Creating video content takes time and budget, so understanding how it performs is critical.

YouTube’s native analytics in YouTube Studio are robust, but they’re locked behind account access. That can make reporting difficult — especially when you need to share data or don’t have direct login access.

Moving that data into Google Data Studio (formerly Looker Studio) makes it easier to analyze and distribute.

With Data Studio, you can:

• Pull YouTube data into reports you already use.
• Schedule automated updates for stakeholders.
• Customize dashboards around the metrics that matter.
• Track performance without relying on backend access.

Here’s how to pull your YouTube analytics into a Data Studio report.

Using a template or starting from scratch

You have two options when setting up a YouTube report in Data Studio.

• If you want something quick and easy, you can use Google’s YouTube Analytics template from their template gallery. It’s a great place to start because it provides a clean, well-designed report with foundational metrics and puts you in a good position to understand which metrics are available. But know that this template has problems you’ll need to fix, which I’ll discuss below.
• The other option is to create a report from scratch, which is a great choice if you already have a report you want to add a new YouTube Analytics page to, or if you just want to learn how to use Data Studio.

The information below will help you do both.

Your customers search everywhere. Make sure your brand shows up.

The SEO toolkit you know, plus the AI visibility data you need.

Start Free Trial

Get started with

If you’re not the YouTube account owner

If you’re setting up this report for a client, or if you’re not the owner of the YouTube account, you’re going to run into an issue where the YouTube account doesn’t show up as a usable source in Data Studio. Here’s how to get around it:

• Go to YouTube Studio settings > Permissions, and give Manager permissions to the account email that you’re using in Data Studio.
• Get the Channel ID from the channel’s YouTube URL.
• Add a YouTube connector to Data Studio, go to Advanced, and paste the Channel ID.

You should now have access to that YouTube account.

Using the Data Studio YouTube Analytics template

From the Data Studio home page, click Templates > Template Gallery. Under the category dropdown, click on YouTube Analytics.

Clicking this will create a brand new Data Studio report that’s mostly ready to use. It loads up with sample data from the Google Analytics YouTube channel. Click the button at the top that says “Use my own data.”

The first time you set up a report, you need to authorize access to your data. Click the Authorize button.

Choose the Google Account connected to your YouTube channel, and then you’ll see any connected channels in the dropdown at the top of the page.

You’ll notice that the data doesn’t change when you select a site here. That’s because this dropdown is connected only to the other dropdowns next to it, not any of the charts on the page.

To update everything else on the page, click the Edit and Share button.

If this is the first time using Data Studio, you’ll also need to do some basic account setup.

Then click the Edit button at the top of the page.

Now you’ll need to add your YouTube channel as a source. Click the Add data button and then search for the YouTube Analytics connector.

If the Google Account is the owner of the YouTube account you connected to this Data Studio report, it’ll show up in the Channel section as an option. 

Your main YouTube channel will be in the My Channel tab, and other channels are in the All Channels tab, as shown below. 

If you don’t own the channel, see the section above to connect other channels that you don’t own, but have access to.

Now you’ll be able to change the data source on any charts on the page. Simply click a chart, and you’ll see the data sources available to you in the right Properties panel.

You can change the source of all of the charts on the page by selecting a chart, right-clicking on it, going to the Select menu, and then choosing “Charts with this data source on page” and then choosing your data source in the Properties sidebar.

You’re mostly done, but as mentioned earlier, there are some errors in this report that you’ll need to fix. The charts at the bottom of the report are using the wrong metrics.

I don’t know why Google hasn’t updated this template. It’s been like this for a long time, so I don’t know if they ever will. In the meantime, you’ll need to update the following.

Change:

• Likes from “Average Watch Time” to “Video Likes Added”
• Subscriptions from “Video Link” to “User Subscriptions Added”
• Dislikes from “Average View Percentage” to “Video Dislikes Added”

The charts in the Comments section are correct, so you don’t need to change anything there.

Click on each of the charts highlighted above, one by one, and change the metric in the Properties sidebar.

And now the report is finished and ready to use. Click the View button at the top of the page to view the report in a view-only format.

---

Copying a template into an existing report

Data Studio doesn’t support the ability to add or import templates into an existing report, but you can copy a page from one report to another. Follow the steps above to create a report using the YouTube Analytics Channel template, then copy it into another report.

To do that, go into Edit mode, select all (Ctrl+A or Cmd+A), and copy all (Ctrl+C or Cmd+C). Then, in your existing report, create a new page, and paste everything you’ve copied into the page (Ctrl+V or Cmd+V), or right-click on the page and select Paste.

