FindYogi -Product Comparison With Automated Value For Money Scoring

Hacker News

hi,<p>We have released a fresh version of FindYogi.com (http://www.findyogi.com). Please help us with feedback.<p>New Features:<p>A. Quantify Value for Money. We have introduced FindYogi Index, a rating out of 5, that tells you if a product is worth buying at its current market price. This a completely automated feature that takes into account all the products, and their prices, of that particular category into account. We do not currently account for brand perception and novelty of the product.

Visit product View on Hacker NewsJun 12, 2013

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Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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

64%64% predicted probability of success on Product Hunt, 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

35%35% predicted probability of success on Indie Hackers, 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

33%33% 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

32%32% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

27%27% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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