Keyword Optimization (The Data-Driven Method) w Graphext + Deepnote + Adwords [Video]

To improve our SEO, we built a data-driven method to analyze keywords inside the content of top-ranking Google search results. Starting with a single search term, our technique uses web scraping + NLP techniques to find specific keywords that are already proven to boost the rank of similar pages.

‍https://www.graphext.com/post/data-driven-seo-a-keyword-optimization-guide-using-web-scraping-co-occurrence-analysis-graphext-deepnote-adwords

What do we need?
– 1x Blog Post / Article / Digital Content Piece (we’ll be optimizing this).
– 1x Initial search term.
– The ability to run a Deepnote (Python) notebook (we’re supplying the notebook).
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What are we going to do?
1. Use Google Adword Keyword Planner to get a list of search queries we want our article to be listed under.
2. Use Python to retrieve the top 10 search result URLs for each of the search queries.
3. Save this as a dataset with one URL per row.
4. Upload the dataset to Graphext.
5. (5 clicks) Use Graphext to scrape the text from each URL and model the co-occurrence of keywords in all this text.
6. Find new, directly relevant keywords.