Which Feature Request Prioritization Framework Should You Use? [Top 15]

Choosing the right feature request prioritization framework enables product teams to make informed decisions and deliver the maximum customer value possible, especially when resources are limited. They can also help product managers secure key stakeholder buy-in.

Our guide introduces 15 popular prioritization frameworks along with their pros and cons. It also looks into factors that you need to consider when choosing one.

Let’s dive in.

Feature request prioritization framework summary

• A prioritization framework is a system for ranking feature requests based on set criteria like the value they add.
• The Kano model prioritizes features by dividing them into basics, satisfiers, and delighters.
• The RICE framework weighs the Reach of the features, their Impact, and Confidence level against the Effort needed to build them.
• MoSCoW classifies features into those the that product Must have, Should have, Could have, and Won’t have.
• Story mapping helps teams prioritize features in the context of the user journey.
• Opportunity scoring helps teams identify features that users consider important but are not satisfied with.
• The Value vs Effort matrix considers the positive impact of the feature against the resources and time needed to deliver it.
• Product tree is a visualization tool for presenting the hierarchy of features.
• In the Cost of Delay technique, teams prioritize features based on how much it costs the company not to have the feature.
• Buy a feature is a prioritization game in which participants spend money on features they find most valuable.
• Priority poker is a collaborative game where participants try to reach a consensus on how important the feature is.
• The ICE scoring model is a simplified version of the RICE feature request prioritization framework. It focuses on Impact, Confidence, and Ease.
• The Opportunity Solution Tree (OST) is a tool for visualizing the interdependencies between business goals, user pain points, and features.
• The KJ method is a collaborative prioritization method involving feature classification and voting.
• The Urgent vs. Important Matrix is based on the same principle as Value vs. Effort or Opportunity scoring.
• In the MoAR method, teams consider how well a feature helps achieve a product goal and the resources it requires.
• To decide which prioritization framework is right for you, consider important factors, like the product management stage and the time available to create the feature.
• Once features have been prioritized, ensure to validate them, create a feature roadmap, and collect feedback for iterative testing.
• To see how Userpilot can help you prioritize and validate features, book the demo!

What is a feature prioritization framework?

A prioritization framework is a system that product teams use to rank feature requests and product motions in their backlog.

The system is normally based on processes and a set of criteria that are often weighed against each other. For example, apart from the value the feature brings, you also need to look at the effort or resources it requires to build.

15 Common methods to prioritize feature requests

Let’s check out 15 popular frameworks you could use for prioritizing feature requests and investigate their pros and cons.

1. Kano model

The Kano Model is one of the best-known prioritization frameworks.

When applying the Kano Model, you divide your feature requests into 3 categories:

• Basic features, aka Threshold features – the core features that you would include in your MVP. They are essential – if they’re missing, the product won’t meet its goals.
• Performance features, aka Satisfiers – these features aren’t essential, but they increase customer satisfaction. The more of them your product has, the happier your customers are.
• Excitement features, aka Delighters – the features exceed users’ expectations and give them extra joy. They may not be essential or improve product performance, but they capture the users’ imagination and differentiate your product from the competition.

Pros and Cons

✅ Focus on customer needs and satisfaction.

✅ Helps prioritize painkillers over vitamins.

❌ Very general, doesn’t allow for prioritization within the categories.

❌ Time-consuming as requires extensive customer surveys.

2. RICE framework

RICE is a prioritization framework developed by Intercom.

The acronym stands for:

• Reach: how many customers will benefit from the potential features?
• Impact: quantifiable impact on customers or the business, for example, lower churn rate.
• Confidence: how confident are you the feature will have the planned impact on customers after investing the estimated effort you put into it?
• Effort: the resources necessary to realize the feature request.

To prioritize feature requests, the team scores them along each dimension using predefined values. Next, they multiply the Reach by Impact and Confidence and divide the total score by the Effort.

Pros and Cons

✅ Objective as it uses quantitative data.

❌ It’s difficult to estimate each of the values accurately.

3. MoSCoW model

MoSCoW is an acronym for

• Must have’s: the essential features, basics
• Should have’s: the performance features
• Could have’s: optional, delivered if time and resources allow
• Won’t have’s: not going to be included

Just like the Kano Model, it’s useful in the early days of product initiatives.

Pros and Cons

✅ Quick, easy, and intuitive.

❌ More suitable for scoping waterfall projects than agile product development.

❌ Very general and doesn’t provide tools for prioritization within each of the categories.

4. Story mapping

Story mapping is a visualization technique that enables the product team to get a clear view of dependencies between all the features that make up the product.

