Ne

Neighbourhood sharing startup

Hacker News

Neighbourhood sharing startup

Checkout a neighbourhood sharing startup myself and a great team are working on at Ottawa Startup Weekend. The basic idea is neighbourhoods want to share and create a community around the space they take care of. We let neighbourhoods share high priced items like snow blowers, lawnmowers, gardening supplies, camping gear etc. with their neighbours in return for borrowing their stuff. Take a look at us at http://signup.moochable.co or fill in a survey at http://app.fluidsurveys.com/surveys/josh-m2/community-sharing-website/. Any advice or questions are appreciated. Moochable - Share. Care. Grow PS - I am a long-time lurker on HN. Basic background is I am an Aerospace Engineering from Canada learning how to program.

Visit product View on Hacker NewsApr 28, 2012

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

71%71% 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 · Missing: supports, reddit linkedin, podcasting

67%67% predicted probability of success on Indie Hackers, 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

41%41% 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.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

28%28% predicted probability of success on TrustMRR, 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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