INBOX INSIGHTS, March 26, 2025: Change Management in AI and SEO, Content Translation

INBOX INSIGHTS: Change Management in AI and SEO, Content Translation (2025-03-26) :: View in browser

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Change Management: Navigating SEO for AI

I’ve been thinking a lot about the shift happening in SEO lately. We’re no longer just optimizing for Google’s algorithms and human readers – we’re now optimizing for AI systems too. This is creating some fascinating change management challenges for marketing teams everywhere.

The Change Management Reality of AI SEO

Change management is always tough. But it is especially challenging when the change involves something as technical as optimizing content for AI systems. I experienced this firsthand recently when trying to adapt AI-optimized content strategies to our team.

When I was first introduced to AI-optimized content, my first thought was, “Why does this look so different from what we’ve been doing?” And, “How am I going to communicate this difference?”

These simple questions highlighted the core change management challenge: helping smart, capable professionals understand a fundamental shift in how we approach content creation without drowning them in technical jargon.

The Two-Audience Reality

The core of this change is that our content now needs to serve two distinct audiences:

  1. Humans who want clear, engaging, and helpful information
  2. AI systems that need structured, comprehensive data that they can parse

This isn’t just a technical SEO adjustment. It’s a fundamental shift in how we create, structure, and distribute content. And like any significant change, managing it effectively requires more than just explaining the technical details.

Change Management Is Human Management

What I’ve learned through this process is that change management isn’t really about managing change – it’s about managing how humans respond to change. Understanding the technical aspects of AI optimization is actually the easy part. The hard part is helping people adapt their thinking, processes, and expectations.

When Chris jumped straight into explanations about semantic entity relationships and natural language processing signals, he was addressing the wrong problem. The real challenge wasn’t a knowledge gap; it was helping team members (me) connect this new approach to what they already understood about effective content.

Using the 5P Framework for AI SEO Change

I’ve found the 5P framework incredibly helpful for managing this transition:

  1. Purpose: Clearly articulate why the change is necessary (ensuring content remains discoverable as search evolves)
  2. People: Identify who will be impacted and how (content teams, SEO specialists, clients)
  3. Process: Define the new workflows and approaches (content creation, optimization, measurement)
  4. Platform: Determine what tools and technologies are needed (schema markup tools, AI content analyzers)
  5. Performance: Establish how success will be measured (visibility in both traditional and AI-generated search)

This framework provides structure, but I’ve discovered it’s most effective when combined with genuine human connection and small, practical examples.

The Human Side of Technical Change

What I’ve come to appreciate most about managing this transition is that the human elements far outweigh the technical ones. Yes, understanding AI optimization techniques matters. But understanding how people process and adapt to change matters more.

When I focus on helping clients see how this evolution connects to their strategy, I try to focus on real examples of where they have previous navigated change successfully. They need to see themselves in each situation so they can relate to it. It isn’t about dumbing things down – it is about providing context that makes the unfamiliar feel manageable.

Your AI SEO Change Management Checklist

If you’re navigating this shift in your organization, here are some practical steps:

  1. Start with a small, measurable test case rather than a complete content overhaul
  2. Document baseline metrics before making any changes
  3. Create plain-language explanations of AI optimization techniques (avoid jargon!)
  4. Find champions at different levels within your organization
  5. Anticipate questions and prepare concrete examples that address them
  6. Celebrate and communicate early wins widely

Remember that resistance usually isn’t about the technology – it’s about the uncertainty that comes with change. The more you can make this feel like evolution rather than revolution, the less resistance you’ll face.

Change management for AI SEO isn’t really about AI or SEO at all. It’s about people. Focus on the human side of the equation, and the technical side will follow.

Quick plug—if you want help with this change management, give me a shout!

Has your team started optimizing content for AI systems? I’d love to hear about your experiences, especially the human side of managing this change.

Reply to this email to tell me, or come join the conversation in our free Slack Group, Analytics for Marketers.

