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Eazypay.me – Invoicing Made Simple

Hacker News

Eazypay.me – Invoicing Made Simple

Hi I'm Chris, a developer based in London. EazyPay.me is simple invoicing software. You can create invoices using templates, share them via email, direct link and pdf. And recently I added getting paid electronically via invoices. I created EazyPay.me because from personal experience, invoicing software comes loaded with features I don't need. Also, my Dad still hand delivers printed out invoices and a friend of mine said he just wants to get notified when he get's paid. I'm monetising EazyPay.me by charging a subscription for additional features and more usage (more invoice for example). And also charging a fee on invoices paid electronically. I've gone with a fremium model as I want to gather feedback fast, but I'm open to trying a free trial. It's still early but I have just over a thousand sign ups, the vast majority of which are still free. Any feedback would be massively appreciated! Like I mentioed above, there's a free tier so you can take a look around for free. https://www.eazypay.me/?source=hn Thanks, Chris

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Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting
69%69% 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.
TrustMRRLess likely to generate early MRR · Strong signals: personal · Missing: mobile apps, ios, entrepreneurs
49%49% predicted probability of success on TrustMRR, 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
42%42% 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 · Strong signals: model, email, using · Missing: mac, agents, macos
37%37% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: subscription · Missing: arr, mrr, revenue
13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: paid · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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