Selling a web app, Auto Swatch

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Unfortunately, I have a failed startup that needs to pay off some of its debts. Myself and a few others have over a combined 300 hours of work into this project. I'm hesitant to put this on Flippa or eBay or whatever; I just don't think that crowd will appreciate it. I'm looking for suggestions on where to try and sell it (other than HN). The site is Auto Swatch: http://swatch.nick.sg (this is just a demo site for the purpose of selling it. Actual domain is http://autoswatch.com). Discussion of the launch on HN: http://news.ycombinator.com/item?id=2466545 Obviously this is a depressing outcome. The project IMO still has a ton of potential, but I don't have the resources or time to make it successful. I've grown tired of the idea of investors, shlepping myself out just to get some PR, etc. The business side of things sucks. I hope someone can take over and go up against the big guys like Edmunds, Cars.com, etc. New-car research online still needs help. The project also includes an entire dealership inventory management system that pushes to Cars.com, etc. Just this mini-project alone has a ton of work into it: http://cl.ly/311e1B132N3S3l3E2P08 Email's in profile, if interested.

Visit product View on Hacker NewsFeb 3, 2012

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

76%76% 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: ide, io · Missing: https docs, excited, just released

64%64% 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 HuntOn track for Day 1 leaderboard · Strong signals: new, email · Missing: mac, agents, macos

54%54% predicted probability of success on Product Hunt, 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.

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

36%36% 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

13%13% 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.

Correct prediction on native model

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