Ep

Epic levels of tracking from a website

Hacker News

Epic levels of tracking from a website

I was looking into alternative mail clients for Windows and came across a site called AddictiveTips [0] and was immediately shown their cookie and spying declaration. I use UBlock Origin and block all third party cookies and empty my browser when it's closed and I thought I had seen it all with newspapers taking the piss with their trackers but these people are showing an extreme level of contempt for visitors. If I am to interpret them correctly, they want to save hundreds of cookies on my computer and pass my data to potentially dozens and dozens of third parties, some of which (in fact a fair few) duplicate the efforts of others. WTH? [0] - https://www.addictivetips.com/

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: computer, 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 HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
62%62% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
50%50% 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
45%45% 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
45%45% 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
2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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