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Arrived – Easily buy shares of rental properties

Hacker News

Arrived – Easily buy shares of rental properties

Hi HN! We’re Ryan, Kenny, and Alejandro, the co-founders of Arrived (https://arrivedhomes.com), a real estate investing platform where anybody can buy shares of rental properties in under 4 minutes. Rental properties have historically been one of the best ways to build wealth over time. They provide consistent passive income & allow investors to benefit from rising home values. But buying and managing rental homes has always required a TON of capital, time, & expertise. We want to change this. This is the first time that anyone (including non-accredited investors) can buy shares of individual rental homes online. Arrived acquires properties in the top markets, rents & operates them, and allows investors to invest any amount from $100 - $10,000 per property. We think it’s pretty cool :) On Arrived, investors can browse individual homes (just like Zillow) and then purchase shares with an easy e-commerce checkout experience. After purchasing shares, investors earn rental income quarterly and watch their investments grow as the home appreciates. We’re working to remove the main points of friction to real estate investing so that more people can access this asset class. We've just opened our 2nd market and we’d love any feedback from the HN community. Thanks! Ryan

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Indie HackersFits the IH revenue-focused audience · Strong signals: including · Missing: supports, reddit linkedin, podcasting
82%82% 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.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
40%40% 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, 000, io · Missing: https docs, excited, just released
38%38% 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
38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: open · Missing: mac, agents, macos
26%26% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit
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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