Use Of Google Search Console’s Bulk Data Export To Google BigQuery

Use Of Google Search Console’s Bulk Data Export To Google BigQuery

Google Search Console is a free service provided by Google for monitoring, maintaining, and troubleshoot site’s presence in Google Search results.

Search console provides tools and reports for the following actions:

• Confirm that Google can find and crawl your site
• Fix indexing problems and request re-indexing of new or updated content
• To view Google Search traffic data for your site:
• Receive alerts when Google encounters indexing, spam, or other issues on your site
• Show which sites link to your website

Break Free From Data Constraints With BigQuery Bulk Exports

Bulk data export was meant for websites receiving traffic to tens of thousands of pages and/or from tens of thousands of queries.

Google Search Console (GSC) offers absolutely great insights into your website’s performance in Google search results, yet the platform has inherent limitations in how data can be analysed and utilized. Exporting this data to BigQuery removes these limitations and opens a wealth of new opportunities you never thought of for deep, really custom analytics.

Benefits of GSC Data to BigQuery Export: Sending data from Google Search Console to BigQuery transforms your SEO and marketing efforts by providing a scalable, flexible platform for your data needs. This level of access enables you to conduct thorough, granular studies on every aspect of your site’s search performance.

Data Volumes

• Most of the reports in GSC enable you to export up to 1000 rows
• You can get up to 50,000 rows via a Looker Studio integration
• With the API, you can get up to 50,000 rows, enabling pulling a few more elements beyond the performance data: URL Inspection, sitemaps, and sites data.

Data Retention

Data retention is the practice of storing data for a specific period of time, which can be done for a variety of reasons, including legal compliance, business continuity, and data analytics.

Google BigQuery allow unlimited data retention, which allows SEO pros to perform historical trend analyses that are not restricted by the 16-month data storage limit in Google Search Console.

As a storage solution, BigQuery enable stocking data for as long as you wish and overcomes this limitation.

The ability to retain and access unlimited historical data is a game-changer for SEO professionals due to comprehensive long-term analysis, seasonal and event-driven trends, customized reporting, improved troubleshooting, and adaptability.

Data Caveats

Data caveats are anything that should be flagged about the dataset you are using. This includes data limitations, notes, and context. Keeping caveats in mind helps in guiding interpretation so that you have a more thorough understanding of what the data is telling you.

Use of Google Search Console’s bulk data export to BigQuery enables creating two main tables, which are searchdata_site_impression and searchdata_url_impression.

Advantages of setting up BigQuery bulk exports:

• Joining GSC Data with other data sources
• Run complex calculations/operations using SQL
• Anonymized Queries

Developing Expertise Beyond SEO. Get familiar with Google Cloud Platform, BigQuery, and SQL on top of your GSC knowledge. Starting a bulk data entails carrying out tasks in GSC, but also in Google Cloud.

SQL-Based Platform Requiring Specific Expertise. BigQuery need SQL for accessing and making the most of your data. You need to make SQL queries or have someone in-house to do it for you.

URL Impressions Contain More Anonymized Queries. Consider the difference in anonymized query volume between the searchdata_url_impression table and the searchdata_site_impression table. Like the GSC interface, some queries for particular URLs in specific countries might be so infrequent that they could potentially identify the searcher.

Potential Costs. BigQuery is billed based on the amount of data stored in a project and the queries that you run. The solution has thresholds from where you start to pay, potentially each month. It might then become costly, but it all depends on the amount of data exported and queries you run to access and manipulate it.

Queries Data

• Query multiple pages at once

In BigQuery, running a single SQL query to get metrics for all pages (or a subset of pages) without having to click through each one individually.

• Traffic seasonality report

Comparing the performance metrics by season for identifying trends and optimizing campaigns accordingly.

• Bulk analysis across multiple sites

Managing a brand with more than one website enables you to look at clicks across all these sites at once

• Click-through rate (CTR) by page and query

Instead of just looking at the average CTR, you could calculate the CTR for each page and search query.

Conclusion

The built-in bulk export feature from Google Search Console to Google’s BigQuery provides a more robust solution for data analytics in SEO.

Need to develop expertise in Google Cloud and SQL, and potential costs associated with BigQuery storage and queries are certain limitations associated with Google BigQuery.