ICE Scoring | Prioritization Framework Guide [2025]

You’ve got some new ideas, and you’ve built up a good backlog.

The marketing team wants landing page tests, developers suggest performance improvements, and customer support keeps pushing for feature enhancements.

Now it’s time to put some thought into which ones to test first.

Without a structured approach, teams risk pursuing low-impact projects while missing crucial opportunities.

Traditional prioritization methods often lead to endless debates and decisions based on gut feeling.

 The ICE framework offers a simple yet effective solution. It provides an easy way to evaluate and rank ideas, features, or initiatives based on three key factors: Impact, Confidence, and Ease.

In this comprehensive guide, we’ll explain everything you need to know about the ICE prioritization framework, like what is the ICE method, how it’s calculated, why you should use it, and everything in between.

What is the ICE Prioritization Method?

ICE stands for Impact, Confidence, and Ease. ICE model is one of the many prioritization frameworks used for prioritizing feature and product ideas. It’s a lightweight scoring model designed to help teams evaluate and rank different initiatives.

The ICE framework is widely considered to be the original scoring model for growth marketing teams.

It was created by Sean Ellis, the founder of GrowthHackers, when he needed a simple way to evaluate growth experiments at LogMeIn and Dropbox. After witnessing its effectiveness, Ellis shared the framework with the growth community, where it quickly gained popularity.

The ICE method breaks down each initiative into three key components: Impact, Confidence, and Ease. 

The idea is to assign a score or rating (on a scale of 1 to 10) to each of these components based on their potential impact, the level of confidence, and the ease of implementation. The scores are then multiplied to calculate a final numerical score, which helps compare different initiatives objectively.

While there are other prioritization frameworks like the RICE model and the MoSCoW method, the ICE score model stands out for its simplicity. The Kano model might help understand feature satisfaction, but the ICE score makes it particularly valuable for teams that need quick, actionable decisions. 

Its data-driven approach helps cut through subjective opinions and align teams around the high-priority projects to finish first so that they can make data-informed decisions.

Unlike more complex frameworks, ICE can be applied quickly, making it ideal for fast-moving teams that need to evaluate multiple ideas regularly. Growth teams particularly favor ICE because it helps maintain momentum while ensuring efforts are focused on the most promising opportunities.

Why Should You Use the ICE Score Framework?

Product teams often struggle with objective decision-making when faced with numerous options. The ICE framework solves this challenge by providing a structured, yet simple approach to prioritization.

Here’s why the ICE model stands out:

• Quick decision-making: Unlike complex prioritization methods, the ICE model is a relatively quick way to assign values to different potential ideas or projects. This makes it perfect for fast-paced environments where decisions need to be made quickly. This method is particularly great for people in startup environments or innovative workplaces.
• Easy to understand: The best part about the ICE method is that there are only three factors to consider, which makes it easy for team members at all levels to grasp and apply the framework effectively. Simplicity is its biggest selling point and helps product teams narrow things down.
• Flexibility: The ICE model simplifies daily product management struggles and is extremely flexible. Whether you’re prioritizing A/B tests, feature releases, or bug fixes, ICE adapts to various scenarios with ease. This includes relative prioritization for when you’re handling a longer list of things like your backlog.
• Data-informed decisions: The ICE method provides a practical framework for decision-making by evaluating the impact, confidence, and ease of ideas or projects. Whether you’re optimizing your SaaS conversion funnel or launching new features, ICE promotes data-driven thinking by encouraging teams to justify their scores with data-backed evidence and reasoning.

While originally developed for growth experiments, ICE has proven effective for prioritizing various initiatives, from feature development to marketing campaigns and optimization efforts. The ICE model’s versatility and ease of use have made it a staple in product and growth teams’ toolkits.

3 Key Factors of the ICE Score

The ICE scoring model is a brilliant prioritization tool that helps product managers and teams quickly assess different ideas or features based on the three key factors:

Impact

Impact refers to the potential positive outcomes or benefits of an idea or feature. It measures the potential effect of your initiative on key business metrics. It answers one key question, “How much does a feature contribute to your main goal?”

Use a scale of 1 to 10 when scoring impact, where 1 represents minimal impact, and 10 indicates a significant improvement.

When scoring Impact, consider the following:

• Consider key metrics such as conversion rate, feature adoption, net revenue retention, etc.
• Number of users affected
• Strategic alignment with business goals
• Long-term benefits versus short-term gains

For example, a checkout page optimization might score 8 or 9 because it directly impacts conversions, while a minor UI improvement might score 2 or 3.

Confidence

Confidence is how certain you are that the project will have the estimated impact if you make that choice. It can be based on subjective judgments or data-driven evidence. A higher confidence level means you are 100% sure that the idea or feature will work.

On a scale of 1 to 10, your confidence score stems from the same information you use to estimate impact.

