Self-service, no-commission platform for online business acquisitions

Hacker News

After selling a couple of my own online businesses and helping others sell theirs, I noticed a need for a new type of acquisition platform. One that would tick the following boxes: - Free for both buyers and sellers - 0% commission on sales, so sellers keep 100% of proceeds (aside from escrow fees) - Self-service, meaning the seller can set their own price, handle negotiations, and transfer the business themselves - Accepts any type of online business - not limited specifically to SaaS, content sites, domain names, etc. I built Acquire Sites to meet all of these needs. Feel free to share your thoughts/feedback/questions.

Visit product View on Hacker NewsMay 30, 2024

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Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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

77%77% 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.

AppSumoStrong fit for a featured deal · Strong signals: platform · Missing: plus, intuitive, reviews

50%50% 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

49%49% 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

44%44% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

24%24% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

13%13% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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