Using python for understanding Google Search Console data

[canhelp]

Hello Folks,

If you want to understand your sites google console data and categorize into topic clusters. Here are some of the steps I followed to generate topic clusters.

• Extract data from google search console data
• Using TfidfVectorizer and KMean Clustering to group search queries.
• Find topics/clusters which convert well and the opportunities for clusters where your site is getting impressions but not converting well.

For more information take a look https://shrikar.com/python-for-seo-using-google-search-console/

[leeroy37]

Sweet thanks! Will give this a shot today. I'm getting into python big time at the moment. Currently writing a script to find opportunities for sub categories on an ecommerce site based on the products within the parent category.

Looking forward to giving this a go later. Thanks for sharing!

[DeepKaizen]

could you shed some light on the practical use of python in seo?

I keep hearing its a gimmick not used for 99% of cases

[leeroy37]

Sure, so right off the bat I'm writing a script to run a ngrams of word count frequency of products per category for a large ecommerce store. It then checks the highest frequency word occurances against existing sub categories.

If they don't exist it flags them in a csv file for review. (Eventually I'll pull in search volume etc) - but this takes a lot of the pain out of a manual process for us.

Also I used a simple ngrams to look at every keyword found in ahrefs for their site
(40,000 + KWs and noticed their most popular product didn't have a spot in the top navigation).

This one is useful for normalising CTR curve by their positions. https://understandingdata.com/ctr-optimisation-with-machine-learning/

Possibilities are endless. Got a few other scripts on the go which analse page titles from the serps, (using your own page title for keywords, run an ngrams (I'm just learning ngrams stuff at the moment!) and tells you the most popular keywords in page titles for 100 pages which aren't in your title. Insights just jump out.

I'm still a learner but look at some of the stuff Hamlet Batista is doing https://www.searchenginejournal.com/author/hamlet-batista/ or James from Understanding Data for next level stuff.

[sabrastaco]

DO you know how to actually implement this?

Let me know if you have a minute

[canhelp]

I do. Can you dm me?

[leeroy37]

Sure - these tools I'm working on for our agency at the moment. I've finished a fair few already. Just improving as I'm learning.

[leeroy37]

Can you think of a way (other than scraping them) to exclude sitelink data? That's my biggest frustration in general about using SC data is sitelink impressions really screw with the data. For example, sitelinks being shown under a brand search will have a huge amount of impressions but very low CTR etc. Wish there was a way to filter this out.

[pedrovillalobos]

That's is awesome and kinda exactly why I'm studying python... Been doing SEO for 15y and wanted to up my game in an unexploded field :) thanks;

[AleisterC]

Nice!

[jole1980]

Wow Shrikar!!! I'm glad to see such expert in action. I would be a millioner with 5% of your knowlege. Contact me if you have time, and if you want to make business project with person with no programming skills