Profitability Calculator for Startups

Hacker News

Finance in startups is a very underestimated problem. There are less tools and even less that are not locked in to particular service. We're trying to solve this with Cusk. Cusk is a set of Finance Tools that are designed for small to medium sized startups. We're currently load testing and internally using these things at DoShare Cloud [1] for managing finance. One of them is a profitability calculator for subscription based businesses to calculate their break-even with users and duration as primary parameters. Here is the link to the first of the set of finance management tools for developers and startups - https://cusk.thesafezone.xyz/ [1] https://getcloud.doshare.me

Visit product View on Hacker NewsNov 26, 2024

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Indie HackersFits the IH revenue-focused audience · Strong signals: para · Missing: supports, reddit linkedin, podcasting

78%78% 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.

AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive

44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

39%39% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: users, para · 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: profit, subscription · Missing: arr, mrr, revenue

17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: user, using · Missing: mac, agents, macos

16%16% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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