Simplify Your Podcast Sharing with Skill Piper

Hacker News

Hey HN, We're thrilled to introduce SkillPiper — a game-changing platform explicitly designed for podcasters like you who want to streamline their sharing process and maximize their audience reach. Why Skill Piper? Imagine updating all your listeners across every platform with just one link. Skill Piper allows you to create a single, shareable link that directs your audience to your podcast on their preferred platform. No more cluttered messages or posts with multiple links. One link is all it takes! Here’s What You Need to Know: - Totally Free: There’s no cost to use Skill Piper. It’s 100% free. - Easy to Set Up: You only need your Podcast Apple ID to create your unique link. For example https://skillpiper.com/share/your_podcast_apple_id - Maximize Your Reach: With just one link, you make it easier for your listeners to access your podcast on their preferred platforms, increasing your visibility and listener numbers. - Customize As You Like: We understand that every podcast is unique. - SEO Optimization: Our links are SEO-friendly, helping improve your podcast’s visibility on search engines. Let us know if you need any customizations or personal touches to your link or its landing page. I'll be more than happy to accommodate your specific needs to make sure your podcast shines. We’d love to hear your thoughts and feedback. How can we improve SkillPiper to serve the podcasting community better? What features would you like to see next? Looking forward to your comments and discussions!

Visit product View on Hacker NewsMay 14, 2024

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Launch Intel predictions

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

87%87% 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.

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

76%76% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

62%62% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: personal · 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: pipe, io · Missing: https docs, excited, just released

30%30% 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

8%8% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: introduce · 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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