Product prioritization is the discipline of deciding what to build next when you can't build everything.

Steve Saper
Founder & CEO of PM33. Building the agentic-PM platform and writing about how product management is being remade in the AI era.
Product prioritization is the discipline of deciding what to build next when you can't build everything.
Most teams use bad frameworks. They say: "Let's do what customers ask for." Result: You end up building a feature nobody needed and ignoring the features that matter.
Shreyas Doshi, VP of Product at Stripe and advisor to the most successful product teams, has spent years studying how the best teams prioritize.
I agree, however, the best prioritization framework isn't universally applicable. What works for a B2C marketplace is different from what works for enterprise B2B. Context matters.
Here's what Shreyas has learned: The best prioritization framework for your company is the one that reflects how you actually make decisions.
Shreyas has identified four frameworks that work:
When to use: Early-stage startups, small product teams
Score each initiative on four factors:
Formula: (Reach × Impact × Confidence) / Effort
Higher score = higher priority
Advantages: Simple, transparent, easy to explain
Disadvantages: Hard to estimate numbers, doesn't account for strategic value
When to use: Customer-obsessed teams, product-led companies
Prioritize based on jobs customers are trying to accomplish and how well your product serves those jobs.
Steps:
Advantages: Customer-focused, reveals true value
Disadvantages: Time-consuming, requires customer access, interpretation varies
When to use: Growing companies with clear strategic goals
Score each initiative on how well it supports your company's strategic priorities:
Examples of strategic priorities:
Each initiative gets a score: How directly does it support one of these priorities?
Advantages: Ensures team alignment, prevents random feature building
Disadvantages: Strategic priorities can be vague, hard to compare across priorities
When to use: Data-driven teams, products with clear metrics
Score based on:
Opportunity Score = Opportunity Size × (Problem Intensity - Solution Satisfaction)
Advantages: Data-driven, identifies genuine market gaps
Disadvantages: Requires good data, can miss strategic value
Shreyas recommends matching framework to stage:
Early Stage (0-1M ARR):
Growth Stage (1M-10M ARR):
Scale Stage (10M+ ARR):
You prioritize features that increase daily active users. But your metric that matters is retention, not DAU.
You optimize for the wrong thing, and your strategy fails.
Fix: Define success metrics first. Prioritize features that move those metrics.
You keep shipping features while your product becomes increasingly fragile.
Technical debt grows. Bugs multiply. Customers leave.
Based on my experience, allocate 20% of capacity to debt and stability. Don't negotiate on this.
You decide what's important without input from engineering, design, customer support.
They see things you don't. They'll fight your decisions because they weren't consulted.
Fix: Make prioritization collaborative. Include engineering, design, and support in the decision.
You reprioritize every sprint based on new feedback.
Your team can't execute anything because targets keep moving.
Fix: Prioritize quarterly. Stick to it unless something fundamental changes.
Here's the process Shreyas recommends:
There's no perfect prioritization framework. Pick one that matches your:
Use your chosen framework consistently. Measure impact. Learn. Improve.
The best team isn't the one with the perfect framework. It's the one that ships impact regularly and learns from every decision.