BigQuery Hack to Track Total Rankings in Data Studio

Tracking keywords make a whole lot of sense for SMBs and a few mid-market companies, however as we scale our content material advertising we want to look past monitoring a small set of key phrases.

Clients need to see a birds-eye view of how their key phrase set is performing. However, search engine optimisation professionals hadn’t actually figured one easy approach to obtain this utilizing present instruments.

In this column, you’ll study a BigQuery hack to observe complete rankings with Data Studio.

You’ll additionally get entry to a free Data Studio template for visualizing BigQuery knowledge. Ready? Let’s soar proper in.

The Google Sheets Problem

Typically, I present shoppers the overall quantity of key phrases they’re rating for, damaged out by place. Semrush’s natural analysis software has an important visualization for this.

This chart will be filtered to present solely sure positions and solely sure sections of the location, which is helpful.

However, this chart alone has many filtering and reporting limitations that could possibly be solved by means of Data Studio.

Semrush and different SEO tools have related charts and most of them join to Data Studio. However, none of them have a chart in Data Studio that permits us to view all rating key phrases damaged out by month.

They solely allow us to see tracked key phrases or at present ranking keywords for that given month.

search engine optimisation professionals have tried getting round this hole by downloading the brand new checklist of key phrases each month and including them to Google Sheets as their connector to Data Studio.

So what’s the issue with this?

Adding massive units of information to Google Sheets can take a really very long time. Once you get to the a whole lot of hundreds of rows of information, Google Sheets might even freeze or crash your browser.

The greatest burden right here is time.

The BigQuery Fix

BigQuery permits us to add exported knowledge with none modifications and sync that straight to Data Studio in a fraction of the time.


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The draw back is that you just nonetheless at present have to export your complete rating key phrases each month, however bypassing Google Sheets will find yourself saving a ton of time in the longer term.

Disclaimer: BigQuery has a paid element. However, it’s pennies till you attain a TB of information. The value is nominal and really a lot definitely worth the time misplaced ready for Google Sheets to load, praying it received’t crash.

How to Setup Your First BigQuery Project

Getting began is sort of straightforward. The solely prerequisite is that you have already got a Google account of some variety; even a Gmail will work.

I do know working in the Google Cloud Platform will be fairly intimidating. There are a whole lot of superior options and it’s not probably the most intuitive platform.

However, I’ve included a screenshot for each step of the method to assist information you thru the setup.

If you get caught, please don’t hesitate to attain out to me in the feedback under.


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1. Log in to Google Cloud Platform and Create a New Project

Create new project.Name the project.

Go to Google Cloud Platform, create a brand new venture, and assign a reputation and placement.

2. Go to BigQuery

Go to BigQuery.

3. You might have to arrange billing for those who haven’t carried out this already.

4. Once you’re prepared to go, select to Create Dataset.

A fast tip: this should include solely letters, numbers, or underscores.

Create dataset.Fill in dataset information.

5. Go to new dataset.

Go to dataset.

6. Create a brand new desk:

Under supply, change the “Create desk from:” to Upload and choose your CSV file. This must be your first set of key phrase rankings.


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Under Destination, give your desk a Table identify and be sure you use this identical desk identify for each knowledge add. In the instance under, I named my desk “cardinal” however you possibly can identify your desk no matter you need. I like to recommend utilizing your web site identify in order that it’s straightforward to establish later.

Under Schema, be sure to choose the checkbox beneath Auto detect.

Select the blue “Create desk” button on the backside.

Create table.
Steps to create a table.

7. Now, you possibly can add extra knowledge.

Select Create Table once more.


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Upload your second set of information. For instance, in case your first add from Step 6 was February key phrase rankings, this step you’ll add March key phrase rankings and subsequent month you’ll observe these steps and add April key phrase rankings.

Under Destination, give your desk a Table identify and be sure you use this identical desk identify for each knowledge add.

Under Schema, be sure to choose the checkbox beneath Auto detect.

Select the blue “Create desk” button on the backside.

Important: Under Advanced choices, for the write choice dropdown, choose “Append to desk.”

Add more data.

Repeat step 7 for each new month’s set of information.


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Okay, the laborious half is over!

Each month going ahead, as a substitute of importing your knowledge to Google Sheets, you possibly can observe step 7 to replace your knowledge.

Free Data Studio Template to Visualize BigQuery Data

Bigquery data studio template.

I’ve created a free Data Studio template that requires little or no setup in order for you to get began.

Page one of many template contains the directions under, however with screenshots. Feel free to skip straight to the template!


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How to Setup the Template

Open the template.

Duplicate the report by clicking the duplicate button in the highest proper of the report.

You will want to create a brand new knowledge supply and join it to your BigQuery venture. Click “Create New Data Source.”

On the connection choices, choose BigQuery.

When including the brand new knowledge supply, create a customized area to type place distribution. This will also be carried out after you join the information supply.

Create a custom field in data studio.

Name this area, “Position (Custom)” and replica the method under into the sector.


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    WHEN Position <= 3 THEN "Top 3"
    WHEN Position <= 10 THEN "Top 10"
    WHEN Position <= 20 THEN "Top 20"
    WHEN Position <= 50 THEN "Top 50"
    WHEN Position <= 100 THEN "Top 100"

Click Done.

From right here, the report must be totally up to date along with your knowledge.

That’s it! I hope this BigQuery hack helps you observe complete rankings in a approach that's extra visually attention-grabbing and scalable.

More Resources:

Image Credits

All screenshots taken by writer, April 2021

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