To create a story map, you start by outlining the user journey. Next, you identify all the touchpoints and corresponding tasks or activities that users will perform phrased as user stories. Keep breaking them down until they can be completed within one sprint.

Once you have the stories mapped out, prioritize them using pre-defined criteria, like impact or business value.

Pros and Cons

✅ Focuses on user experience.

✅ Easy and quick method to identify the MVP features.

❌ Story mapping can be time-consuming to start with.

5. Opportunity scoring

Opportunity scoring is a customer-centric technique that helps you identify features that users find important but are dissatisfied with.

To apply it, start by asking your users two questions:

• On a scale from 1-10, how important is the particular feature/outcome?
• On a scale from 1-10, how satisfied are you with the feature?

Next, plot the features in a chart where the X-axis stands for Importance while the Y-axis stands for Satisfaction. In this way, you will be able to identify which of the features are underserved and require more attention.

Pros and Cons

✅ Prioritizes customer value.

✅ Simple and quick to implement.

❌ Depends on the accuracy of customer feedback.

❌ Different user segments can provide very different scores for the same feature.

6. Value vs effort

The Value vs Effort matrix is similar to Opportunity scoring as it also uses two main criteria.

However, it looks at the features from the perspective of the organization rather than the customer. Instead of satisfaction levels, it considers the effort required to deliver the feature.

The principle is simple.

To start with, score each feature along both dimensions on a scale, say 1-10. Next, plot the features in the graph. In this way, you can classify features into 4 categories:

• Low value/low effort – fill-ins, built when there’s nothing else to do
• Low value/high effort – time slinks to get rid of asap
• High value/low effort – low-hanging fruit to pick first
• High value/high effort – big projects requiring considerable resources but worth it

Pros and Cons

✅ Helps to categorize features into actionable groups.

✅ Provides clear and easy-to-interpret visualization.

❌ Very simplistic and general classification along two dimensions only.

❌ Scoring can be subjective.

7. Product tree

A product tree is a visualization technique for prioritizing features based on customer needs.

How does it work?

Different parts of the tree will represent different features. The trunk is the core functionality, the roots are the technical requirements, the outermost branches depict the feature categories, and the leaves represent the future features.

Customers are invited to place their feature requests on the tree. In this way, you will be able to determine how important they are in reference to one another and prioritize or deprioritize their development accordingly.

Pros and Cons

✅ Facilitates the involvement of customers/stakeholders.

✅ Helps to determine feature importance in the product context.

❌ Not very precise.

8. Cost of Delay

In the Cost of Delay technique, the feature value is the key prioritization factor.

However, instead of concentrating on the value that the feature brings, it looks at how much it costs you not to have the feature. The higher the cost of delay, the sooner you should build the feature.

Pros and Cons

✅ Focuses on the financial impact, which matters a lot to many organizations.

❌ Ignores other factors, like customer satisfaction.

❌ Cost estimates may be inaccurate.

9. Buy a feature

Buy a feature is a prioritization game that you can use to gauge how much the feature is worth to its users.

How does it work?

Start by assigning monetary value to the features in the backlog based on the money and time it will cost to build them.

Next, gather a group of key internal stakeholders, customers, or product team members. Give each of them a fixed amount of cash to spend on the features they like. Finally, prioritize the features based on how much the participants are ready to pay for them.

Pros and Cons

✅ Engaging and collaborative.

✅ Involves customers.

❌ Difficult to collect all stakeholders in one place at the same time.

10. Priority poker

Priority poker is a prioritization technique popular with Agile teams.

During the game of poker, each team member gets a deck of cards with numerical values. Say 1 to 5, 1 being very low priority, and 5 being very high priority.

Next, the team considers all the feature requests one by one. For each of them, the team members individually choose one card and reveal them all at once.

The person with the lowest and highest score gets a chance to justify their scores, which acts as a springboard to the team discussion. Having considered all the views, the team settles on the final value for the feature.

Pros and Cons

✅ Encourages discussion and consensus-building among team members.

❌ Can be time-consuming.

❌ Works only for small teams.

11. ICE scoring model

The ICE scoring model was developed by Sean Ellis (the PMF survey guy) and it’s a simplified variation of the RICE framework.

It uses 3 criteria instead of 4: Impact, Confidence, and Ease.

You rate each feature along the 3 dimensions by assigning them a value on a scale of 1-10 and calculate the average. The higher the average, the higher the feature request ends up in the backlog.

Pros and Cons

✅ Easy and intuitive.

❌ Depends on subjective scoring and may not capture the full complexity of the features.

❌ Assumes equal weightage of the three prioritization factors.

12. Opportunity solution tree

The Opportunity-Solution Tree (OST) is a visualization tool rather than a prioritization framework. It helps teams map out the possible features so that they can prioritize them more easily.

