SEO-focused high-ticket dropshipping store that specializes in home decor

Acquire.com

eCommerce store with $12,000 in TTM revenue and $4,000 in TTM profit, selling contemporary Scandinavian decor. This is a matured SEO Dropshipping store in the high ticket home decor niche (B2C and B2B). Since its inception in October 2018, this store has consistently generated a yearly traffic of 15-20k from targeted SEO. ✅ $12,000 in TTM revenue ✅ $4,000 in TTM profit ✅ $1,000 in revenue last month ✅ $500 in profit last month ✅ Competitors: Articture.com, Venettodesign.com

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Actual performance

Did not reach leaderboard

Traction signals

Asking price$10,000

Launch Intel predictions

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

84%84% 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.

Hacker NewsStrong engagement from HN community · Strong signals: 000, io · Missing: https docs, excited, just released

63%63% predicted probability of success on Hacker News, based on ML models trained on real launch data.

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

59%59% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

43%43% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

29%29% predicted probability of success on BetaList, based on ML models trained on real launch data.

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

19%19% 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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