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GetnFIT – A Health and Fitness Marketplace

Hacker News

GetnFIT – A Health and Fitness Marketplace

Hi HN! GetnFIT.io is a marketplace that helps connect health and fitness service providers to consumers. Our objective is to help consumers take control of, and improve all aspects of their physical health by providing them access to various in-person and online (where possible) services covering fitness, recovery, nutrition and diagnostics domains. A bit of background: During the pandemic, we became acutely aware that we weren’t really optimizing for health. Also, our experience as consumers of health and fitness services was not finding good, peer reviewed fitness facilities /personal trainers / sports groups. We like most people were unidimensional in our approach towards health i.e. focusing on either physical activity or nutrition or recovery but not tying them all together. Many athletes and sports teams have professionals helping them optimize all domains of health and fitness. Therefore, we decided to build a platform that address all these issues that we faced and bring a holistic approach to fitness to regular people like us. Furthermore, we realized that there is tons of good scientific information, hacks and protocols available now via online blogs and podcasts such as Professor Andrew Huberman’s Hubermanlab, Dr. Peter Attia’s Drive etc. but there is a lack of personalized guidance and accountability that keeps people from bettering their health - a platform that fosters communities working towards common goals with professional guidance could help address this problem. Based on what we’ve learnt about kickstarting a marketplace, we decided to focus on building the supply side first and we have onboarded 7 partners and about 30 services (in person and online) and we are now looking for initial users on the consumer side. Current Status: Apps are LIVE on app/play store Tech Stack: PHP + Laravel (Framework) SASS + HTML + Boostrap + JQuery + AngularJS Flutter MySQL

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Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
91%91% 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, activity · Missing: mac, agents, macos
58%58% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: personal, apps, users · Missing: mobile apps, ios, entrepreneurs
48%48% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
42%42% 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: platform, users · Missing: plus, intuitive, reviews
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.

Correct prediction on native model

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