Rentables, the Community Rental Marketplace

Hacker News

What started as a learning project that solved a problem of mine, snowballed into a product that I'm working to grow. It's called Rentables. It's a community marketplace that allows anyone to rent their things to their community. I'm big on DIY, but with every project I do I'm always finding myself buying a new tool, using it once, and then it lives in the shed collecting dust. This was a problem I thought I could solve, and so I set myself the challenge to build something that did. I believe the concept has the potential to change behaviour around buying, and make so many things accessible to everybody. I've built this as a solo-dev, completely bootstrapped, and I'm wanting to grow this into something great. Right now I'm starting small – I'm working with my local community, engaging with people on a small scale to iron out as many user wrinkles, iterating, rinse and repeat. They key challenge I'm trying to overcome at the moment is the dichotomy of a two-sided network, and ensuring that I'm focusing on the right audience at the right time. For now I see the most important audience being the Owners who will be listing their items. Doing that should help develop more of a catalogue of items, in turn making the platform more appealing to renters. It's not perfect, but I know there's a lot of bright minds here on HN so I wanted to share and hopefully get some feedback, perspectives and challenges on how I'm approaching things. All of these will help me, and Rentables grow. Edit: It's currently locked down to Australian sign ups so that I can keep it manageable.

Visit product View on Hacker NewsSep 15, 2023

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · 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: user, new, using · Missing: mac, agents, macos

79%79% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

44%44% 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 · Missing: plus, intuitive, reviews

29%29% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: bootstrapped · Missing: arr, mrr, revenue

12%12% 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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