Prioritize feature requests without asking people 'what they want'

A user-centric way to prioritize features without sacrificing time and quality

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Hello, Curious PwDR!

Asking users what they want often leads you down the wrong path. Henry Ford once said, “If I had asked people what they wanted, they would have said faster horses.” People are notoriously bad at predicting what will actually solve their problems. So, instead of asking them outright, you need frameworks that allow you to understand what they need and focus on delivering high-value features in the shortest possible time.

This article will show you exactly how to do that, using frameworks like Opportunity Gap Analysis and Pairwise Comparison to prioritize feature requests in a user-centric way without sacrificing quality or burning through your development time.

Step 1: Understand the problem, not the solution

Users can describe the symptoms of a problem but rarely provide the right solution — they aren’t designers, after all. So, when a feature request comes in, your first job is to identify the underlying issue it’s trying to solve.

For instance, if your users ask for a search feature in your app, they’re not really saying they want to search. What they’re telling you is that they’re struggling to find what they need. Your job is to figure out the root cause of their frustration.

• Listen carefully to requests by digging deeper and asking why. Why do they need this feature? What are they struggling with? Keep peeling the layers until you uncover the real problem.

• If possible, observe users interacting with your product. You may find that their problem could be solved in a more straightforward way than building an entirely new feature.

Once you understand the real problem, move to the next step.

Step 2: Use the Opportunity Gap Analysis to identify high-impact features

Opportunity Gap Analysis is a powerful framework that helps you prioritize features based on how much value they provide to users versus how difficult they are to implement. It’s the perfect tool to ensure that you’re focusing on features that will make the biggest difference to your users with the least amount of effort.

Here’s how to get started:

1. Break down the steps a user takes when interacting with your product. Identify pain points or areas where the user experience falls short. These are your opportunity gaps.

2. Once you’ve identified these gaps, evaluate the impact of closing them. How much will improving this part of the product help users achieve their goals? The bigger the impact, the higher the priority.

3. Look at the technical difficulty of implementing each solution. Some fixes might require a complete overhaul, while others might be quick adjustments. Rank features based on effort and group them into easy wins versus complex projects.

4. Now that you’ve mapped out the opportunities and evaluated both the impact and the effort, it’s time to prioritize. First, focus on features with a large gap (high user value) and low effort. These quick wins will build momentum and show your users that you’re making progress.

Opportunity Gap Analysis in action

B2B example:

Your B2B customers are complaining about the time it takes to onboard new team members in your enterprise software. You might be tempted to build an entirely new onboarding wizard.

However, through Opportunity Gap Analysis, you discover that simplifying the current permission settings (which are confusing) would speed up the onboarding process significantly, solving their problem faster.

B2C example:

Your online grocery app users want more personalized recommendations. Rather than developing an advanced recommendation engine from scratch, you realize that reorganizing the product categories and making the search process easier would quickly improve their ability to find relevant products, providing immediate value.

Use opportunity gap analysis to focus on solving the biggest problems for your users with the least amount of effort. This helps you prioritize high-impact features without sinking too much time or sacrificing quality.

Step 3: Evaluate feature requests with Pairwise Comparison

Once you have a list of potential features or improvements, it’s time to evaluate them. Pairwise comparison is a method that helps you rank feature requests by comparing them against each other, two at a time. This is useful when you have several competing priorities and need to determine which one should come first.

1. Write down every request you’ve identified as a potential priority.

2. Look at two features side by side and ask yourself: “If I could only implement one, which one would deliver more value?” Repeat this process for every possible pair of features.

3. After all the pairwise comparisons, you’ll have a clear ranking of which features are the highest priority. These are the ones you should focus on first.

Pairwise comparison forces you to make trade-offs and helps you see which features will provide the most value relative to one another. By doing this, you avoid the trap of treating every feature request as equally important.

Pairwise Comparison in action

B2B example:

You’re deciding between three feature requests for your collaboration software:

1. Single sign-on (SSO) integration

2. Automated status updates

3. Task priority labels

By doing a pairwise comparison, you decide that SSO integration should come first, as it simplifies access management for large corporate clients. Next, you prioritize task priority labels since they would improve daily workflows. Automated status updates are ranked last because they offer the least immediate value.

B2C example:

You’re deciding between three feature requests for your online food delivery app:

1. Real-time driver tracking

2. Restaurant wait times

3. A rating system for drivers

After comparing, you decide that real-time driver tracking is most important since it directly reduces customer anxiety. Restaurant wait times come next because they help users manage expectations. The driver rating system ranks last since it’s a “nice-to-have” and doesn’t significantly impact the experience.

Step 4: Score features with a RICE framework

If you’re dealing with a lot of feature requests and need a more structured approach, try using the RICE framework to score each feature based on four factors:

1. Reach: How many users will this feature impact?

2. Impact: How much will this feature improve the user experience?

3. Confidence: How sure are you that this feature will deliver the expected impact?

4. Effort: How much time and resources will it take to implement?

Scoring example:

Let’s say you’re considering adding a dark mode to your mobile app. You estimate that dark mode will affect 50% of your user base (reach), significantly improve the user experience for those users (impact), and work well (confidence). However, implementing dark mode will require a lot of development work (effort).

You give it the following scores:

• Reach: 8 (50% of users)

• Impact: 7 (improves user experience significantly)

• Confidence: 8 (you’re sure this will be a hit)

• Effort: 5 (it’s a big project)

Your RICE score for dark mode is:

(8 × 7 × 8) ÷ 5 = 89.6

Now, compare this score to other feature requests and prioritize accordingly.

RICE Framework in action

B2B example:

Your B2B SaaS tool is considering adding a data export feature for clients to download their reports in different formats. You estimate that this will impact 70% of your enterprise customers (Reach), will have a high impact because it allows flexibility in using the data (Impact), and you’re confident in its success based on customer interviews (Confidence). However, the effort is medium since it will require several weeks of development. After running the RICE score, it’s prioritized near the top of your feature list.

B2C example:

For your e-commerce platform, you’re thinking of adding a “save for later” feature on product pages. You estimate that about 60% of users will use this (Reach), it will improve the shopping experience by allowing them to keep track of products (Impact), and you have moderate confidence that users will love it (Confidence). The development effort is low since it’s a simple feature. After scoring it using RICE, you find that it’s a top priority compared to other potential features.

By assigning a score to each feature request based on these criteria, you can prioritize features more objectively. The higher the RICE score, the higher the priority.

Step 5: Avoid the “Build Trap” with continuous evaluation