Profitable real estate investor training & SaaS

Acquire.com

This profitable real estate investor training and SaaS business, founded in 2018, generates revenue through digital info-products, AI-powered software, and high-ticket coaching. The business produces ~$1MK annually with ~50% profit margins and operates a scalable, multi-tier funnel designed for growth. Its plug-and-play structure is not dependent on the founders, with roles easily replaceable by contractors. Growth is driven by paid traffic across multiple platforms and a large email databas...

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Actual performance

$88,136/yr

Made the leaderboard

Traction signals

Asking price$1,250,000

Annual revenue$1,057,642

Annual profit$537,079

Revenue multiple1.2x

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

85%85% 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.

Acquire.comFits revenue-generating acquisition profile · Strong signals: revenue, profit, saas · Missing: arr, mrr, ttm

76%76% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRFits verified-revenue profile · Strong signals: profitable · Missing: mobile apps, ios, personal

61%61% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released

40%40% predicted probability of success on Hacker News, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews

19%19% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

17%17% predicted probability of success on BetaList, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: email · Missing: mac, agents, macos

11%11% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Correct prediction on native model

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