I

I build most beautiful SEO checklist tool

Hacker News

I build most beautiful SEO checklist tool

Hey HN! Super excited to share SEO-Checklist.app with you today! When I launched my e-commerce store a year ago, navigating the world of SEO felt super overwhelming. As a developer with no SEO background (except technical bits), I needed a simple tool to track progress but couldn’t find one that clicked. So I built https://seo-checklist.app – a free, easy-to-use tool to simplify your SEO journey. Here’s what it offers: Unlimited Checklists: Organize your SEO workflow, track progress, and hit your goals faster. Automatic Site Checks: Let scans do the work! Validate and check off tasks automatically. Step-by-Step Instructions: Learn as you go with clear, actionable guidance. Keyword Position Tracking: Stay updated on your rankings with daily position insights. I’d love to hear your thoughts and answer any questions you might have.

Visit product View on Hacker NewsDec 19, 2024

Actual performance

3points

4comments

Did not reach leaderboard

Launch Intel predictions

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

80%80% 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: tasks · Missing: mac, agents, macos

67%67% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal

54%54% 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

47%47% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: excited, io · Missing: https docs, just released, exist

45%45% 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

15%15% 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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