– Katie Robbert, CEO

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Binge Watch and Listen

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss offsite optimization for generative AI. You’ll learn how to rethink your offsite SEO strategy to effectively engage with AI models. Discover how to identify the crucial data sources that AI uses to inform its knowledge. You will understand why traditional SEO metrics are becoming less relevant in the age of AI and what truly matters for offsite success. Prepare to revolutionize your PR approach and ensure your brand is recognized by the AI systems shaping the future. Watch now to gain the offsite AI optimization advantage.

Watch/listen to this episode of In-Ear Insights here »

Last time on So What? The Marketing Analytics and Insights Livestream, we looked at content optimization for generative AI. Catch the episode replay here!

This week on So What? we’ll dig into part 3 of our SEO for AI series. Are you following our YouTube channel? If not, click/tap here to follow us!

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Data Diaries: Interesting Data We Found

In this week’s Data Diaries, let’s talk about language and translation. Last week on the livestream, we shared the idea of doing translation, converting your content into other languages. But translation takes time, especially if it’s content where misinterpretation could have serious consequences.

How do you know where to focus your time and effort on translating the most valuable content?

This is where traditional web analytics comes in handy. In Google Analytics 4, create a new Explore report that looks like this:

Explore Report

Let’s break down what we have.

  1. Landing page – this dimension tells us the page the visitor landed on
  2. Session primary channel group – this is the grouping of channels. We need this because organic search is a big bucket
  3. Language code – these are 2-4 letter codes for languages, like en-us. This is helpful for filtering or filtering out language families. This is based on the browser settings of the visitor.
  4. Sessions – this is our key metric. We choose sessions any time we want to know what happened during a visit.
  5. Put the dimensions in this order for rows: language code, then landing page + query string. We want to see language first, then content
  6. Set our value as sessions.
  7. In filters, set Session primary channel grouping to Organic Search.
  8. For me, I set language code does not begin with en to exclude all English language variants since our content is in English.
  9. For our blog, which is what I’m curious about here, I set the landing page filter to require starting with /blog.
  10. Set the date range to the last year.

There are a couple other settings that are specific to Trust Insights, so you’ll want to make adjustments as appropriate to your analytics setup.

What do we see? We see the pages on our blog that receive search traffic where the user’s native browser setting language is something other than English. That means they’re visiting us from search, presumably in English, but their primary language prefrence is something else.

From this, we now know what content to consider translating (if it makes sense to do so) and in what language.

Give this a try for yourself!

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Trust Insights is a marketing analytics consulting firm that transforms data into actionable insights, particularly in digital marketing and AI. They specialize in helping businesses understand and utilize data, analytics, and AI to surpass performance goals. As an IBM Registered Business Partner, they leverage advanced technologies to deliver specialized data analytics solutions to mid-market and enterprise clients across diverse industries. Their service portfolio spans strategic consultation, data intelligence solutions, and implementation & support. Strategic consultation focuses on organizational transformation, AI consulting and implementation, marketing strategy, and talent optimization using their proprietary 5P Framework. Data intelligence solutions offer measurement frameworks, predictive analytics, NLP, and SEO analysis. Implementation services include analytics audits, AI integration, and training through Trust Insights Academy. Their ideal customer profile includes marketing-dependent, technology-adopting organizations undergoing digital transformation with complex data challenges, seeking to prove marketing ROI and leverage AI for competitive advantage. Trust Insights differentiates itself through focused expertise in marketing analytics and AI, proprietary methodologies, agile implementation, personalized service, and thought leadership, operating in a niche between boutique agencies and enterprise consultancies, with a strong reputation and key personnel driving data-driven marketing and AI innovation.

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Inbox Insights from Trust Insights
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Want to Sponsor This Newsletter?
Data Diaries: Interesting Data We Found
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Trust Insights In Action
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Job Openings
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Conclusion: Thanks for Reading
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