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Serializd: An App for TV Logging
Hacker NewsSerializd: An App for TV Logging
Hello HN! I wanted to share a passion project of mine. Its called Serializd, and its an app that allows you to track your TV content. Think of it like a Goodreads for TV (or a Letterboxd for TV). Its currently available on iOS, Android, and the Web. I built the iOS and Android apps using React Native. The web version uses NextJS on the Frontend, and Django on the Backend. Currently, Serializd has 100k+ users. There is a strong focus on community and interacting with other people as you're logging your own TV watching and keeping up with the newest TV shows.
Share cardActual performance
4points
Did not reach leaderboard
Launch Intel predictions
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Indie HackersFits the IH revenue-focused audience · Strong signals: ios · Missing: supports, reddit linkedin, podcasting82%82% 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: apps, user, new · Missing: mac, agents, macos73%73% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: ios, apps, users · Missing: mobile apps, personal, entrepreneurs63%63% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released44%44% 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, intuitive42%42% 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, revenue24%24% 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, crypto0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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