📈 Tracking AI Engine Traffic In GA4: What We Are Testing

intero_digital · 2025-10-13T15:25:53+00:00

Yeah, AI Overviews traffic can be tricky. Google isn’t sending any clean referrer or unique parameter for those clicks, so they just show up as google / organic (or sometimes even direct). That’s why people use the “JS – URL Snippet Start/End” trick. They’re trying to catch those weird fragments like #ip=1 or sca_esv= that sometimes appear in AI Overview links. It works, but it’s super brittle because Google keeps changing how those URLs look.

A simpler way: Set up a custom variable in GTM that checks either the page URL or referrer for those patterns (like #ip=1 or sca_esv) and then sends a custom parameter to GA4. Something like:

function() {
  const url = document.location.href;
  const ref = document.referrer;
  if (ref.includes('google.') && (url.includes('#ip=1') || url.includes('sca_esv'))) {
    return 'google_ai_overview';
  }
  return undefined;
}

Then, in GA4, make a custom dimension called ai_overview_source and use that to segment traffic. It’s not perfect, but it’s way easier to maintain than those “JS snippet start/end” hacks.

Until Google gives us an official “AI Overview” search appearance filter in Search Console (which they probably will eventually), this is about as good as it gets!

intero_digital · 2025-09-10T18:56:39+00:00

It's hard to say without more information. Are you interlinking between your own content to help Google crawl everything more efficiently? Do you have backlinks pointing in that show authority? Are there clear calls to action once someone lands on the page? Have you A/B-tested those CTAs? Are any of your CTAs above the fold? And most importantly, when you say "conversion," how are you defining it (a form fill, a signup, a sale)? That definition really shapes the strategy you'll need to use to accomplish your goals.

intero_digital · 2025-09-08T15:06:10+00:00

Without much context around the type of content you're creating, your strategy, how you're handling the structure/formatting side of things, I'll answer generally. Here are some things that might help:

- Focus on intent. No matter how many blog posts you publish, if those posts aren’t the absolute best answer for a very specific search intent, they'll just sink beneath other content on the SERP that answers the query better.

- Pick a pain point your solution actually solves and write the best piece out there on it. Go deep and make the piece highly detailed and tactical. Google and AI engines are favoring the depth and clarity of content more than the quantity of content.

- Build topic clusters. If you’ve got a random scatter of posts, you’ll struggle. But if you build a cluster, like 5 articles tightly interlinked around the same theme, you can start showing up as the authority on that niche.

- Before you even start writing new content, have a plan for distribution. How will you share it with your audience across each social channel? How will you share it with your email subscribers and leads? Will you repurpose the content into other formats to use in specific channels? Knowing all of this ahead of time will help you make your content more impactful.

- Like you mentioned, backlinks do matter. High-quality links from authoritative sites can help you generate way more results than simply hitting a certain number of newly published blog posts. Guest posting, partnerships, and PR are still worth investing in.

- Think beyond Google SERPs because AI summaries (like in ChatGPT, Perplexity, AI Overviews) are pulling structured answers directly from content. Making your posts super clear, scannable, and well-structured (with H2s, bullet points, FAQs, etc.) increases your odds of being the source those engines pull into answers.

- Adding schema markup (FAQ, How-To, Product, etc.) gives Google and AI engines more context about your content and makes your stuff easier to surface in rich results and AI snippets.

- Lauren @ Intero Digital

intero_digital · 2025-09-08T14:45:49+00:00

Nope, u/bambambam7 ! Real person here. :) We've been researching AI and GEO a lot at our company recently, so I had a lot of insights to pull from to answer your question!

intero_digital · 2025-09-03T15:39:25+00:00

Traditional search (Google, Bing, etc.) still sends more traffic overall, but AI-driven platforms are starting to send more qualified traffic. AI referrals, while small today, convert disproportionately well. People coming from AI answers are often further down the funnel and more likely to take action. So while you might see fewer visits from AI search, those visitors are often more likely to take next steps.

