4 min.
6 reasons you should connect your SEO data to a data warehouse
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6 reasons you should connect your SEO data to a data warehouse

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The advent of Law 25 and its many effects on digital marketing is forcing marketing professionals to facilitate the customer journey to the maximum extent possible.


From now on, having a deep understanding of customers is even more strategically necessary and important. This involves having a 360-degree view of customers, in addition to performing a comprehensive analysis of the marketing channels you’re using. The solution? Break down data silos and develop an omnichannel strategy. One that includes SEO data!
 
Data warehouses were created for just this purpose—to unify 360 data. For example, thanks to warehouses it’s now possible to save all SEO and SEM data in the same place in order to obtain a more general understanding of how you’re performing in search engines.

 

Why is Google Search Console data important? 

The data presented in Google Search Console is essential for properly activating any SEO strategy. That’s why this data is highly valued by SEO experts around the world, who use it to develop their analyses and recommendations.

Basically, your Google Search Console account contains a lot of essential information on your site’s presence and organic performance, and this information is directly based on Google search results. In particular, you will find keywords entered by users, the number of clicks to your site from these keywords, impressions, position and click-through rate. This is where the power of Google Search Console’s data resides—this direct connection with Google lets you see the true organic performance of your marketing efforts.

 

The advantages of adding your Google Search Console data to a data warehouse 

1. Establish an omnichannel strategy 

Unifying all your data in the same place gives you a more complete and overarching view of your various channels. This 360-degree view lets you activate a more effective omnichannel strategy for reaching your business goals. It then becomes easier to understand the relationships between various channels, leveraging them to improve your overall performance.
 
To use a concrete example, a data warehouse can facilitate comparative analyses with data from Google Ads to evaluate SEM. By obtaining a view of both your SEM and SEO performance, you can rally your SEO and SEM efforts and refine your overall strategy when it comes to search engines.

 

2. Eliminate the time limit for data 

Data in Google Search Console is limited to the past 16 months. It is therefore, for instance, impossible to go back five years in the pastWithout a data warehouse, it’s harder to obtain an understanding of the results of an SEO strategy spanning a number of years, and therefore harder to determine the best options to explore in the future.

It’s kind of like climbing stairs in the dark with a torch: you can see a bit behind you, a bit in front, and that’s it.

By investing between 2 and 3 cents per gigabyte per month on BigQuery (the price as of the time of writing), the data you extract and warehouse today will be available forever, or for as long as the data warehouse remains available. You can even extract all the data from the warehouse and instead save it outside the cloud, in a CSV file on a number of hard drives.

By analyzing historical data, you can mine data to extract knowledge that will inform your future decisions.

It’s like using the past to get a glimpse of the future.

Or like dropping the torch and turning on the lights.

So take note! The data you are extracting is not retroactive. This means it’s essential to establish a connection with a data warehouse as quickly as possible in order to start collecting it for the long term.

 

3. Reduce constraints related to the limit on extracted data thanks to BigQuery (or even eliminate them)

Exporting data directly from Google Search Console is limited to 1,000 lines of data per export, which can sometimes be very restrictive. If you extract this data via the Search Analytics API to a data warehouse, the limit is instead 50,000 lines per day, which is generally enough to perform interesting, impactful analyses.

But there is one exception: with a direct connection from BigQuery, there is no technical limit on how much data can be extracted per day! The only limitation is your BigQuery account’s collection capacity, which is determined by the investments you have made in that account.

 

4. Simplify omnichannel reporting  

By unifying data in a warehouse, it’s easier to connect that data directly to visualization tools for your dashboards. This means it’s no longer necessary to connect several data sources to your dashboards. Just plug in your data warehouse and you’re all set!

Coming back to the BigQuery example, it can be connected directly to Looker Studio (formerly Google Data Studio) to produce dynamic reports that include the performance of all your channels in the same window.

 

5. Fully own your data 

Another advantage of exporting data to a warehouse is that it means you completely own it, and can therefore collect it. With no constraints on data exports or any limits on data history, for a few dollars a month you can be free to manipulate your own data as you wish. It’s a bit like having a CSV file, but one that potentially has billions of lines, which you can filter, reorganize, pivot, attach, change, delete, etc., however you want.

The data belongs to you, and you can do whatever you like with it.

 

6. Easily automate the warehousing process of Google Search Console data with BigQuery 

Today there are many connectors that can be easily installed to automatically and continuously collect Google Search Console data for the purposes of adding it to a data warehouse. The most well known and the easiest to integrate is the native Google Search Console connector to BigQuery, which was integrated directly into GSC in February 2023.

We’ll explain the process.

 

How do you connect Google Search Console (GSC) data to BigQuery?

To get started, go to Parameters located on the left-hand side of your Search Console property:

image (3)

Next, click on “Bulk data export”:

Capture d’écran, le 2023-08-03 à 15.58.07

There are two steps for you to follow.

 

Step 1 - Follow the first step in the link provided to prepare your cloud project 

image (4)-1

Start a new bulk data export - Search Console Help 

Step 2 – Complete the requested fields 

Project ID: at your discretion.

Name of data set: leave the default value search console

Note: If you have more than one GSC property, use a suffix to help you identify the export. For example, searchconsole_adviso_ca and searchconsole_adviso_com would let you identify the exports from adviso.ca and adviso.com.

Location of data set: to be determined with your technical and legal teams. If you have any doubts, a Quebec-based company would generally choose Montreal.

 

Step 3 – Click on “Continue,” then “Yes”

After 48 hours, your data should appear in BigQuery.

Finished! You have successfully connected your Search Console data to BigQuery.

What about other types of data warehouses?

We have used BigQuery as our example for this article, but there are many other solutions for warehousing data for the purposes of analytics. In fact, there are a dizzying number of AI, machine learning and warehousing solutions.

A quick look at the page The 2023 MAD (ML/AI/Data) Landscape might just give you the spins.

If we had to name a few, we’d mention Snowflake, Amazon RedShift, Azure Synapse and Databricks as good examples of warehouses that have their own particular advantages and disadvantages and which could be suitable for different situations. However, these other warehouses lack a native connection with Google Search Console. You therefore need to use the GSC API to export data to them, while keeping in mind the additional limitations of the API compared to native exporting.

If you would like to avoid the API’s limitations and keep your Snowflake warehouse, for example, you would need to use the native GSC export to BigQuery, then transfer the data from BigQuery to Snowflake.

A little work for big results

Data warehousing comes with many business advantages, and the work you need to put into it is minor in comparison. If you’re familiar with the 80/20 rule and like basing your decisions on the ratio of amount of work to results, then this one's for you!

The earlier you start collecting data, the earlier you can start getting interesting insights to activate effective and sustainable SEO strategies.

Get in touch with your marketing experts and start the process!