I made a native HTML5 animated banner generator

Hacker News

I want to share the tool I have been working on for almost a year. It takes a multi-frame Figma design and converts it to native HTML5. Then applies a preset animation to elements based on their type. The result is an animated HTML5 banner ad from a static Figma design, with each frame appearing in sequence and delivering the marketing message. For example: - Frame 1: Name the problem - Frame 2: Show your product - Frame 3: CTA or disclaimer You can process many sizes at once, such as 300x600 with 2 frames + 728x90 with 4 frames + 1080x1080 with only one frame. So all creatives are animated in a second. Building this tool with ad creative automation in mind, as my entire background revolves around display ads. I also tried to make it developer friendly. It generates tiny human readable HTML+CSS code. I think this would be helpful for brands and marketing teams and want to get as much feedback as possible. Thanks for your time and support. Alex

Visit product View on Hacker NewsSep 10, 2024

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best fitHighest predicted score across all platforms for this description.

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

70%70% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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42%42% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: friendly · Missing: plus, platform, intuitive

32%32% 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, 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.

Correct prediction on native model

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