Re

Releasing my own SEO tools, free of charge

Hacker News

Releasing my own SEO tools, free of charge

Hello HN! Being a software engineer and an SEO guy I wrote a heap of tools and scripts to make my life easier. Now I've decided to share some of them with the community, and made a small site where I will be publishing them. They are all completely free (yes, free forever) and you don't even need to sign up for the site. Just use the thing as you like, no limits. Currently you can access 4 instruments: - Backlink retriever - Thin/weak content analyzer - Traffic trend analysis - Visitor list retriever I am planning on releasing more free tools with time, and trying to stay original by creating something unusual and valuable at the same time. Tell me what you think and whether you have any ideas or requests. You can find the project here: https://seosupertools.com

Visit product View on Hacker NewsSep 3, 2018

Actual performance

17points

4comments

Made the leaderboard

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

67%67% 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.

Hacker NewsStrong engagement from HN community · Strong signals: lua, ide · Missing: https docs, excited, just released

53%53% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos

27%27% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

11%11% 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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