TrackMySaaS
Indie HackersSaaS Management for Startups - All your SaaS on Autopilot
Back in my previous job, I was asked to create burn-reports one every 2 weeks for all the tools we use. The first time I did this - Found nearly $800 of unused/undiscovered SaaS service expenses. Spent 2 hrs every 2 wks
Share cardActual performance
2followers
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting80%80% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released57%57% predicted probability of success on Hacker News, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive28%28% predicted probability of success on AppSumo, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto27%27% predicted probability of success on BetaList, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos23%23% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: saas · Missing: arr, mrr, revenue20%20% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Incorrect prediction on native model
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SaaS B2C PPU de provisión de datos
TrustMRRFintech