Crushing Our Crowdfunding Campaign (The Love Game)

Hacker News

https://www.indiegogo.com/projects/a-game-for-falling-in-love/x/571421 This project got it's start on HackerNews a little over a month ago and has gone on to be featured by TechCrunch, Forbes, ABC, CBS, even "Liked" by Mark Zuckerberg.. The Love Game™ app is now a print BOOK in the Amazon store as well as a card game we are fundraising for on indiegogo. We were at about 60% of our goal this AM, and then indiegogo featured us in their daily email and the backers have been pouring in since. We are now at 143% of our goal and they keep coming. Thinking for any HACKERNEWS backers I'll host a private ~1-2 hour google hangout, break down the entire story from idea to posting on hacker news, to the crazy press, to the physical product, to the book, etc. and answer any questions people have and help you all in anyway I can. If you back the project, just let me know you want the HACKERNEWS deal. Thanks again for the inspiration and support! Links... The Love Game™ - Card Game Crowdfund: http://bit.ly/thelovegame The Love Game™ - Book: http://bit.ly/lovegamebook Forbes: http://bit.ly/lovegameforbes TechCrunch: http://bit.ly/lovegametc Original HN Post: https://news.ycombinator.com/item?id=8869305 The Original Love Game App: LoveActualized.com With Deep Love & Infinite Gratitude, Anthony David Adams

Visit product View on Hacker NewsFeb 22, 2015

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

88%88% 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: hacker news, 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: google, new, email · 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, way · 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 · Strong signals: host · Missing: plus, platform, intuitive

40%40% 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.

Incorrect prediction on native model

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