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Productonboarding.com – Mobbin for SaaS product onboarding

Hacker News

Productonboarding.com – Mobbin for SaaS product onboarding

Hey Hackernews, Eric here! Wanted to share a new website we just built called productonboarding.com (Next.js and RSC). The site has screenshots and videos of product onboarding from companies like Figma, Notion, Framer, and more. It’s sort of like Mobbin for web-based product onboarding. We build a lot of product onboarding at our startup Frigade, and over the last year we’ve put together an internal library of hundreds of product onboarding examples that we refer to all the time with customers. It helps them find and copy patterns that work at other companies so they don’t need to create net new experiences or A/B test their way into the best performing pattern from scratch. Given it's been so useful to us, we decided to open it up to the world. We bought productonboarding.com and have started adding examples from our collection and made them browsable and sortable. We’re planning to add new examples weekly. Hope this is helpful to any of you who are currently thinking through building new onboarding experiences. Would love any ideas and feedback. Thanks!

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
93%93% 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: new, open · Missing: mac, agents, macos
87%87% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
67%67% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: video, way · Missing: mobile apps, ios, personal
51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: saas · Missing: arr, mrr, revenue
20%20% 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.

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