Cralert - Crowd sourced alerts for WP8 and Android

Hacker News

Cralert uses crowd sourcing to answer questions about when events take place. This is my first app and I am looking for feedback on usability/design and anything else that could be better. http://windowsphone.com/s?appId=e5c10dad-7dbd-4bef-87ec-317ffc1145a4 https://play.google.com/store/apps/details?id=com.enk.cralert You can subscribe to events posted by others. The app notifies you when events take place. Features - Search for events - Ask to be notified for a particular event - Browse questions asked by other users - Post answers, up vote correct answers - Create event groups to post related events - subscribe to a group to get reminded for all events in the group https://play.google.com/store/apps/details?id=com.enk.cralert

Visit product View on Hacker NewsAug 24, 2013

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

63%63% 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, google, answers · Missing: mobile apps, ios, personal

59%59% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntOn track for Day 1 leaderboard · Strong signals: google, apps, user · Missing: mac, agents, macos

56%56% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

42%42% predicted probability of success on AppSumo, 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

33%33% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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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