Page Level Query Analysis at Scale

The author’s views are entirely his or her own (excluding the unlikely event of hypnosis) and may not always reflect the views of Moz.

The YouTube playlist referenced throughout this blog can be found here:6 Part YouTube Series [Setting Up & Using the Query Optimization Checker]

Anyone who does SEO as part of their job knows that there’s a lot of value in analyzing which queries are and are not sending traffic to specific pages on a site.

The most common uses for these datasets are to align on-page optimizations with existing rankings and traffic, and to identify gaps in ranking keywords.

However, working with this data is extremely tedious because it’s only available in the Google Search Console interface, and you have to look at only one page at a time.

On top of that, to get information on the text included in the ranking page, you either need to manually review it or extract it with a tool like Screaming Frog.

You need this kind of view:

…but even the above view would only be viable one page at a time, and as mentioned, the actual text extraction would have had to be separate as well.

Given these apparent issues with the readily available data at the SEO community’s disposal, the data engineering team at Inseev Interactive has been spending a lot of time thinking about how we can improve these processes at scale.

One specific example that we’ll be reviewing in this post is a simple script that allows you to get the above data in a flexible format for many…

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