4 Prioritization Techniques For Deciding What To Build
Product managers have to decide what to build, what needs more research, and what to drop, usually with conflicting input from customers, engineers and execs. Four prioritisation techniques cut through the noise:
“RICE Scoring ranks features by Reach × Impact × Confidence ÷ Effort. The MoSCoW Method sorts them into Must, Should, Could and Won’t Have. The Kano Model classifies them as Basic Needs, Performance Needs or Delighters. And Customer Problem Stack Ranking asks users to rank their own problems, so the roadmap follows real priorities, not internal guesses. MoSCoW is the fastest; RICE adds more factors; Kano and Customer Problem Stack Ranking bring in user research.”
Prioritisation matters in every job, but product managers have to be ruthless at it on a whole other level. As a PM, you decide which features get built, which need more research, and which get dropped altogether. It's a hard process, made harder by the conflicting opinions coming from customers, engineers, data analysts and the executive team.
Luckily, some good prioritisation frameworks help you sort through it and decide what to work on. Here are 4 techniques for deciding what to build.
| Technique | What it does | Best for |
|---|---|---|
| RICE Scoring | Scores features by Reach × Impact × Confidence ÷ Effort | Comparing features using internal estimates |
| MoSCoW Method | Sorts features into Must, Should, Could and Won't Have | A quick, calculation-free triage |
| Kano Model | Classifies features as Basic Needs, Performance Needs or Delighters | Balancing must-haves against moments of delight |
| Customer Problem Stack Ranking | Asks users to rank their own problems by importance | Grounding the roadmap in real user priorities |
1. RICE Scoring
The RICE Scoring system is one of the most popular prioritisation methods product managers use to inform their roadmap. It weighs priorities across 4 categories: Reach, Impact, Confidence and Effort.
Reach: How many people will this feature affect? Use the data you have to estimate how many will use it each month. Work out the profile of customer who needs it, then count how many people fall into that group.
Impact: How much will it affect them? Knowing how many people a feature affects isn't enough; you also need the depth of that effect. It's hard to measure, with no perfect calculation, so we suggest rating it 0-3, where 3 is massive impact and 0 is none.
Confidence: How confident am I that this feature will work? Measuring confidence is subjective and unscientific, but most experienced product people can make a reasonable estimate of how well a feature will land.
Effort: How much effort will it take to build? As a PM, you'll want to consult your design and technical colleagues for the most accurate estimate. Accounting for time, complexity, opportunity cost and other factors, score the effort 0-5, where 0 is easy peasy and 5 is endless sleepless nights.
Calculating the RICE Score: Multiply Reach, Impact and Confidence, then divide by Effort to get your RICE score. Compare it to your other candidate features to prioritise your roadmap or backlog. For a worked example with real numbers, see our guide to calculating impact for RICE scoring.
2. The MoSCoW Method
The MoSCoW Method is a simple, calculation-free way to quickly sort what's important from what's not. The name comes from the 4 categories it uses: Must Have, Should Have, Could Have, and Won't Have.
Must Have: These features are non-negotiable. You can't launch without them. A feature might land here for lots of reasons: it's the core of your value proposition, it's the primary layer of security, or your sales team promised it to the top-paying customers. Either way, you're not getting away without building it.
Should Have: These features are ideal, but missing them won't sink the company. Everyone's just better off if they exist.
Could Have: These features aren't required for success. They're "nice to have".
Won't Have: These don't make the cut this time. That doesn't mean they won't show up in a later version.
3. Kano Model
The Kano Model is a prioritisation framework that looks at features across 3 dimensions, and it works best as a graph.
Delighters: These features make customers go wow. They leave a lasting impression and put your competitors behind.
Performance Needs: These features help customers hit their goals better. They're much appreciated and leave customers content.
Basic Needs: Without these, the product is useless. They're the minimum your users expect.
You'll need questionnaires or customer conversations to understand which features they feel belong in each category. Your goal as a PM is to work your way up the list. First, make sure all the Basic Needs features work perfectly, with no friction. Then move to Performance Needs, where customers start to value what you offer. Finally, blow them away with Delighters.
4. Customer Problem Stack Ranking
The best products and features solve a burning customer problem. Customer Problem Stack Ranking asks your users to rank their problems by importance, so the PM can see which are most urgent to solve.
Customer Problem Stack Ranking needs customers to take part, and you can run it two ways:
1) Manual Customer Problem Stack Ranking. Ask customers to list their problems and rank them by importance. You can do this during user interviews.
2) Automated Customer Problem Stack Ranking. Use customer stack ranking software. The advantage over the manual process is scale: you learn the most important problems to everyone, not just a few.
Companies that set outcome-focused objectives ("increase revenue by 25%"), not output-focused ones ("build features X, Y and Z"), often use problem stack ranking to prioritise. You can also use it at other stages of the product development cycle, like validating product ideas and refining messaging.
Which prioritisation technique should you use?
Your method should match your project needs. For a quick check, the MoSCoW Method helps you sort a list of tickets. To draw on internal knowledge, RICE Scoring uses more factors for a more informed result. The ideal approach, especially for new projects, is to pull insights from user research with methods like Customer Problem Stack Ranking or the Kano Model.
If you're weighing up ranking-based methods specifically, our guide to choosing a survey ranking method walks through the trade-offs, and why startups should have a problem-focused roadmap makes the case for starting from customer problems, not a feature list.
These aren't the only prioritisation methods, of course. There are plenty more, and you'll only find what works best for you through practice and testing. Create a free Customer Problem Stack Rank on OpinionX in just 60 seconds.
Frequently asked questions
What are the main product prioritisation techniques? Four of the most widely used are RICE Scoring (Reach × Impact × Confidence ÷ Effort), the MoSCoW Method (Must, Should, Could, Won't Have), the Kano Model (Basic Needs, Performance Needs, Delighters), and Customer Problem Stack Ranking (users rank their own problems by importance).
What is RICE scoring? RICE scores each feature on four factors, Reach, Impact, Confidence and Effort, then multiplies Reach, Impact and Confidence and divides by Effort. The higher the score, the higher the priority. See our full RICE guide for a worked example.
What is the MoSCoW method? MoSCoW is a calculation-free way to triage a backlog by sorting each item into Must Have, Should Have, Could Have or Won't Have. It's the fastest of the four techniques and works well for a quick pass over a list of tickets.
Which prioritisation technique should you use? It depends on the decision. MoSCoW is quickest for triage, RICE adds more factors for a more informed comparison, and Kano and Customer Problem Stack Ranking bring in real user research, which is the strongest basis for new projects where you can't yet trust internal estimates.