Market-Leading Secondary Ticket Marketplace

Acquire.com

This profitable 8-year-old secondary ticket marketplace connects fans with tickets for sports, concerts, and live shows. A trusted Guaranteed Ticket system releases seller funds only after the event, boosting buyer confidence. The platform is scalable, multi-language, multi-currency, and mobile-first. Leader in its home market and expanding across Europe, it serves 3.1M+ active users and ~16M annual page views. A 25–30% commission and ~$250 average order power strong margins with a lean team...

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Actual performance

Did not reach leaderboard

Traction signals

Asking price$12,250,000

Annual profit$1,000,000

Launch Intel predictions

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

63%63% 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.

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

52%52% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

38%38% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

34%34% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

34%34% predicted probability of success on AppSumo, 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

30%30% predicted probability of success on Hacker News, based on ML models trained on real launch data.

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

22%22% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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