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Utilizing Gamecenter in apps that are not games

Hacker News

Utilizing Gamecenter in apps that are not games

We were able to successfully get an app into the App Store that utilized Gamecenter, but was not a game. It is called Reminders with Friends. We used the turn based matchmaking in order to send and receive data (in this case reminders) between Gamecenter friends. We then use these reminders to set off time based or GPS based reminders. This was the first app that we found that was able to utitilize Gamecenter in this way. If you have any questions, I would be happy to answer them. Link to app: http://itunes.apple.com/app/reminders-with-friends/id486230629?mt=8 Link to website: http://slyceapps.com/reminders/

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Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
68%68% 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: apple, apps · 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: apps, way · Missing: mobile apps, ios, personal
53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
36%36% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
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
14%14% 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
2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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