Score your BetaList description
ML models trained on 1k+ real BetaList launches. Get your probability score in seconds.
What the model looks for in BetaList descriptions
Competition level: Low. Success criteria: Signup conversion and early traction.
Early access / waitlist / beta language
BetaList readers expect to join before public launch. Make the signup ask explicit.
Clear problem statement up front
State the pain point in the first line before describing your solution.
What early adopters get for signing up
Offer a concrete benefit such as lifetime discount or priority access.
Live product (not just an idea)
Listings with a working demo convert better than concept-only submissions.
Training data for BetaList
Our BetaList model is trained on 1,452 real listings collected from the platform. Success is defined as: signup conversion and early traction.
Highest-scoring examples
- Lett3r99.8%
- Blockbrain99.7%
How to use Launch Intel
Paste your description
Name, tagline, and full description.
Get your score
Instant probability and missing signals.
Optimize with our tool
Re-score after each edit.
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