Funny/Joke App. Worst Idea Ever.

Hacker News

From the about Tab: With lootitooti.com, we made one of the goofiest ideas come to life. My bro and I get real goofy when we play video games. One day I was playing League of Legends with my bro and humming Game of Thrones theme(Tana Nana). My bro started humming the same song with a different lyrics (looti tooti), and we kept going. I decided we can turn this into an app, and troll a bit on humanity. We enjoy this absolutely goofy stuff, maybe someone else will like it too. If we get good response (highly unlikely), We can turn this into a platform where people would be able to create funny variations of their favorite tunes. We want to stay anonnymous for now :P, but if you have anything to say, please feel free to email primac.apps@gmail.com Thanks for checking out Looti Tooti. I'm sure now you can get through with the rest of your day!

Visit product View on Hacker NewsDec 24, 2012

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Actual performance

3points

2comments

Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · 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.

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

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

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

49%49% 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: mac, apps, email · Missing: agents, macos, agent

36%36% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

34%34% 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

18%18% 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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