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CarCheck – Car Buying Checklist App

Hacker News

CarCheck – Car Buying Checklist App

Hey HN! A few years ago my brother in-law was looking to purchase his first car. He was struggling to know what to look for when going to car dealerships and felt quite overwhelmed with the financial and practical decisions required. Not that I have any particular expertise with cars or the engineering involved, but through my own experiences purchasing cars and owning them I gave him some advice and "tips". As anyone would. Things only morphed from there, I spent the next couple of years in my spare time learning to code, researching, and developing CarCheck. It's been a journey! Hindsight is 20/20 and some things I would have done differently, but that's part of the fun. I am proud to be sharing my (imperfect) first app with the world and excited to learn from you all for my next project :) I would love to hear your feedback!

Visit product View on Hacker NewsMay 13, 2024

Actual performance

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

74%74% 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

60%60% 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 · 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 · Strong signals: code · Missing: mac, agents, macos

33%33% 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

19%19% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

16%16% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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