MoodTrack, a simple iPhone app to track your moods and thoughts

Hacker News

I've often wondered whether there are any patterns or cycles to my moods so I built a simple iPhone app that occasionally pings me to ask how I'm feeling on a scale of 1 - 10. I also note down what I'm thinking or doing at that moment and automatically grab my location. I use the data to show some basic statistics on how I've been feeling on average over the past three days, past week and since I started tracking. There's also a graph of my moods over time. I'd love to get feedback on whether people would find something like this useful. I'm curious about what other things people would want to track about themselves and interesting things to do with the data. http://itunes.apple.com/us/app/moodtrack/id541505268?mt=8

Visit product View on Hacker NewsJul 28, 2012

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43points

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Launch Intel predictions

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

85%85% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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.

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

51%51% 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

50%50% 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 · Strong signals: occasional · 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

16%16% 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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