Launch Intel
iHatePosting

iHatePosting

TrustMRR

iHatePosting is a social media scheduling platform that helps creators, businesses, agencies, and marketing teams plan, create, schedule, and publish content across multiple social networks from one p

iHatePosting is a social media scheduling platform that helps creators, businesses, agencies, and marketing teams plan, create, schedule, and publish content across multiple social networks from one place. Create your content once, tailor it for each platform, organize campaigns with a visual content calendar, and keep your publishing schedule consistent without switching between apps all day. iHatePosting supports publishing workflows across 14 social platforms, like Instagram, LinkedIn etc

Visit productView on TrustMRRSep 1, 2026ProductivityMobile Apprevenuecat
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Actual performance

Did not reach leaderboard

Traction signals

Domain Rating26

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: apps, visual · Missing: mac, agents, macos
84%84% 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 · Strong signals: supports · Missing: reddit linkedin, podcasting, created
76%76% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: apps · Missing: mobile apps, ios, personal
58%58% predicted probability of success on TrustMRR, 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: platform · Missing: plus, intuitive, reviews
45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released
32%32% predicted probability of success on Hacker News, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
27%27% 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
7%7% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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