Consider these factors when scoring Confidence:

• Available data and evidence
• Past experience with similar initiatives
• Market research and user feedback
• Technical feasibility assessment
• Industry benchmarks and case studies

For instance, a feature repeatedly requested by customers might score higher (let’s say 8 or 9) in confidence, while a new technology that’s still in its infancy stage might score less (3 or 4).

Ease

Ease evaluates the level of effort required to implement the idea or feature. What is the ease of implementation? It represents the effort, resources, and complexity required to complete the project or implement something. It’s a measure of effort to launch the test.

Score it on a scale of 1 to 10, where 1 means extremely difficult and 10 means very easy to execute. The more time and people involved, the lower the score.

When scoring Ease, evaluate the following factors:

• Required resources and time
• Technical complexity
• Development time, cost, and resource availability
• Potential risks and obstacles
• Dependencies on other teams or systems
• Feasibility and practicality of execution
• Testing and validation needs

If it’s something that can be done quickly with minimal effort, you can give it a score of 9 or 10. A complex integration that requires the involvement of more people who need to design or code might score 2 or 3.

How is an ICE Score Calculated?

Each component plays a crucial role in determining the final ICE score, which is calculated by multiplying all three scores together, representing the overall priority. This single numerical value can be used to compare and rank different initiatives.

The ICE score is calculated using a simple formula:

ICE score = Impact × Confidence × Ease

Let’s look at some real-world examples to understand this better.

Suppose you’re trying to implement a single sign-on for your existing product page. Here are the scores:

• Impact score = 8 (will significantly improve enterprise user experience)
• Confidence score = 7 (strong demand from existing customers)
• Ease score = 4 (requires significant development effort)

ICE score = 8 × 7 × 4 = 224

Now, take another feature implementation, let’s say you’re optimizing your SaaS signup pages.

• Impact score = 6 (could improve conversion rate)
• Confidence score = 9 (based on clear analytics data)
• Ease score = 8 (simple form field changes)

ICE score = 6 × 9 × 8 = 432

Looking at both the scares, you can tell the second feature with the highest ICE score will be on first priority. The first feature’s low Ease score dragged its overall ICE score down, so it’s second on the priority list.

How to use ICE scores effectively?

Remember that the ICE scores are meant to guide decisions, not make them for you. It isn’t the perfect method for prioritizing individual ideas. It’s designed to be a system of relative prioritization. The ICE score is not objectively perfect, but it’s enough to get the job done.

Teams can quickly evaluate initiatives while monitoring their SaaS analytics tools for performance data.

It’s helpful to use frameworks like the LIFT CRO Model alongside ICE scoring to ensure a comprehensive analysis of each feature’s potential impact.

Consider these points when using the ICE score for prioritizing ideas:

• Use consistent scoring criteria across all initiatives
• Have a clearly defined main goal 
• Document your reasoning for each score
• Review score as a team to align understanding
• Consider business context, not just numerical values
• Revisit and adjust scores as new information comes to light
• Create a high-quality testing backlog backed by credible data sources

Sometimes you may need to prioritize a lower-scoring initiative due to strategic reasons, which is perfectly fine. Remember the real value of ICE scoring lies in making these trade-offs explicit within your team. The goal is to help you prioritize your efforts and make data-backed decisions.

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• Automated ICE score calculations
• Ready-to-use scoring guidelines
• Priority ranking visualization
• Real-world examples

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ICE Prioritization Framework
Template!

• Streamline decision-making with a proven scoring system
• Prioritize your projects with data-driven confidence
• Save time and focus on what drives the highest impact

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Download

Examples of Using an ICE Prioritization Framework

Now, a little context.

When building and optimizing a SaaS product, teams need to evaluate both major feature developments and smaller optimizations.

Here’s how ICE scoring can help prioritize different types of initiatives:

Product Feature Prioritization

1. Advanced User Permissions System

Impact score = 8 – Critical for enterprise customers, could increase expansion revenue by 40%

Confidence score = 7 – Strong demand in sales calls and customer interviews, already implemented by competitors

Ease score = 4 – Complex development, requires database restructuring

ICE score = 8 × 7 × 4 = 224

2. Custom Report Builder

Impact score = 9 – Data shows reporting is a top feature request, could reduce churn by 15%

Confidence score = 8 – Based on user surveys and competitor analysis

Ease score = 3 – Requires new backend architecture and extensive UI work

ICE score = 9 × 8 × 3 = 216

3. Slack Integration

Impact score = 6 – Would improve workflow for existing teams

Confidence score = 9 – Multiple integration requests, clear technical requirements

Ease score = 8 – Well-documented API, straightforward implementation

ICE score = 6 × 9 × 8 = 432

Experiment Prioritization

1. Onboarding Flow Optimization

Impact score = 7 – Could improve activation rate by 20%

Confidence score = 9 – Clear drop-off points in analytics

Ease score = 8 – Simple UI changes, no backend work needed

ICE score = 7 × 9 × 8 = 504

2. Pricing Page Redesign

Impact score = 8 – Potential increase in conversion rate by 25%

Confidence score = 6 – Based on competitor research

Ease score = 7 – Requires design work but minimal technical changes

ICE score = 8 × 6 × 7 = 336

3. Account Settings Simplification

Impact score = 5 – Could reduce support tickets by 30%

Confidence score = 8 – Based on support ticket analysis

Ease score = 9 – Mostly UI improvements

ICE score = 5 × 8 × 9 = 360

Based on the ICE scores above, the team might prioritize the onboarding flow optimization first, as it ranks higher on the priority list, offering a perfect balance between impact, confidence, and ease of implementation.

