My bootstrapped sideproject app, Movie Trailers and Showtimes

Hacker News

https://itunes.apple.com/us/app/movies-trailers-showtimes/id954721891?mt=8 I'm proud to show you the latest version of my passion project Marquee - an app for discovering movies, showtimes and trailers. It's chockfull of little details that make the app a pleasure to use. Rather than try to raise funding and pursue this full time, I've chosen to do this on 'Hard Mode' and treat it as a side project until it gets more traction. I realize that probably creates a catch 22 situation. How can I get traction if I don't devote time to it. Given my current life situation, it's a little tough to drop everything and "go for it". Any feedback and advice on the app is greatly appreciated.

Visit product View on Hacker NewsApr 30, 2015

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Product HuntOn track for Day 1 leaderboard · Strong signals: apple · Missing: mac, agents, macos

77%77% 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

68%68% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

48%48% 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 · Missing: plus, platform, intuitive

32%32% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

30%30% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: bootstrapped · Missing: arr, mrr, revenue

24%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, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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