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Invoice Master – A Simple Tool for Managing Freelance Invoices

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Invoice Master – A Simple Tool for Managing Freelance Invoices

Hi HN, I’m excited to share a project I’ve been working on: [Invoice Master]( https://www.invoicemaster.org ). As a freelancer, I found managing invoices to be a tedious and time-consuming task. I built Invoice Master to simplify this process and help freelancers and small businesses manage their invoicing more efficiently. Key Features: * Easy-to-use interface * Automated recurring invoice generation * Customer & Product management * File attachment to invoices I’d love to hear your feedback on the site, especially any suggestions for features you think would be useful. My goal is to make invoicing as painless as possible, so your input is invaluable. Thank you!

Visit productView on Hacker NewsMay 17, 2024
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Actual performance

4points
7comments
Did not reach leaderboard

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Indie HackersFits the IH revenue-focused audience · Strong signals: efficiently · 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.
Hacker NewsStrong engagement from HN community · Strong signals: excited, lua, io · Missing: https docs, just released, exist
51%51% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: interface, efficient · Missing: plus, platform, intuitive
43%43% 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.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos
25%25% 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: recurring · Missing: arr, mrr, revenue
14%14% 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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