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ThemeIQ.com, Mobile App Theme Marketplace

Hacker News

ThemeIQ.com, Mobile App Theme Marketplace

I'm getting ready to launch a new marketplace for mobile app themes and designs. But before I do any feedback that anyone might have on the copy, design, concept, execution, etc. would be greatly appreciated. Background: I have a web development background and have developed a some mobile apps over the past few years. Although I know my way around Photoshop/Fireworks/The Gimp, I am by no means a designer. That being said, while developing my latest app I was thinking that it would be nice to just buy and download a nice theme for the app just like you can buy stock photographs or themes for WordPress. ThemeIQ was born. I used Bootstrap because I like the fonts and subtle graphics - plus it sure gets things going a lot quicker. Although it is a fully functioning marketplace, it is an MVP that will be iterated after fully validating the market. I just want to get something out there. I have already received some preliminary validation from designers & developers I know and will continue to expand on that. Again any feedback would be fantastic. URL: http://themeiq.com Cheers,

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
92%92% 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.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
49%49% 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: plus · Missing: platform, intuitive, reviews
46%46% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: mobile apps, apps, way · Missing: ios, personal, entrepreneurs
41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: apps, new · Missing: mac, agents, macos
35%35% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
14%14% 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.

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