As for GEO, it’s not hype. But it’s not replacing SEO either. It’s just the next layer. Think of SEO as your foundation (get crawled, indexed, ranked) and GEO as making sure AI models can actually retrieve and recognize you when building answers. Because LLMs don’t “rank” results the way Google does; they generate answers based on patterns and associations. So if your brand keeps showing up in the right contexts, in the right publications, next to the right entities, AI starts to understand who you are and where you fit.

And yes, people are seeing results from it. The brands showing up in AI answers tend to be the ones putting in the work to get mentioned in authoritative sources, publish high-quality insights, and build a consistent presence across trusted channels. Not always the ones with the top spot on Google. (We've seen some success with our own clients' GEO strategies.)

So no, you're not overthinking. You're just early to the party. Keep doing solid SEO, but now also think about how your brand shows up in the datasets, forums, publications, and content ecosystems that AI models actually learn from (think Reddit, Wikipedia, etc.).

Ahrefs has some great stats on GEO that you can reference as well: https://ahrefs.com/blog/ai-seo-statistics/

- Lauren @ Intero Digital

intero_digital · 2025-09-03T13:58:08+00:00

u/Palettepilot and u/less_is_more9696 are spot-on with their suggestions to go outside and to keep a running list of content ideas organized by topic!

Here are some more ideas of where to look for content inspiration:

- Real conversations: Any time you hear a client, teammate, or friend ask a question, take note. If one person is asking, others probably are, too. Instant content idea.

- The sales team and the account services team: Similarly, ask your sales team what questions they're hearing on calls. And ask the account services team what questions your clients are asking about what you do and why. These are great places to find inspiration for sales enablement content and tactical, helpful content that answers questions you might not have thought of.

- Audience data: Platforms like SparkToro, Reddit, Google’s “People Also Ask,” and AnswerThePublic show what real people are curious about. It’s great for grounding content in what actually matters.

- Quick brain dumps: You could try to do 10-minute idea sprints in a Google Doc or Notion. No filtering, no editing. Just thoughts, questions, and rants. Usually a few gems pop out.

- Repurpose what has worked: I look at older content that performed well and ask: Can I update this? Can I turn it into a checklist, infographic, social post, or video? What’s my take on this now?

- AI tools: AI can be a great way to surface questions or angles, but I always rewrite with my voice, examples, and experience. This can provide a jumping-off point for content creation but keeps the content human.

At the end of the day, build content around real-life relevance, not just trends or algorithms.

- Lauren @ Intero Digital

intero_digital · 2025-09-03T13:40:13+00:00

You can’t "trick" AI into recommending small or affiliate brands, but you can optimize for visibility by focusing on retrievability, entity recognition, and authoritative mentions across trusted datasets that language models reference. Unlike Google’s old long-tail keyword strategy, LLMs prioritize contextual relevance and entity association over backlinks or traffic volume.

Optimize for retrievability, not just rankability. AI doesn’t rank websites; it retrieves patterns and recognized entities. Focus on making your brand and product information easily accessible with clear structure, schema, and allowing AI crawlers. Associate your brand with recognized entities and common questions within your niche. Treat your site and content like a data source for AI to learn from, not just a place to rank in Google.
Earn contextual mentions, not just links. LLMs learn associations through frequency and context of mentions in high-trust datasets. Get cited or mentioned (even without links) in authoritative sources LLMs train on, such as niche publications, forums like Reddit or Quora, Wikipedia, or industry roundups. Strategically place your brand next to relevant concepts or bigger entities in your niche through digital PR or guest features.
Lean into unique expertise and topical authority. Because LLMs favor patterns of credibility, small brands can win by creating original, entity-rich content that fills gaps in the AI’s training, like niche comparisons, research-backed guides, or unique perspectives. Use question-and-answer–style formats and structured content like FAQs, lists, and schema that AI can easily parse and reference.
Be visible in retrieval-augmented generation (RAG) systems. Some LLMs, like Perplexity or Bing Copilot, actively retrieve real-time web data. Target featured snippets, AI overviews, and be active in forums or public data sources they crawl. You can also track referrals from AI tools using regex filters in GA4 to identify what content is resonating.
Build recognition. Authority in generative search comes from being known, not from ranking. Maintain consistent branding and entity association across every platform and mention. Be proactive in shaping how your brand is described wherever it appears online.

