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SimpleCosts – All Your SaaS Projects' Revenue and Costs in One Place

Hacker News

SimpleCosts – All Your SaaS Projects' Revenue and Costs in One Place

I've done this all wrong but here we are, I've built the thing before validating it but in attempt to rectify my mistake I've built a wait list regardless, so here it is. I'm excited to share SimpleCosts, a SaaS platform designed to help you streamline the management of all your SaaS projects. Whether you're running multiple SaaS products or just one, SimpleCosts makes it easy to see the big picture of your revenue and expenses in one unified dashboard. See more here: https://simplecosts.app/ Any feedback, questions or comments feel free! Thanks, JS

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
82%82% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Hacker NewsStrong engagement from HN community · Strong signals: excited, io · Missing: https docs, just released, exist
61%61% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos
46%46% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews
41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: revenue, saas · Missing: arr, mrr, profit
20%20% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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