The tree consists of 4 levels:

• Outcome (business goal)
• Opportunities (user problems, needs, or desires)
• Solutions (features that address specific opportunities)
• Experiments (tests that help you validate the solutions)

To draw the OST, you start by defining the business goal you want to achieve and identify opportunities that will help you achieve it. For every opportunity, you brainstorm different solutions. Finally, you identify ways to validate how well the solution addresses the opportunity.

Teresa Torres, who developed the tool, recommends starting the prioritization process from the opportunities and only then moving on to ideating and prioritizing the solutions.

Pros and Cons

✅ Helps ensure alignment between business/product goals and features.

✅ Clear and easy to interpret. Perfect for communication with non-tech stakeholders.

❌ Not really a prioritization tool.

13. KJ method

The KJ method is a collaborative prioritization technique that encourages team members to identify dependencies between features.

Here are the steps:

1) List all feature requests on separate sticky notes.

2) Ask each group member to pick two that they think belong together.

3) Ask the participants to organize all the requests into logical groups and label them.

5) Each participant has 6 votes and must use them on 3 different groups (3-2-1).

Pros and Cons

✅ Encourages collaboration and communication between team members and stakeholders.

❌ Relies on subjective scoring.

14. Urgent vs. Important Matrix

The Urgent vs Important Matrix is similar to Opportunity scoring or Value vs Effort.

The team scores feature requests according to their importance and urgency. As a result, the features end up in one of 4 buckets:

• Urgent/Important – do now
• Not urgent/Important – schedule to do later
• Urgent/Not important – delegate
• Not urgent/Not important – don’t bother

Pros and Cons

✅ Helps to categorize features into actionable groups.

✅ Provides clear and easy-to-interpret visualization.

❌ Very simplistic and general classification along two dimensions only.

15. The MoAR method

The acronym MoAR stands for Metrics over Available Resources. It is a quantitative prioritization method ranking features based on their forecast contribution to the product goal and the resources it requires.

Here’s how it works:

• Choose a goal, e.g. ‘Improve customer satisfaction by 20%’
• List features that will help you achieve the goal
• In percentages, determine how much each of them will contribute to the goal
• Decide how many weeks it will take to deliver each feature
• Calculate MoAR by dividing the percentages by the number of weeks
• Prioritize features with the highest score

Pros and Cons

✅ Provides a clear ranking based on quantitative data.

✅ Considers both the impact and the feasibility of the options.

❌ Relies on accurate forecasting and estimation, which are usually very challenging.

How to choose the right feature request prioritization framework?

Which of the above framework you choose will depend on a number of factors.

Some of them include:

• The stage in the product management process.
• How quickly you have to make the decision.
• Who is available or needs to be included in the process.
• The organizational culture and internal processes.

For example:

• An organization that focuses on customer satisfaction is more likely to use a framework like Kano, while Value vs Effort will be more appealing to companies that prioritize business goals.
• To make a quick decision within the team, the Cost of Delay will be more suitable than the KJ method because it doesn’t require the involvement of stakeholders.

What should product teams do after they prioritize features?

Prioritizing the feature requests effectively is just the beginning of the work. The feature success depends a lot on what you do afterward.

Validate product features to gauge user interest

If the feature was requested by the customers and they were involved in the prioritization process, you may assume it’s safe to build it.

But what if the feature was requested only by a select few power users, and not a representative sample of the user base?

To avoid wasting resources on failed initiatives, make sure to validate the feature. Engage different user segments, not just innovators or early adopters, and use prototypes to ensure the feature solves genuine user problems and will actually enhance their experience.

Create a product roadmap of prioritized features

Once you validate the feature, it’s time to include it in the product roadmap.

This should be pretty straightforward because if you’re looking at feature requests from existing customers, you probably already have a product roadmap in place. The prioritization doesn’t happen in a vacuum and all features are considered in the context of the existing functionality.

Consequently, all you have to do is adjust the timelines for other features that may be delayed as a result.

Iterate on features based on customer feedback

Once you build the feature, make sure to collect user feedback, for example via in-app surveys.

It’s good practice to trigger the surveys contextually, just when the customer has used the feature. In this way, the experience is still fresh in their minds and they’re more likely to respond in the first place.

It goes without saying that you should close the feedback look and use the customer insights to inform future iterations.

Conclusion

Using a prioritization framework to rank feature requests allows a product manager to make decisions in a structured and consistent way. This improves the chances of building features that truly enhance the user experience.

If you want to see how you can use Userpilot to collect feature requests, validate them, and manage customer feedback, book the demo!