Dating website where ladies get paid

Hacker News

Happy new year fellow HNers! This is my first Show HN... and it's a dating website. The crowd here is not my target market, so I'm not looking for SEO/traffic, but looking for feedbacks. Lots of it. I'm fully prepared that I'll get bashed due to the nature of my product. What: An online Indonesian dating website where the ladies get paid if their date sucks. That "paid" part is just a gimmick (the feature is not fully implemented) which seems to work. So far nobody questions the lack of implementation. If people do need it, I'll implement it. Why: I want to quit my job and "do startup" but I don't have any good idea. Dating website is (saturated but still) easy to get traction. I also use this as a learning vehicle (Scala, CoffeeScript, AngularJS, Google App Engine). When: I'm doing this after hours and weekends. Where: http://www.ngajakjalan.com How: Most likely you don't want to create an account, so please login with demo/demo. It's a real account, so please don't send message to other members from there :) Stats so far: Landing page for 2 months, then 2 months running. 8k members, 85% male, 100k pageviews/month. Spending $10 daily for FB ads to get female members. Specific questions: I'm thinking of raising seed money so I can quit my job and work on this fulltime. Given my situation (single, employed, solo founder) and my website progress, (1) Is this a good idea? (2) What would it take to get me there? (3) If not good idea, what are the alternatives?

Visit product View on Hacker NewsJan 1, 2013

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

90%90% 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

72%72% 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: google, new, single · Missing: mac, agents, macos

61%61% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: month, google · Missing: mobile apps, ios, personal

54%54% 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

41%41% 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

26%26% 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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