Launch Platform

Score your AppSumo description

ML models trained on 4k+ real AppSumo launches. Get your probability score in seconds.

<3%

of submitted products get a featured deal

What the model looks for in AppSumo descriptions

Competition level: Low (gated by acceptance). Success criteria: Above-median review count.

Revenue-adjacent language (MRR, paying customers)
Top AppSumo deals reference existing revenue or paying users, not just product vision.
B2B positioning with specific user persona
Name the job title or team that buys, such as agency owners or marketing managers.
Integration ecosystem mentions (Zapier, Slack, etc.)
Mature SaaS products signal fit by naming tools they connect to.
Maturity signals over early-stage language
Words like beta, MVP, and coming soon correlate with lower deal performance.

Our AppSumo model is trained on 3,714 real listings collected from the platform. Success is defined as: above-median review count.

3,714

Products in dataset

49.6%

Avg prediction score

Top-deal rate

Step 1

Name, tagline, and full description.

Step 2

Instant probability and missing signals.

Step 3

Re-score after each edit.

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