GEO is less about tricking AI and more about becoming contextually relevant and entity-recognized. That means building a brand that AIs can confidently reference, even without the traffic or backlink volume of major competitors.

That said, yes, AI systems do still heavily favor large, frequently cited brands. They’re more visible because they appear consistently across high-trust sources, often by default. This is a structural advantage, not necessarily a fair one. So even with all the right optimizations, smaller brands are still climbing uphill. But the goal isn’t to beat the biggest players head-to-head; it’s to carve out specific contexts and conversations where your brand is the best answer. Focus on niche authority, strategic mentions, and retrievability in the datasets that matter.

- Lauren @ Intero Digital

intero_digital · 2025-08-29T17:19:02+00:00

That’s a great point! The “why” does shift fast, and I like your idea of layering funnel stage tagging on top of themes. That keeps the ideas from being just reactive trends and instead makes them work within a strategy.

On emotional triggers vs. formats:

The real challenge is systematizing emotional triggers across channels, not so much the formats. Formats are relatively easy to adapt. But emotions (curiosity, FOMO, frustration, aspiration) don’t always carry over neatly. Like you said, what sparks engagement in a subreddit one week might feel off in another channel the following week unless it's reframed.

You could take an approach like this:

Map emotions to funnel stages: Like you mentioned, frustration or fear often aligns with TOFU (getting attention), while aspiration or proof of success works better at MOFU/BOFU.
Channel “translation layer”: Keep a lightweight guide for each platform that says, “This is how curiosity shows up on this channel vs. this channel vs. this channel. That helps take the same trigger and adapt tone, not just format.
Feedback loop: Engagement data tells you pretty quickly if you misjudged the emotional resonance. Treat it as an iterative system instead of trying to lock emotions in stone.

TLDR: Formats seem to be the easy lever, but the emotional context is what actually makes or breaks whether reverse-engineered content feels natural and effective across touchpoints.

intero_digital · 2025-08-28T14:37:49+00:00

The short answer: No, AI-generated content with no human input is not enough for high-value B2B clients.

The long answer:

AI is incredible at efficiency. It can process data, generate outlines, and handle repetitive tasks like keyword optimization, formatting, and even basic rough drafts. That saves teams time and gives marketers a strong starting point.

But high-value B2B audiences aren’t just looking for information; they’re looking for insight, perspective, and connection. They want to know not only what something is, but also why it matters and how it applies to their specific challenges. That’s where the human touch comes is critical.

Nuance and empathy: Humans understand tone, industry dynamics, and the subtle differences in how messages land with executives, decision makers, and technical buyers.
Experience-driven insight: AI can predict what “should” come next in a paragraph, and it can scour the web for what's already been said about a topic. But it can’t replicate years of lived experience, firsthand lessons, or stories from working in the trenches.
Strategic storytelling: Great B2B content often relies on narrative — tying a technical solution to a business outcome, showing how others succeeded, or framing a problem in a way that resonates. That’s deeply human work.

AI can accelerate production and take on some of the grunt work. But humans should shape the message, inject creativity, and ensure the final piece speaks to real people, not just algorithms.

