If

If Snapchat and Foursquare had a baby

Hacker News

If Snapchat and Foursquare had a baby

PartyHere is my first attempt at developing a sizeable, yet simple mobile web app. The idea is that users can easily create temporary "parties" at their current location, and then their friends can check in to said parties. The parties only last a few hours, so the user doesn't have to worry about the party after creating it. The idea came out of 3 Day Startup (http://cornell.3daystartup.org/) in November. Since then I've been working nonstop on coding up the project, and have been having way too much fun with it! It has provided me with an incredible opportunity to play with open source technologies like socket.io, backbone.js, and Phonegap/Cordova. Currently, the iPhone and iPad apps are under review by the app store. My request to you is for any kind of feedback. Please be honest and let me know what you feel needs to be fixed/changed (UI/UX, marketing, features...). So, what do you think?

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
92%92% 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.
Product HuntOn track for Day 1 leaderboard · Strong signals: apps, user, coding · Missing: mac, agents, macos
79%79% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: open source, ide, io · Missing: https docs, excited, just released
56%56% 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 · Strong signals: apps, users, way · Missing: mobile apps, ios, personal
50%50% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive
35%35% 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
19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
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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