Dot Star Media
Indie HackersFind and respond quickly to requests from journalists
Our aim is to provide an efficient way of monitoring, receiving and responding to the best media requests on social media without having to spend hours wading through noise and spam.
Share cardActual performance
1followers
Did not reach leaderboard
Launch Intel predictions
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TrustMRRFits verified-revenue profile · Strong signals: way · Missing: mobile apps, ios, personal56%56% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting55%55% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos49%49% 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: ide · Missing: https docs, excited, just released47%47% predicted probability of success on Hacker News, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: efficient · Missing: plus, platform, intuitive36%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, revenue19%19% 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, crypto6%6% predicted probability of success on BetaList, based on ML models trained on real launch data.
Incorrect prediction on native model
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