Integrating AI Into SEO Testing Workflows
Dana DiTomaso
I help you level up your analytics and digital marketing skills linktr.ee/danaditomaso
Curious how AI can help with SEO experiments? 🧪 Celeste Gonzalez shares how to streamline your workflow and run smarter tests.
(This post was written by Kick Point Playbook team member, Kyra Piper !)
SEO testing doesn’t have to be complicated or time-consuming. In the latest KP Playbook webinar, we were joined by Celeste Gonzalez , Director of SEO at RooLabs ( RicketyRoo Inc ), who showed us how to integrate AI into SEO testing workflows to make testing more efficient, especially for teams with limited time and resources.
Celeste walked us through practical examples, showcased how she uses tools like ChatGPT, Clarity , and SEOTesting.com to brainstorm, analyze, and report on tests faster (without losing the human touch), and shared a wealth of resources that you can find here in the recap.
Watch the replay below and read the key takeaways to learn how you can make your SEO testing workflow faster and more efficient with a little help from AI.
What is SEO testing?
“SEO testing is the process of optimizing parts of a site and measuring the impact on organic traffic and visibility.” – Celeste Gonzalez
Why is SEO testing important?
If you’ve ever had to convince a stakeholder or client to try something new, SEO testing can help you:
You’re probably already doing some testing without calling it that, like updating a title tag or refreshing content. The key is tracking your changes and analyzing the results.
Key takeaways
SEO testing ideas to start with
You don’t need a massive enterprise site to start testing. Most teams are already doing some form of testing without calling it that.
Common SEO test ideas:
How to prioritize what to test first
If you’ve got a list of ideas a mile long, Celeste suggests thinking about:
“ If you have a client that’s more risk averse, even if you have a testing idea that you believe will make a bigger impact than a different one, you might want to give the easier or lower impact test to the client first. Because it won’t take as many resources or as much time. You want them to say yes and get their buy in for it.” – Celeste Gonzalez
Where AI can help in your SEO testing workflow
AI tools (especially LLMs like ChatGPT or Claude) aren’t here to replace SEO testing—but they can help speed things up. Celeste broke down three ways AI can improve your workflow:
1. Data pulls
Use ChatGPT, Claude, or Perplexity to help write Python scripts that extract and filter your data. For example, Celeste demoed a Google Colab notebook to help you analyze striking distance keywords from an Ahrefs CSV file. It even creates visualizations by subfolder.
“ I’m not a coder, I don’t have a background in code, I’m a beginner but using these LLMs to create that has been really helpful and has made things a lot more efficient” – Celeste Gonzalez
Tools mentioned:
💡 Data privacy concerns with LLMs: Avoid feeding proprietary data to LLMs as they may train on it. Set ChatGPT to not train on your data and use Python scripts to work with data without exposing it to AI models.
2. Brainstorming and test ideas
AI can help generate ideas for metadata testing, content creation, or internal linking updates, especially when it’s built into tools you already use.
Celeste highlighted how:
3. Reporting
Make it easy for stakeholders to understand what happened. Use AI to:
“ Writing a giant report is great, but are they going to read all of it? Are they going to understand all the key points there? You want to find where an explanation can benefit from a visualization. Sometimes people are more visual people and that’s what’s going to get through to them.” – Celeste Gonzalez
What is Google Colab and why use Python for SEO testing?
If you’ve never used Python before, Google Colab is a great place to start. It’s a free, cloud-based platform for running Python code in your browser. You can upload CSVs, write code (or paste in AI-generated code), and share notebooks with others.
Why use Python instead of Google Sheets?
Sheets are great, but with a lot of data, they can get slow. Using Colab is way more efficient, especially when you’re filtering, re-filtering, and trying to explore trends.
Even if you’re not a developer, AI tools can help you build your own beginner-friendly notebooks.
🧰 Use Celeste’s Striking Distance Keyword Tool Colab Notebook.
How to use AI to make your SEO more efficient
Step 1: Data extraction
The first step is to pull your data into Colab. Marco Giordano has a great tutorial on how to extract data from Google Search Console API for data analysis in Python, if you’re just getting started. You can also create a script from scratch using AI tools like ChatGPT or find existing scripts shared by other SEOs on GitHub or Colab.
Use ChatGPT or Claude to generate Python code for uploading CSV files. Here’s an example prompt:
“I want to upload a CSV from Ahrefs into a Colab notebook using Python. These are the column names: keywords, SERP features, volume, keyword difficulty, cost per click, and organic traffic. Please help me write the code.”
Using pandas (a popular data analysis library), you can upload and view your CSV as a data frame—basically, a spreadsheet within Python. This makes it easy to filter, adjust, and view your data without repeatedly exporting from tools like Ahrefs.
