Hey Reader!

My webinar on "Uncovering AI Insights in GA4" happened last week, and I got a number of questions but there are two that stuck with me that I want to share with you.

"Can I Use AI to Rate Content Complexity?"

Amy asked about using AI to analyze content and rate blog posts 1-5 based on how complicated the English is, then cross-referencing that with traffic metrics.

This is actually a great use case for AI, but the prompt needs work. The word "complicated" would trip up any AI tool because it's way too vague. What does complicated mean? Long sentences? Technical jargon? High reading level?

My recommendation is to create an instruction set first. Define exactly what you mean by complexity levels 1-5. Are you looking for reading grade level? Sentence length? Technical terminology density? Give the AI specific criteria for each rating level, and you'll get much more consistent and useful results.

This is a perfect example of why better prompts lead to better answers. Don't assume the AI knows what you mean, because it probably doesn’t. Make sure to spell it out clearly.

"How Do I Explain AI Traffic to Stakeholders?"

Jeff asked about communicating AI traffic tracking to clients and stakeholders, which is something we all need to get better at.

First, be honest about limitations. Not all AI traffic is trackable. For example, some tools like DeepSeek seem to withhold referrer information, so they show up as direct traffic. What we need to look at is directional data, not perfect numbers.

Here's what I've found works: focus on engagement quality, not just volume. When I show clients their AI traffic, I always include engagement rate alongside the visitor counts. In my experience, people coming from AI tools typically have engagement rates that meet or exceed the site average. They're often higher-quality visitors than what comes from display ads, for example.

Also, think long-term. Create audiences of these AI visitors and track whether they come back to your site later. Are they signing up for newsletters? Converting on subsequent visits? This helps stakeholders understand that even if the volume is relatively low, these might be valuable discovery moments in longer customer journeys.

Miss the webinar live?

You can catch the replay over on my YouTube channel.

Dana DiTomaso Founder ​dana@kpplaybook.com​

The Reality Behind "Zero-Click" Marketing Panic

Andy Crestodina at Orbit Media published a thoughtful piece on zero-click marketing and the truth about search traffic. His main argument? The panic about dropping organic traffic misses the bigger picture.

What I appreciate about Andy's take is that he acknowledges the traffic drops are real! In fact, their own site shows the same downward trend we're all seeing. But here's the thing: zero-click searches often come from zero-intent searchers who just want quick answers. Those visitors weren't going to convert anyway.

The key insight? Focus on commercial-intent phrases where people are actually looking for solutions and ready to visit websites. Not every piece of traffic is good traffic, and sometimes losing the noise helps you see the signal more clearly.

How to Actually Do Data Analysis (Not Just Implementation)

Juliana Jackson wrote an incredibly comprehensive guide on how to do data analysis for business. This is exactly the kind of content our industry needs more of — practical frameworks for turning data into business impact.

Juliana walks through a complete analysis from start to finish using a fictional skincare brand, covering everything from strategic framework setup to implementation roadmaps. What makes this so valuable is that she doesn't just show you how to pull reports, she shows you how to think about the business context that makes those reports meaningful.

This matters because most analytics content focuses on the "how to track" without ever getting to "what to do with what you tracked." If you've ever felt stuck between collecting data and making recommendations, this guide bridges that gap beautifully.

Making Metrics Actually Useful with Metric Trees

Related to Juliana’s post, Timo de Chau wrote about metric trees for digital analysts, and it's a concept that I’ve talked about before but I didn’t know there was a specific name for it! A metric tree shows the relationships between your metrics instead of treating them as isolated numbers.

A single metric sitting alone often struggles to tell you what to do next. But when you can see how metrics connect to each other, for example how improving your email signup conversion rate affects your overall revenue, you suddenly have a roadmap for where to focus your efforts.

Timo makes the case that metric trees work as both communication tools and optimization guides. I've seen many measurement conversations derail because different teams can't agree on what matters. Having a visual map of how your business actually works could solve that problem.

Speaking at MeasureSummit 2025

I'll be speaking at MeasureSummit 2025 with a session called "From Page Views to Performance: Advanced GA4 Content Analysis for Strategic Decision-Making."

We're moving beyond surface-level metrics to build a three-level resonance framework: Attention (did they stay?), Engagement (did they consume?), and Action (did they convert?). I'll show you how to create custom GA4 metrics that reveal true content consumption patterns, use traffic acquisition data as content intelligence, and leverage path analysis with AI tools to spot opportunities your competitors are missing.

Perfect for marketing analysts, content strategists, and digital marketers who want to move from reactive reporting to proactive content planning. Hope to see some of you there!

That's it for this edition of The Huddle. As always, if you have questions or want to share what you're working on, just hit reply. I read every email!

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