Meme Battle Com

Hacker News

Meme Battle Com

Meme Battle is a platform with a new format for viewing and rating memes. In a battle between two memes, you act as the judge and decide which one wins and which one loses. Memes with the most victories make it to the top list of the best memes at the moment – the "Hot" section. The main feature of the platform is its international scope and the absence of a specific language requirement. Created memes are automatically translated into several languages, allowing users from different countries and regions to also rate them. As the number of users and created memes increases, advanced algorithms will be activated to select content that perfectly suits you. Meme Battle is available on the following platforms: Web: https://meme-battle.com ( https://meme-battle.com/hot-memes?utm_source=telegram ) Android: https://play.google.com/store/apps/details?id=com.memebattle... ( https://redirect.appmetrica.yandex.com/serve/118185550920499... ) IOS: https://apps.apple.com/us/app/meme-battle-app/id6478446990 ( https://redirect.appmetrica.yandex.com/serve/821567547085183... ) In the future, we plan to increase the number of supported languages, run promotions, and add new features. Please give us some feedback about platform: - Do you like idea? - What do you like about this platform and what don't you like? - Do you have some idea

Visit product View on Hacker NewsAug 27, 2024

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Indie HackersFits the IH revenue-focused audience · Strong signals: created, ios · Missing: supports, reddit linkedin, podcasting

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best fitHighest predicted score across all platforms for this description.

TrustMRRFits verified-revenue profile · Strong signals: ios, apps, google · Missing: mobile apps, personal, entrepreneurs

67%67% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Strong signals: platform, users · Missing: plus, intuitive, reviews

59%59% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: apple, google, apps · Missing: mac, agents, macos

36%36% 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, io · Missing: https docs, excited, just released

36%36% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

21%21% 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.

Correct prediction on native model

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