We

We built the ultimate Walmart review checker – spot fake reviews

Hacker News

We built the ultimate Walmart review checker – spot fake reviews

Ever wondered if Walmart reviews are real? We did too. So we built FakeFind — a free tool that scans Walmart (and other sites like Amazon and eBay) for suspicious reviews using AI. FakeFind checks for fake review patterns like: Repetition and stock phrases Sudden surges of positive reviews Seller manipulation and review hijacking Paste in any Walmart product link and get a Trust Score, Adjusted Rating, and a quick review authenticity summary — in seconds. No extension needed. Would love feedback from the HN community. Try it here: https://fakefind.ai

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Actual performance

3points
1comments
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
AppSumoMay struggle as an AppSumo deal · Strong signals: reviews · Missing: plus, platform, intuitive
49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
43%43% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: using · Missing: mac, agents, macos
41%41% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
28%28% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
21%21% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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