All of the charts will likely come in broken, but you can easily update them using the tip mentioned earlier – right-clicking a chart, choosing Charts with this data source on page, and then choosing the correct source in the Properties sidebar.

Customizing your report

The YouTube template in Data Studio has most of what you need, but you can add much more.

There are some metrics you simply can’t get in Data Studio that you’d find in the official YouTube Analytics backend, such as revenue, how viewers find your videos, watch behavior, popular viewing times, device types, genders, and retention, so there are some big limitations, but there’s still plenty to work with.

To add more charts to your report, you’ll need to create more space at the bottom. In the menu, click on Page > Current page settings.

In the Style tab of the Current Page Settings sidebar, set the canvas size to something like 3,000 pixels. This will give you plenty of space to work with, and you can always shorten or lengthen it as needed later.

Now you can add many types of charts with a wide range of dimensions and metrics.

You can add multiple metrics to graphs to get the data you need for better analysis. You can also rename headers to clean them up, and make them look less cluttered.

You can pull in quite a lot of data. Here’s what’s currently offered:

Using Data Studio for ongoing YouTube reporting

Setting up a Data Studio report for YouTube is a great way to track your top-level metrics, and can be especially useful for monthly client reporting. It takes siloed, hard-to-share data from YouTube, and puts it into a clean, automated, centralized tool for easier decision-making.

You can also set up scheduling so that Data Studio sends automated PDF exports to your email.

That’s it. As you can see, it’s fairly simple to set up, but you can also add more advanced customizations to track many other KPIs.

Picture this: Your company relies on Data Studio for SEO reporting. 

It’s right before your next big meeting when you’re planning to present results… but Data Studio has an outage (again) and suddenly you have nothing to show. 

That’s embarrassing. And it happens more than it should.

It wasn’t even a year ago that I touted the benefits of Looker Studio (now Data Studio) for SEO reporting. Now the platform feels archaic compared to the agentic coding tools available today.  

Here’s how rigid SEO dashboards like those produced in Data Studio are holding you back and why code-driven SEO reporting is the only way to remain efficient and competitive.

The problem with Data Studio 

In the not-too-distant past, Data Studio was considered one of the best ways to customize SEO reporting. 

But things have evolved, and with new technology at our fingertips, Data Studio’s flaws are only becoming more pronounced. 

Here are some common issues that you may recognize when generating reports using Data Studio.

It’s easy to explode your dataset, and then everything breaks

You assume Data Studio can handle massive “Google-scale” data, but it’s buggy. For example, there are low limits on rows and fields, and even adding a few dimensions or joining multiple data sources can break the report at the worst times. 

You’re manually clicking through a slow interface

Every change in Data Studio requires manual updates. You’re clicking, refreshing and waiting to see whether it worked. That makes iteration painfully slow. Even with added AI features, they only address a small part of the report development workflow.

Relatedly, debugging reports is a nightmare

Whereas agents can simply scan files with code-based reports, in Data Studio, a user has to laboriously click around the interface. 

The API is weak

Like a lot of Google services, Data Studio isn’t built as an API-first platform. This is something Google got institutionally wrong decades ago. Not being able to manage the platform using external tools creates bottlenecks.

Despite its recent rebrand, Data Studio hasn’t become any more relevant — not with the technologies that are now in play for SEO reporting.

But it’s not just Data Studio. Really, what SEO teams are up against is the rigidity of any dashboard-based reporting tool. Now all that is changing.

Your customers search everywhere. Make sure your brand shows up.

The SEO toolkit you know, plus the AI visibility data you need.

Start Free Trial

Get started with

What’s changed: AI, APIs, and coding 

The shift away from rigid SEO dashboards is now possible because large language models are becoming more capable of generating reliable code, and APIs are accessible across many platforms.

This has led to the rise of AI-driven coding tools, including Claude Code, OpenAI Codex, and Gemini CLI.

At a high level, it works like this: You describe what you want in your SEO report, and they handle the heavy lifting. 

These tools are “agentic” because they can execute multi-step workflows like pulling data, transforming it, analyzing it, and then generating reports with minimal intervention.

You don’t need advanced coding skills to use them, but a basic understanding of data structures and APIs will make the process effective.

In practice, the entire reporting workflow can be done programmatically from start to finish.

They generate code that connects directly to data sources through APIs, removing the need to rely on dashboard connectors or preconfigured data pipelines.  

From there, they can analyze the data and create full reports. This can happen in minutes as you become more familiar with the tools.