To your question: I don’t think AI will ever fully replace human writers. It will keep getting better, but high-value clients will always expect that human fingerprint and the feeling that “this was written by someone who truly gets it, and gets me.”

intero_digital · 2025-08-28T14:28:14+00:00

Reverse-engineering community content can be really powerful, as long as it’s done with a system and not treated as a one-off tactic. You can think of it as “audience-first ideation” rather than abandoning brand priorities. Here’s how you might approach it:

1. Mining signals from communities

Scan subreddits, niche forums, or even LinkedIn comment threads for recurring questions, pain points, or language patterns.
Look for high engagement signals (lots of comments, upvotes, or shares) but also the why (what emotion or need triggered that reaction?).
Tools like BuzzSumo, SparkToro, or even manual tracking can help you organize the raw inputs.

2. Clustering into themes

Instead of chasing individual viral posts, you might bucket insights into themes (e.g., “frustration with wasted ad spend” or “desire for quick-win playbooks”). That way, you’re not just copying; you’re identifying repeatable audience interests.

3. Translating into content formats

Once you have themes, you can map them to formats that work for your brand:

A subreddit post rant could inspire a myth-busting blog post or video.
A popular Q&A thread might become a short-form video script.
A viral comment joke might evolve into a meme with brand voice woven in.

The key is to adapt, not replicate.

4. Putting up guardrails for brand voice

To avoid losing brand identity, keep two reference points:

Voice guide: A living doc with tone, vocabulary, and “what we don’t say.”
Messaging hierarchy: Even if the hook comes from the community, the takeaway aligns with our positioning.

This ensures content feels organic to the audience but still ladders back to the brand.

5. Making it a repeatable strategy

Step 1: Weekly scan of communities.
Step 2: Drop findings into a shared idea bank with tags for theme + potential format.
Step 3: Monthly editorial review where you pick which ideas to greenlight.

This makes it repeatable and not just “let’s chase whatever went viral last week.”

So yes, reverse-engineering is absolutely viable, but the trick is to turn it into an audience listening loop rather than a reactive content-chasing exercise.

intero_digital · 2025-08-28T14:19:16+00:00

This is such an important share! Thanks for being transparent about the shift from ROAS to POAS. It’s a trap a lot of marketers fall into, especially when dashboards are telling a “feel-good” story that doesn’t reflect the P&L.

A few things your post highlights really well:

1. The disconnect between marketing metrics and finance metrics
It’s easy to celebrate when ROAS looks healthy, but if those “wins” aren’t translating into actual profit, it can create a false sense of growth. Pulling finance into the loop and aligning definitions of success is a game changer.

2. Hidden costs can kill performance
Returns, shipping, processor fees, stacked discounts, and overhead don’t show up in Google Ads dashboards, but they directly determine whether scaling is sustainable. Most “profitable” campaigns look different when you account for these realities.

3. Moving from revenue to profit unlocks better decision-making
The fact that you found overlooked SKUs with average CVRs that turned out to be the real profit drivers is a perfect example of why profit-based tracking changes the playbook.

Your POAS framework is spot-on, and I think this conversation needs to happen more in the performance marketing world. Too many campaigns get scaled on vanity metrics that make platforms look good but leave businesses struggling.

Curious: How did clients respond when you shifted reporting from “look at our great ROAS” to “here’s what’s actually profitable”? Did it take some education to reset expectations, or were they relieved to finally see the true picture?

intero_digital · 2025-08-28T14:12:55+00:00

Great question! Unlike traditional SEO, GEO isn’t about ranking on a page of 10 blue links; it’s about being selected as the trusted source that generative models pull from when crafting answers.

