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Solved SEO for Carrd Sites

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Solved SEO for Carrd Sites

I've been using Carrd for years to build sites for my personal projects, but one thing always frustrated me—SEO. Carrd’s single-page structure with hash-based navigation (#sections) makes it almost impossible for search engines to properly index your content. No real URLs, no sitemaps, and limited meta tags meant my sites just weren’t showing up in search results. That's why I created a small tool to solve SEO for Carrd sites: - Multi-Page Structure: ZerpHost transforms your Carrd site into a properly structured website with real URLs for each section (no more # links). - Auto-Generated Sitemaps: It automatically creates a sitemap so search engines can actually find and index your content. - Optimized Meta Tags: Each page gets proper meta tags and canonical URLs, giving your content the SEO love it deserves. It would be great to get your feedback on this solution, how it works for you, and what you think can be improved.

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Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting
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best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: single, using · Missing: mac, agents, macos
77%77% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Strong signals: host · Missing: plus, platform, intuitive
55%55% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: personal, way · Missing: mobile apps, ios, entrepreneurs
37%37% 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 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 · Strong signals: arr · Missing: mrr, revenue, profit
12%12% 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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