Have product recommendations really been reinvented? We don't think so

Hacker News

Some days ago I came across an interesting article in a german online journal which reported about a „new feature in online marketing“ — product recommendations. The protagonists: two of the world’s largest companies in online business — Amazon and Facebook. The fact that Facebook recently changed their terms and conditions captured my interest, especially as this forces the majority of Facebook users (including me) to rise the curtain covering their personal data once more. As our business primarily focuses on personally driven recommendations, the following quotation let me sit up: „It is noteworthy, that Amazon itself is considered as the inventor of recommendations. “ Really? Read the full article on medium! https://medium.com/world-of-recommendo/back-to-the-roots-d754de66381f

Visit product View on Hacker NewsMay 27, 2015

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

81%81% 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, new · Missing: mac, agents, macos

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

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

57%57% 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, including · Missing: https docs, excited, just released

45%45% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

36%36% 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

15%15% 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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