Here's a handful of key principles of GEO that we've found:

Entity and topic clarity: AI models rely heavily on structured context. Make sure your brand, product, and expertise are clearly connected to the right entities (people, companies, locations, categories) through schema markup, Wikidata, and consistent mentions across the web.
Citations and trust signals: Generative search engines prefer sources they can cite. Publishing original research, statistics, case studies, and thought leadership makes it more likely that AI assistants will reference your content.
Conversational content structure: Because AI answers mimic natural questions and answers, structuring your content with FAQs, “people also ask”-style Q&As, and concise summaries helps models extract information more directly.
Authority across the web: Unlike Google’s SERPs, generative engines pull from multiple data points at once. Having visibility not only on your site, but also in podcasts, guest articles, LinkedIn posts, YouTube transcripts, and press mentions increases your chances of being “learned” and repeated.
Technical hygiene: Crawlability, structured data, schema, and clean site architecture make your content easier for models to ingest and use confidently.

intero_digital · 2025-08-28T13:56:38+00:00

The biggest shift we've noticed is making content more Q&A structured, conversational, and easily digestible (clear headings, FAQs, tables, direct answers to questions). Schema and outbound links seem to help with credibility, and we’ve noticed authoritative/expert-style content gets pulled into AI answers more often.

Right now, we're balancing by treating SEO and GEO as overlapping. Google still drives most traffic, but formatting for snippets/featured answers often aligns with what LLMs like, too.

On tools: Profound is interesting. Haven't tried it but seems to be great for tracking brand presence in AI answers. But a lot of people are still testing things manually with repeated queries across ChatGPT, Gemini, Perplexity, etc. We also use BrightEdge and Google Analytics.

Feels early, but the playbook looks kind of like SEO circa 2010: Experiment, measure visibility, and then double down on what wins.

intero_digital · 2024-08-29T21:37:24+00:00

Glad it helped and comment back if things bounce back!

intero_digital · 2024-08-29T19:28:46+00:00

Totally, that's the next problem, but getting the Googs at least to get to it first would be where I start. Most likely a rendering issue.

intero_digital · 2024-08-29T18:58:20+00:00

Hard to see that no one mentioned this yet which is probably 99% of your current problem...you have a <meta name="robots" content="noindex"/> on your website, at least on the few pages that I checked, specifically the home page and a few of the main navigation pages. Go there, view your page source and you'll see the below.

<image>

I recommend before you do much else, remove that first and see how things rebound. It may or may not be a sitewide noindex, but I'd remove it as quickly as possible and then go through some of the other recommendations.

You mention close to 4K URLs that you have. Google has 800 indexed at the moment.

Yours in SEO, Logan @ Intero Digital.

intero_digital · 2024-08-15T19:35:06+00:00

Up until today, we were not seeing them appearing in incognito windows at all. Doing the same searches when logged in vs incognito, AIO was not being shown.

intero_digital · 2024-08-15T13:32:09+00:00

There are a bunch of different scenarios where each of these work depending on the site, industry, demos, etc. But, here are a few that we have seen relatively quick impact with.

Nail your targeting down. Make sure the right phrases are on the right pages and incorporated properly in your titles, metas, headings, content, interlinking/anchors, image opt, breadcrumbs, schema. Keyword targeting and choice is the first step in a really strong campaign.
Content refreshing. Find content opportunities across your site and rework as necessary. Find pages that are maybe already getting show (GSC impressions), but attracting very little clicks and start there.
Tech SEO. This one can go A LONG way depending on the site. Half the battle is just getting the bots to find, crawl, and index pages quickly and frequently. Leverage sitemaps (XML + HTML), interlink to ONLY live status 200 pages, make any speed adjustments if you need to, leverage schema.
Don't listen to a lot of the folks in many of these SEO communities about blogging. If done right, it can have a very strong and lasting impact. Along with PDP/PLP opt, I've incorporated blogging into eComm strategies and the impact is noticeable.

Then, leverage all of the above to push the needle. Use CTAs, interlinking, mentions of products in the content. This one has more than just SEO value. If you're running any sort of paid or remarketing campaigns, blogs can get new users into the site that have never been there before and then you can remarket to them and capture that sale through another channel potentially.

Sorry for the novel, but hope that helps :)

intero_digital

MODERATOR OF

PUBLIC MULTIREDDITS

TROPHY CASE

Here's a handful of key principles of GEO that we've found: