how Project A scores: 4,000 x 1 x 0.8 = 3,200, divided by 2 person-months = 1,600.

A few things stand out. The onboarding checklist wins even though its Impact is only a 1, because it reaches the most people and costs little. The dashboard has the best evidence (100% confidence) and a strong Impact of 2, yet it ranks third because it costs four person-months. Project B has the highest per-person Impact, but a 50% Confidence rating halves it. That's a signal to run a cheap test before committing, not necessarily to drop it.

Notice what the score doesn't do. It doesn't tell you to build A, then B, then C, then D in strict order. Dependencies, deadlines, and strategy still matter. The score is an input to the decision, and its main job is to expose which assumptions are carrying the most weight.

RICE vs other prioritization frameworks

RICE isn't the only way to rank work. The right choice depends on how much data you have and who's in the room.

SAFe describes WSJF as relative cost of delay divided by relative job duration, with cost of delay built from user and business value, time criticality, and risk reduction or opportunity enablement, as laid out in the SAFe WSJF guidance. RICE and WSJF share the same cost-benefit shape. The difference is that RICE adds an explicit Reach number and a Confidence discount, while WSJF adds time criticality.

A practical pairing: use MoSCoW to decide what's in scope for a release, then use RICE to order the items inside the Must and Should buckets.

How to use RICE prioritization step by step

1. List the candidates. Pull items from your product backlog or portfolio list. Keep each one specific enough to estimate, and group tiny tasks together.
2. Agree on the goal and the time window. Choose the one outcome to score Impact against, and the period for Reach (a quarter works for most teams).
3. Define your scales before scoring. Adopt Intercom's Impact and Confidence scales, or write down your own. Write down what a 3 means in your context.
4. Score Reach from data. Use analytics, CRM exports or ticket counts. If you have no data, note it and lower Confidence.
5. Score Impact and Confidence as a group. Have two or three people score independently, then compare. Large gaps point to hidden assumptions worth discussing.
6. Estimate Effort with the people doing the work. The people who'll build it should give the number, not the people who want it.
7. Calculate and sort. Multiply, divide, rank. Keep the spreadsheet visible.
8. Sanity-check the top and bottom. If a result feels wrong, find out which input is driving it. Fix the input, not the formula.
9. Review each cycle. Scores go stale as data changes. Re-score during backlog refinement rather than treating the first ranking as permanent.

RICE scoring template

Copy this table into a spreadsheet and add a formula in the last column. The sample row is illustrative.

In a spreadsheet, the score cell is =(D2*E2*F2)/G2 if Reach is in column D, Impact in E, Confidence in F (formatted as a percentage) and Effort in G. Add a dropdown on the Impact and Confidence columns so people can only pick values from the scale.

RICE examples by business function

RICE came from product teams, but the logic works wherever you're choosing between projects. Adjust what Reach means and keep the rest. The figures below are illustrative.

Product. Reach is active users affected per quarter. A project to fix a confusing export screen might reach 1,800 users with Impact 1 at 80% confidence and 1 person-month of work, scoring 1,440.

Marketing. Reach is the audience a campaign or page will reach. Rewriting the highest-traffic comparison page might reach 12,000 visitors a quarter, with Impact 0.5 on conversion, 80% confidence and 0.5 person-months: 9,600. A brand video reaching 50,000 people at Impact 0.25, 50% confidence and 3 person-months scores about 2,083, which shows how the model weighs cheap, evidence-backed work against expensive guesses.

Sales ops. Reach is the number of reps or deals affected. Automating lead routing might touch 40 reps and about 600 leads a quarter. Use leads as the unit, give it Impact 2, 80% confidence and 2 person-months, and the score is 480. Compare that against a CRM field cleanup project on the same unit rather than mixing units.

HR. Reach is the number of employees or hires affected. Streamlining the new-hire paperwork flow for 150 hires a year (about 38 a quarter) at Impact 2, 100% confidence and 0.5 person-months scores 152. A manager training program for 60 managers, Impact 3, 50% confidence and 4 person-months, scores about 22.5. The small number reflects a smaller Reach, so some HR teams set Reach as employees affected and accept lower absolute scores, comparing only within HR.

IT. Reach is the number of staff or systems affected. A single sign-on rollout for 400 employees at Impact 2, 80% confidence and 3 person-months scores about 213. Patching a legacy tool used by 15 people at Impact 1, 100% confidence and 0.5 person-months scores 30. At a portfolio level, you might feed the winners into project portfolio management to check they fit overall capacity.

One caution: only compare scores built on the same Reach unit and time window. A product score in customers and an HR score in employees don't belong on one list.

RICE dos and don'ts

Do:

• Use the same scales and time window for every item in a scoring round.
• Base Reach on data wherever you can, and lower Confidence where you can't.
• Let the people doing the work estimate Effort.
• Treat the scoring discussion as the real value. The disagreements show where assumptions differ.
• Re-score when new data arrives, especially after a test result.
• Pressure-test the top few items by asking how each could fail before committing.

Don't:

• Don't tweak numbers until your favorite project wins. If you need a project to rank first, say so and decide openly.
• Don't treat a 1,600 as meaningfully better than a 1,500. Scores are rough, and small gaps are noise.
• Don't score tiny tasks. The overhead isn't worth it.
• Don't mix goals. Impact on revenue and impact on morale can't share a scale.
• Don't let low Effort alone drive the ranking. Cheap, low-value work can crowd out important projects.
• Don't ignore dependencies, legal deadlines or strategic bets. RICE doesn't model them.

Limitations of RICE

RICE multiplies estimates, and errors multiply too. If Reach is off by 2x and Impact is off by 2x, the score can be off by 4x. Early-stage estimates deserve the widest error bars.

The model also favors broad, shallow improvements over deep ones for small segments. A critical feature for your ten biggest customers can score poorly on Reach. If that matters strategically, handle it outside the model or add a separate weighting.

Finally, it's easy to add false precision. Using the five-value Impact scale helps, since it stops people from debating whether something is a 1.4 or a 1.6. If scoring sessions drag on, cap each item at a couple of minutes.

Putting RICE to work

Start small. Take the ten items sitting at the top of your backlog, agree on a goal, score them as a group in under an hour, and look at the top three and the bottom three. The ranking will probably confirm some instincts and challenge others. Either way, you'll have a written reason for what you build next, which is worth more than the score itself.

Related reading

• MoSCoW Method
• Product Backlog
• Backlog Refinement
• Story Points
• T-Shirt Sizing
• Project Portfolio Management
• Scaled Agile Framework (SAFe)