The Priority Scoring Formula That Changed How We Build
Discover how Collectic uses votes, ARR impact, and effort estimates to automatically prioritize your product roadmap with data instead of gut feeling.
Posted by
Bart ZalewskiRelated reading
How AI-Powered Duplicate Detection Saves You Hours Every Week
Learn how Collectic uses OpenAI embeddings and clustering algorithms to automatically detect and merge duplicate feedback, saving you hours of manual work.
Why Magic Link Authentication is Perfect for Feedback Boards
Learn why passwordless magic link authentication removes friction for voters while keeping your feedback board secure and spam-free.
Stop Guessing What to Build Next
Most founders prioritize features by gut feeling. Which requests are loudest? What seems most important? Which customer complained most recently?
This leads to building features that don't move the needle, ignoring high-value requests from paying customers, and wasting time on low-impact work.
The Priority Scoring Formula
Collectic uses a simple but powerful formula to automatically score every idea:
score = votes × ARR_impact ÷ effort_estimateLet's break down each component and why it matters.
Votes: What Users Want
Every upvote represents a user saying "I want this." More votes mean more people will benefit from the feature. Simple and democratic.
With Collectic's public feedback board, users can vote on ideas from any channel. The votes automatically aggregate, even when duplicates are merged.
ARR Impact: What Matters for Revenue
Not all votes are equal. A request from a customer paying $10,000/year should weigh more than free trial users. That's where ARR impact comes in.
Collectic integrates with Paddle and LemonSqueezy to automatically track the annual recurring revenue of each voter. High-value customers automatically boost the priority of their requests.
Effort Estimate: What You Can Build
A feature with 100 votes that takes 3 months might be less valuable than one with 50 votes you can ship in a week. Effort matters.
Tag each idea as Small, Medium, or Large effort. Collectic divides by this to surface quick wins - features with high impact and low effort.
Real Example: Making Decisions
Here are three real feature requests from a Collectic user:
- Dark mode: 45 votes, $12K ARR, Large effort → Score: 180
- CSV export: 12 votes, $8K ARR, Small effort → Score: 384
- API access: 8 votes, $24K ARR, Medium effort → Score: 192
Without data, you'd probably build dark mode first (most votes). But the math shows CSV export has 2x the impact per hour of work. Ship that first, delight users faster, and keep momentum.
Automatic Updates
The beauty of automated scoring is that it updates in real-time. As more users vote, as paying customers upgrade, as you refine effort estimates - your priorities automatically adjust.
Your roadmap stays relevant without manual spreadsheet updates. Just check your Collectic kanban board and work from the top down.