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Data Studio is a free Google product that has been around since 2016. It allows you to draw from different data sources in order to produce custom reports, dashboards, and data visualizations.
In addition to plugins for certain data sources, such as Google Search Console and Google Analytics, any data accessible in a Google Sheet can also be used to provide a more complete picture of the KPIs for your business or your website.
Like other Google products in Google Drive, Google Data Studio reports can be easily shared for collaboration with contacts who have a Google login. They follow the same sharing principles and rules as other documents in Google Drive, which means, for example, that reports can also be made public for read-only viewing by anyone who has the link.
Data Studio allows SEOs to view data available elsewhere in new ways that reveal trends we couldn’t see before.
One example of a way to get a new look at data was provided earlier this year by François Goube, CEO and founder of OnCrawl. By examining differences between two periods–a functionality that is not available in Google Analytics but is easy to set up in Data Studio–, François points out that we can find extremely useful information.
He walks us through the example of pages who appear twice (or more!) as often in the SERPs in the past three months compared to the previous three months. As these pages are already ranking, and already seeing a huge increase in visibility, optimizing them can yield massive payoffs. Data Studio allows the SEO to spot this type of opportunity.
More recently, Aleyda Solis, the award winning International SEO Consultant, took a look at how to overcome the same difficulty–the inability to compare two periods–with regards to Google Search Console’s performance metrics. By providing a new Performance Report using only the information drawn from the Search Console, Aleyda is able to create a dashboard that provides actionable insights. This is a vast improvement on the Performance Report available in Google Search Console, which allows us to monitor, but not predict, compare, or identify areas for improvement in performance metrics.
Aleyda gives a few concrete examples of use cases, but there are countless others. For example, you can use Data Studio to:
The examples above illustrate the advantage of Data Studio when using a single set of data. However, the greatest advantage of Data Studio is perhaps the ability to use multiple sources of data in the same report.
Why are additional data sources so important for crawl data? One of the difficulties with crawl data is how it can exist in isolation from user behavior and from indicators of actual website performance. This is why OnCrawl already incorporates many of these analyses when you connect third-party datasets containing information on user and bot behavior, rankings, backlinks, revenue, and so on.
Data Studio also allows you to overcome that difficulty. With Data Studio, you can do deceptively simple things, like present performance data and crawl data on the same page. And Google continues to improve the ability to combine data sources, creating blended datasets that merge data from two separate sources. This feature continues to develop, as indicated by the November 2018 product update, and now includes the ability to create calculated fields based on blended data.
Blending data in Google Studio allows you to create reports that examine the relationship between crawl data and additional behavioral indicators on your site. Below, we’ll look at just one of many use cases.
Puzzling out Google’s behavior and optimizing ranking factors to win the best positions in search results can become so consuming that it’s easy to lose sight of the main objective of search marketing: to use inbound visitors from online searches to increase profitability.
One of the best measures of profitability are Google Analytics’s Goal Completions, particularly if you’ve set up proper goals for your site. Depending on your site, every goal completion can provide you with a qualified lead, rather than just a visitor searching for a quick “how to” or a definition in one of your old blog posts. Since we’re definitely more interested in the lead than in the visitor, tracking the characteristics of landing pages that lead to goal conversions will give us key information as to what really works on the website and what doesn’t.
To blend crawl and analytics data in Data Studio, we’ll first need two data sets–one for crawl data, and one for Google Analytics–that share a unique “join key” we can use to link them. The best key to use is the URL.
From the OnCrawl Data Explorer, begin by creating a report containing columns for page characteristics you would like to analyze.
This data must include the URL of the page, since that is what we’ll be using as our link key, and can include crawl metrics such as:
And any other metrics you want to track.
If you’ve connected logs or backlink data in OnCrawl, you may also want to include columns for:
Export this report as a CSV file by clicking on “Export data”.
Upload the CSV to Google Drive and convert it to a Sheets document. You can then use the Sheets connector to add this sheet as a data set in Data Studio.
Connect your Google Analytics account as a data set in Data Studio. As Landing Pages are listed as relative paths, you will need to add a calculated field to obtain the full URL of landing pages to use as the link key at this time.
After choosing the account and properties when creating the Analytics dataset, you will find the “Fields” step. Choose “+ Add a field” at the top right. Name the field “Full URL”. Enter
CONCAT(“https://www.example.com”, Landing Page)
In the formula box. (Replace “https://www.example.com” with the address of your site.)
To blend datasets, you will need to create a chart in a report. When you create a new blank report, you’ll be prompted to add datasets. Add the Analytics and the Crawl datasets that you have just created.
Add a chart by clicking on the type you would like to create and drawing a rectangle where you would like the chart to appear:
In the Data tab on the right, click “+ Blend data”.
Change the “Join key” dimension for Analytics to “Full URL”. You will need to use the search function to find this field. Add the metric “Goal Completions” as well as any other numerical (blue) fields you might want to use in this blended dataset.
Click “Add another data source” and choose your crawl data. The “Join key” will be listed as Missing. Replace it with the URL field. Add the numerical (blue) metrics you want to be able to compare to Goal completions using this blended dataset.
When you click “Save” in the bottom right, this will most likely cause an error. That will be resolved when you reassign available fields to the different elements of the chart.
Assign fields to the different elements of the chart.
In this case, we’ve plotted goal completions versus the number of follow inlinks (links to the landing page) to view whether or not pages convert. We’ve also weighted the data by number of page views, and excluded the home page, since it performs very differently from other pages on our site.
You can then use the Style tab to modify how the chart is presented; in this case, we’ve chosen colored bubbles.
The trend between the number of inlinks on a landing page and its ability to lead to a conversion is visible in this chart. Using other charts and tables to create a full report, you can track the influence of other crawl metrics on a landing page’s ability to convert.
Although a Data Studio connector is not yet available for OnCrawl, you can still use any crawl data in Data Studio.
Export recent crawl data from the Data Explorer. You should add as many columns of useable information as you expect to use, for every known URL (not necessarily just the fetched ones).
Export this data to a CSV that can be converted to a Google Sheets document.
The advantage of using the Google Sheets connector for your crawl dataset is that it will (sort of) allow you to update your data by replacing old crawl data with new crawl data.
Following a more recent crawl, perform the same export as before. Replace the contents of the current spreadsheet with the contents of the new CSV.
In Data Studio:
Your charts will be updated with the new data.
Data Studio is an exciting, but in some ways still primitive tool. Keep in mind that:
Finally, the drag-and-drop interface means that Data Studio is more accessible than not, but if you’re one of those people like me who enjoys tweaking the code and customizing to perfection, you may find yourself frustrated.
Here are the main takeaways when using OnCrawl with Data Studio: