I made an SEO checker to fix frustrating issues in minutes, not hours

Hacker News

If you have any issues optimizing your website. Seototal will help you. A while ago I was trying to improve my SEO on my first startup, That was when i realized how clunky and overcrowded most SEO tools were I used were, Ahrefs and Semrush initially. I built it to be lightweight and focus on the basics. It checks on page and technical issues to output straight forward reports with quick and helpful knowledge bases that will help you fix your SEO basics fast. The website is still in early stages and is actively being improved. So I'm open to any here any issues or feature recommendations you have. Thank you for your time.

Visit product View on Hacker NewsJul 11, 2024

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Actual performance

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Launch Intel predictions

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

64%64% 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, podcasting

51%51% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

45%45% 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

42%42% predicted probability of success on AppSumo, 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

33%33% 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: active · Missing: arr, mrr, revenue

13%13% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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