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I built an automated SEO Keyword Research tool

Hacker News

I built an automated SEO Keyword Research tool

Ahrefs and SEMrush are the big names in keyword research, but they overwhelm you with data, making it hard to determine your next steps. I wanted to simplify the process to just one click. So, I created a system that scans your homepage, performs keyword research, and delivers a list of target keywords in your niche—ranging from easy to rank (low traffic) to moderately difficult (higher traffic). I also developed an AI content writer with industry-leading humanized outputs, ranking the lowest on AI detection algorithms. With these two tools, you can handle 80% of your startup's baseline SEO in just a few clicks.

Visit product View on Hacker NewsOct 21, 2024

Actual performance

2points

1comments

Did not reach leaderboard

Launch Intel predictions

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

92%92% 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.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

56%56% 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

43%43% 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

38%38% predicted probability of success on Product Hunt, 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

24%24% 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

18%18% 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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