Turnkey lead-generation platform with advanced targeting and CRM integrations

Acquire.com

This fully built SaaS delivers enriched company and contact data that rivals major providers while offering smarter filters. Users define ideal customer profiles with AI classification (by product type and customer segment) and unique criteria such as missing executive roles. The system then pulls qualified accounts, appends LinkedIn and verified email details, and pushes records into any CRM via Zapier. Previously driving $13 K MRR from 83 customers, the product is documented, revenue-ready,...

Visit product View on Acquire.com SaaS

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Actual performance

$13,000/yr

Made the leaderboard

Traction signals

Asking price$96,330

Annual revenue$156,000

Revenue multiple0.6x

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · 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.

Product HuntOn track for Day 1 leaderboard · Strong signals: user, email · Missing: mac, agents, macos

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

64%64% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: users · 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

42%42% 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, users · Missing: plus, intuitive, reviews

36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

33%33% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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