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FigMaps, a visual sitemap builder to plan websites and gather content
Hacker NewsFigMaps, a visual sitemap builder to plan websites and gather content
Generate, build, plan and visualize your website structure. Collaborate with your team in real-time to gather content, improve your site architecture, design, UX and SEO. Start prototyping instantly using AI. Please visit https://app.figmaps.com/ and try it out yourself (Login as guest, no registration required!)
Share cardActual performance
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Made the leaderboard
Launch Intel predictions
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Product HuntOn track for Day 1 leaderboard · Strong signals: visual, using · Missing: mac, agents, macos71%71% 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, podcasting69%69% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Strong signals: builder · Missing: plus, platform, intuitive62%62% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: visualize · Missing: mobile apps, ios, personal57%57% 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 released39%39% 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, revenue16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: collaborate · Missing: web3, chat, crypto10%10% predicted probability of success on BetaList, based on ML models trained on real launch data.
Incorrect prediction on native model
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