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SEOCopilot – Find keywords easy to rank and that converts

Hacker News

SEOCopilot – Find keywords easy to rank and that converts

No magic here, just data science. Around 80% of web content yields no conversions. Our goal: To identify, among millions of search queries, those that lead to conversions (such as purchases, contact form submissions, or app downloads). Technologies involved: Google Search Console, Transformers, Clustering, Semantic Similarity. For more details, visit: https://www.seocopilot.fr/blog/us/conversion-driven-seo Now, you can write content on promising keywords (easy to rank) and stop wasting your time, energy, and money writing useless content. The product is free for everyone! Why? To build trust: We are relatively unknown. To collect data (We need your data to make conversion predictions). What do you get for free? A list of keyword opportunities sorted by traffic potential: We use modeling to predict where you could rank, the expected traffic, and the conversion rate. Is it perfect? No! But continuous improvement is our mantra. Your conversion rate will increase with SEOCopilot. Privacy: Your data is not shared. We can store your data on your servers if necessary. In the future, if we need to enhance our models by aggregating your data, we will clearly request your permission. For everyone? It works well when you have more than 300 webpages. It works well when we collect a substantial amount of conversion data. Will it work without tracking your data? Yes and no: We perform extrapolations to estimate the conversion rate of your content if we don't collect your conversions. However, collecting real data significantly improves predictions. Projected roadmap: Improvements in predictions with a feedback loop (position estimation, impressions, clicks, and conversion rate). Who are we? Sébastien MOUGEL - CEO AI/Software Engineer https://www.linkedin.com/in/smougel/ Want to test it? Please reach out to me at: sebastien@beyond1.fr

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
82%82% 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 NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
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.
Product HuntUnlikely to reach the leaderboard · Strong signals: model, google, models · Missing: mac, agents, macos
45%45% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: google · Missing: mobile apps, ios, personal
24%24% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
17%17% 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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