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Level-Up "game" for people trying to lose weight

Hacker News

Level-Up "game" for people trying to lose weight

Our first iPhone app is finally out: http://itunes.apple.com/us/app/slimkicker-calorie-counter/id512812753?ls=1&mt=8 . We also got a website: slimkicker.com for those without iPhones. As the title suggests, we try to apply gamification for people trying to lose weight. We use a points system similar to Weight Watchers, except in reverse (the more healthy the food, the more points). Some people have commented we're similar to another site: Fitocracy (their app also is out today). But we're reaching a different audience: people who want to lose weight or live healthy, but don't know how/where to start. We offer 7-30 day challenges that help people build long-term habits such as "quit soda for a week". The point is to break down the abstract goal of being healthy to smaller subgoals, and winnable games. We're also working on providing concrete, personalized advice based on your activity too. Tracking and gamification are nice, but it's useless without actionable advice. Links: http://itunes.apple.com/us/app/slimkicker-calorie-counter/id512812753?ls=1&mt=8 http://www.slimkicker.com

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
79%79% 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, activity · Missing: mac, agents, macos
55%55% predicted probability of success on Product Hunt, 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
44%44% 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: personal · Missing: mobile apps, ios, entrepreneurs
42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
39%39% 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
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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