While each of the tools I mentioned has different strengths (for instance, some are better at reasoning, others at speed or integrations), they essentially do the same thing: transform SEO reporting from a manual, rigid process into something with endless possibilities. 

The power of this technology is hard to overstate. 

Why AI coding tools are better for SEO teams

AI coding tools are removing the roadblocks between data, development, and reporting for SEO teams. 

Faster SEO reporting and analysis

Speed is the most obvious advantage. 

Agentic coding assistants are enabling SEOs to create reports that previously required support from developers.  

In many cases, tasks that previously took days can be done in hours and tasks that took hours can be done in minutes. 

You can see this improvement even in small interactions.

For example, when data is processed directly in the browser (instead of re-querying a dashboard), it makes filtering, sorting, and slicing data significantly faster. 

Instead of waiting for a dashboard to refresh after every change, you can interact with the data in real time.

That’s just one way these technologies make you more agile.

Flexible and custom reporting workflows

Instead of having to work in predefined templates and a fixed structure, you can build the report for exactly what the situation requires. 

Plus, every major data visualization and plotting library is available on demand in any programming language. 

If you feel like one approach isn’t capturing the whole story in your SEO report, you can switch or combine multiple frameworks in the same output. 

From rankings and traffic trends to keyword clusters or content performance, you can apply nearly any chart. 

The examples below come from Observable Plot, created by data visualization expert Mike Bostock, but many other charting libraries are available.

While setup and onboarding take some initial effort, these tools are accessible to most roles on the team and immediately become more efficient than traditional reporting.

Transparent data constraints

Data limitations are clearer, too. 

For example, when you’re working with browser-based charting libraries, you have a better feel for how many rows you’re handling and what the system can realistically process. 

And when you do hit a limit, you understand exactly what’s happening and how to adjust. This helps prevent misleading or incomplete reporting. 

---

Real-world SEO reporting applications

What are some practical ways you can use these agentic coding assistants to run SEO reporting? 

Pre-meeting reports

Before client meetings, you can pull data from Google Search Console and GA4 via APIs, then have it cleaned and segmented programmatically and generate a notebook, dashboard or slide deck in a single workflow.

Technical SEO analysis

Say you need to analyze crawl data or log files. Instead of exporting, filtering, and then visualizing the data manually, you could get the raw data, process it with code, and generate custom visualizations tailored to the exact problem you’re trying to solve.

Ad hoc stakeholder requests

Once data connections are established, last-minute reporting requests no longer have to mean staying up late to pull data and build reports. The next time someone asks for something like “non-brand CTR trends by device over the last 90 days,” you can produce this data with much less effort. 

Really, if you can imagine it, you can do it with these agentic coding assistants. As a result, SEO teams can do more proactive analyses.

What this means for agencies and in-house teams

AI is impacting all knowledge workers, not just SEOs. 

By now, many have seen the viral article “Something Big Is Happening” by Matt Shumer, which paints a startling picture about the future of AI-powered work and adopting an “adapt or die” mentality.  

Research is beginning to show how these types of technologies are impacting productivity. 

One study by Stanford and MIT researchers found that access to AI tools in the workplace increases productivity by at least 14% on average, with a 34% increase for low-skilled workers. 

The bottom line is that anything that can be generated with code is going to be eaten by these CLI tools and agents, because they’re just so much faster. 

Businesses are catching on. Up to 64% of businesses now generate a majority of their code with AI assistance, according to a Business Insider report, and high-adoption teams are producing nearly double the output. 

For SEO teams, they’re experiencing faster reporting cycles, more iterative analyses, and the ability to handle more complex data.

AI coding assistants are also helping analysts become builders. Non-technical users can build and iterate in ways that were previously out of reach.

Ultimately, this shift is becoming table stakes. The SEO teams that integrate these tools into their workflows will move faster and produce better results. 

The competitive advantage is going to those who adopt these technologies first.

Where to begin, though? Consider piloting a small project:

• Start with one repeatable reporting workflow.
• Connect a data source like Google Search Console via API.
• Test and refine a single report before expanding to other use cases.

See the complete picture of your search visibility.

Track, optimize, and win in Google and AI search from one platform.

Start Free Trial

Get started with

The future of SEO reporting is agentic and code-driven

Traditional SEO reporting tools are quickly becoming a bottleneck. 

AI coding assistants are helping SEO teams respond to any type of reporting without the added friction, while delivering faster, better insights. 

The companies that adapt will gain the advantage in SEO execution. Start by replacing one recurring report with a code-driven workflow and build from there.