AI Prioritization Tool
Boutique RICE Model CalculatorCEO/FOUNDER Context: “Shiny Object Syndrome” kills startups. This tool quantifies the ROI of your engineering time, helping you ruthlessly prioritize high-impact features over “nice-to-haves.”
1. Feature Backlog
Define value & effort. Click headers to sort.
| # |
Feature Name |
Reach
|
Impact
|
Conf.
|
Effort
|
Score
|
|---|
2. The “Quick Wins” Matrix
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Frequently Asked Questions
What is the RICE model, and why use it for prioritization? +
RICE is a scoring framework that compares initiatives using Reach, Impact, Confidence, and Effort. It gives you a consistent way to decide what to build next when the roadmap is full of competing opinions.
How should I define Reach in this tool? +
Reach is the number of users, accounts, or events impacted per time period. Pick a consistent unit, for example users per month, and keep it the same across all rows so scores are comparable.
What does Confidence mean, and how do I choose 100%, 80%, or 50%? +
Confidence reflects how much evidence supports your Reach and Impact estimates. Use 100% when you have strong data, 80% when you have some evidence, and 50% when it is largely an assumption that still needs validation.
How is the RICE score calculated in this calculator? +
The score is calculated as (Reach × Impact × Confidence) divided by Effort. Higher scores suggest higher expected value per unit of engineering time, assuming you are using consistent units across the backlog.
How do I use the “Quick Wins” matrix after scoring? +
Use the matrix to sanity check the top scores visually. Quick wins sit in the high value, low effort area. Strategic bets have high value and higher effort. Time sinks are high effort with low value, they usually get cut or re-scoped.
Does this tool save my backlog data? +
Yes, it saves your current backlog locally in your browser so you can come back and continue. It does not need an account, and it does not send your backlog to a server by default.