💡Avoiding encoding issues: When exporting data from Ahrefs, always choose UTF-8 encoding instead of UTF-16 to avoid compatibility errors in Colab.
Step 2: Data filtering
Once your data is loaded, you can filter it to focus on what you need. For example, you can:
Using Python functions step-by-step helps you identify and fix any errors along the way, rather than running an entire script at once and dealing with unexpected bugs.
Step 3: Spell check your keywords
To catch typos in your keyword data, you can use a spell-checking library. While JamSpell often has compatibility issues with Colab, an alternative like PySpellChecker works seamlessly. Claude, an AI tool, can help identify and troubleshoot issues when integrating these libraries.
💡 Dealing with language variations: If your data includes non-English words (like Spanish place names), spell-check tools might flag them as errors. Be mindful when interpreting the results.
Step 4: Advanced visualization and reporting
Visualization isn’t just about making your data look nice—it’s about helping stakeholders understand your findings. Consider visual elements like:
Google Colab allows you to easily export your filtered and processed data back into a CSV file, making it simple to share results or continue working with other tools.
Step 5: Integrating AI for SEO testing
In addition to Colab, you can use other AI-driven tools to enhance your SEO workflow:
By combining AI tools with Colab, you can build a powerful, efficient workflow for data analysis, visualization, and reporting.
AI should SUPPORT, not replace human expertise
While AI can make your SEO tasks faster and more efficient, it’s important to remember that it should support—not replace—your expertise. Tools like Google Colab, SEOtesting.com, and Microsoft Clarity are powerful, but they still need a human touch to ensure accuracy and relevance.
AI can help you analyze data, find patterns, and suggest improvements, but it’s up to you to verify those insights. Always question the outputs:
For example, sometimes AI might flag a “dead click” that’s not truly an issue. Or it might suggest optimizations that don’t fit your specific use case. That’s where your critical thinking and industry knowledge come in.
Webinar Q&A
Where can I find a list of libraries like pandas or JamSpell?
Celeste recommends checking out JC Chouinard’s blog and YouTube channel for Python libraries used in SEO. Marco Giordano’s GSC API tutorial also covers using QueryCat by JR Oakes.
People to follow:
Recommended tutorials:
What’s a simple test you recommend for someone just starting out?
“ Doing your SEO strategy, you’re reevaluating pages all the time and making recommendations based on what you believe is going to work and doing a metadata update, changing the title tag that can be your test right there. It’s just a matter of making sure that you’re tracking everything correctly.” – Celeste Gonzalez
The key is tracking what you did and measuring the impact. Metadata updates and blog refreshes are great starting points—low lift, familiar, and easy to explain to clients.
How do you know what pages to test or compare when running a larger test?
According to Celeste, it depends on the size of the site and the amount of traffic.
The important part is to be intentional and track your changes.
How long should you run a test before implementing a change?
Celeste recommends the following testing periods:
Make sure your site is indexed before measuring anything.
“ And don’t check on it before your timeframe is complete too. You don’t want to freak out because something happened one way or another where you’re like, oh my gosh, this is a major success. We definitely need to implement this across. If you said four weeks. Don’t look, wait until the four weeks happens.
How do you balance automating with AI while maintaining quality control?
When using AI for SEO, it’s important to set boundaries and not blindly trust outputs. Here are a few of Celeste’s recommended best practices:
“I think it’s just very important setting those limits with your team. And, working on finding an SOP that works for you all there where you’re not relying on it too much. You can use it to make things faster.”- Celeste Gonzalez
Balancing automation with manual quality control helps you leverage AI effectively.
Any advice for someone opening Google Colab for the first time?
“So it’s important to get a little bit of exposure there, and you can work with people’s existing notebooks.
Can we use Google Colab for NLP content analysis and optimization?
Yes, Marco Giordano’s tutorial covers this well. Celeste recommends following his guide for NLP use cases in SEO with Colab.
What’s been your biggest time-saving discovery since integrating AI?
“Working with Python has really helped. It takes a good amount of time to get started, like not discounting that at all. When you start from absolutely no knowledge of it or just very basic knowledge, it takes a while to get, that type of data extraction data pulling up and to figure out, how it can do everything that you do in Sheets”- Celeste Gonzalez
If you’ve never used Python or Google Colab it’s a steep learning curve at first, but once you’re comfortable, data pulls and filtering get much faster, and you can analyze more pages in less time.
Are you experimenting with AI in your SEO processes? Let’s chat in the comments!
Digital Analytics Consultant | Turning Numbers Into Strategy | Spreadsheets | SQL | Business Intelligence | GA4
2moBeth Chernes, J.D.
Director of RooLabs🧪 | Speaker | Wix Course Creator | Your Fav SEO
2moThank you for sharing Dana!