The Slack integration feature scores highest despite a lower impact score because of its high confidence and ease scores.

This demonstrates how the ICE score helps teams balance quick wins (like optimizing onboarding flow) with more complex features (like advanced permissions) by providing a consistent framework for comparison.

Remember that while the Slack integration scores the highest, it still can be pushed to a later stage of a product roadmap. Strategic considerations might still prioritize permissions system if enterprise customers are a key business focus. ICE quickly puts the best ideas at the top of the list.

Key Mistakes to Watch Out For

While ICE offers several benefits that make it a handy tool for product development teams, there are some clear downsides to the project scoring model too. We still believe it’s a useful prioritization framework, just be aware of these common mistakes so you can avoid them.

• Solely focusing on subjectivity

Everyone has different ideas of what a high-priority feature looks like. Teams can sometimes score initiatives based on personal opinions or preferences rather than data. For example, a product manager might score their preferred feature higher without supporting evidence.

Solution?

Define your score clearly and work as a team. Use specific metrics, user feedback, or market data to justify each score. It can help teams stay on the same page.

• Inaccurate scoring

Remember that ICE scores are only as good as your estimates. Teams often fall into the trap of using only whole numbers (like 5 or 8) or clustering scores around the middle range. This impacts the effectiveness of the framework.

Solution?

Be specific with your scoring – use decimals if needed. Run the numbers by your team members and don’t be afraid to use the full 1 to 10 range when appropriate.

• Not considering customer feedback

Sometimes teams rely heavily on internal opinions when scoring and they ignore valuable customer insights. The problem with ICE is that it’s not customer-centric, but it should be.

Solution?

Take into account user feedback – link each feature to specific customer feedback when assigning a score. Make sure to incorporate support tickets and customer interviews into your scoring process, especially when evaluating Impact and Confidence.

• Under-emphasizing technical debt

The ICE framework often prioritizes projects based on their potential impact and ease of implementation. When scoring Ease, teams often overlook long-term maintenance costs and technical debt, so such projects end up at the bottom of the ICE priority list. A feature might be easy to implement initially but could create complications later.

Solution?

Consider both short-term development effort and long-term maintenance when scoring Ease. Set aside some time specifically for technical debt within your roadmap. This can help you prioritize features from within each project bucket.

• Inconsistent scoring across teams

Different teams might interpret the ICE scoring criteria differently, which may lead to incomparable scores. They make the mistake of believing that ICE scores are the absolute truth. One team’s 8 might be another team’s 5. Remember that ICE scores are just estimates. You cannot turn approximates into absolutes.

Solution?

Establish clear scoring guidelines and calibrate regularly across teams. Think out of the box and consider factors outside the ICE framework. The main problem with the ICE method is that the scoring process is subjective. Use the scores as a starting point for comparisons.

• Ignoring business strategy

Teams sometimes focus too much on ICE scores without considering broader business objectives. A lower-scoring initiative might be strategically crucial for entering a new market or retaining key customers. Sometimes personal biases are also involved when scoring features, which ultimately impacts your business bottom line.

Solution?

Always evaluate ICE scores within your broader business context. Well, the goal is to get customer/market inputs/insights and align them with your broader business goals to make prioritization decisions.

Final Takeaways on ICE Scoring

The ICE framework provides a simple yet powerful way to assess and rank different ideas or features. By breaking down decisions into Impact, Confidence, and Ease, product teams can move beyond gut feelings and subjective opinions to make more objective decisions.

While the framework isn’t perfect for prioritizing individual ideas, its simple approach makes it an indispensable tool for fast-moving teams that need to make quick, informed decisions.

The ICE model is meant to be a system of relative prioritization. Whether you’re managing growth experiments or product features, ICE can help you align your team around what matters most.

Ready to optimize your product decision-making through data-driven insights?

At Vakulski-Group, we help SaaS companies make better and more informed product decisions using data-backed frameworks like ICE scoring. Our team of experienced CRO specialists and product strategists can help you identify high-impact optimization opportunities, create data-driven growth experiments, and optimize your conversion funnel.

Contact us today to learn how our proven approach can help you prioritize the right initiatives and drive growth.

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