I made a mobile app to help people find rooms and flatmates in HCOL

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Hi! I spent 3 years living in Brussels and Paris and oh lord was it overly complicated to find a flatshare. As a student / young worker, I did not have the budget to afford a studio or a flat in those capitals (I mean who does?), so I could only rely on flatsharing or a dorm. The main and almost only source at the time was Facebook groups and it was so chaotic. 30% of the posts are straight up scams or people trying to sell you their dropshipping course (source: trust me). Sending 20 - 30 messages a day floods your Messenger inbox and the chances of getting a reply is extremely low. If the rooms is not already taken, scheduling visits is a nightmare. Lots of informations are lacking on the posts such as price, charges, number of roommates, location and so on. There has to be a better way. My name is Djulian and with my partner, we spent the last few months building Coloco, a mobile app to help you find a roommate and / or a room. Here is a few features for the MVP: - Search cities / region with a search bar or use our interactive map; - Advanced filters; - Instant chat; - Rich description of postings; - And many more features coming!! We finally released yesterday and we are so excited about it because we're hoping to finally fix this finding a room in a HCOL* city problem once and for all. Let me know if you have any questions! Take care, Djulian. PS: Here is a link you can use or your mobile phone to open the app on the store: https://link-to.app/coloco *: High Cost of Living

Visit product View on Hacker NewsJul 13, 2024

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Hacker NewsStrong engagement from HN community · Strong signals: excited, io · Missing: https docs, just released, exist

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nativeThis product was originally launched on this platform.

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

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BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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