How do we show up in AI?
As a marketing enablement partner, it’s a question we often field these days from our clients. And while our goal is to help clients achieve visibility, we recognize it’s just as important to be able to show impact.
That’s why marketing reports, much as the industry itself, are changing. It’s a matter of folding in new metrics that showcase the value of AEO and GEO investments, alongside traditional SEO. But it’s also about leveraging AI tools to provide more insights and depth to the reports shared.
Here’s a look through our lens to help you see how AI is affecting marketing reporting, and what you can do to shape meaningful stories around your own metrics.
Traditional SEO has centered around rankings: Where do we appear on Google? How many keywords are in the top 10? With artificial intelligence, the conversation revolves around citations and visibility.
Think of it like a Venn diagram. SEO still drives discoverability, while AEO/GEO visibility shows how often your brand appears, is cited or influences results in generative AI solutions like ChatGPT, Gemini or Perplexity. There’s overlap between the two, but new territory to explore and metrics to measure.
One area of focus in reporting is AI referrals. In HubSpot, you can see a breakdown of how many sessions and new contacts came from ChatGPT, Perplexity, Gemini and Copilot. You can then look at the notes section on each new contact record and see if quotes were generated to show revenue impact.
We’re also tracking SERP-featured keywords that trigger AI overviews or summaries. A detailed how-to blog might not hold the top organic spot, but if it’s cited in an AI-generated overview, it’s still winning high-value visibility that can drive more qualified traffic and engagement.
When you start to see new contacts or quotes tied to AI referrals in HubSpot, surface those insights in digital marketing reports. At the same time, track them month over month so there’s a holistic view of how many new leads came through AI-assisted search and how they’re contributing to revenue goals.
We’re doing this for many clients already. We’ll highlight new deals that originated from ChatGPT referrals or AI overview citations in weekly meetings to demonstrate tangible business outcomes that these appearances are creating. It’s a quick way to bridge the gap between “Are we showing up in AI?” and “We can see how that visibility is paying off.”
(In six months, one manufacturer saw 583 sessions from ChatGPT — six of which turned into active quotes.)
It also helps to make the story visual. When our clients’ content starts appearing inside Google’s Search Generative Experience (SGE), we capture those examples directly in reports. We’ll show the overview, highlight how it’s structured and then connect that to the content creation behind it. (Glossary pages and how-to guides tend to perform especially well because this type of content marketing aligns with how AI tools summarize trusted information.)
Using these examples helps marketing professionals explain why it’s working: the consistent formatting, the trusted tone, the helpful structure. This builds buy-in across teams and leadership: they start to understand how AI visibility complements SEO, supports enablement content and fuels the lead pipeline.
An LLM tracker is a new kind of visibility metric that helps marketing teams understand how and where their brand is being mentioned across large language models. You can see how your brand, products and content are cited within generative AI tools, providing insights into which topics or pages have the biggest impact on AI-generated responses and where there’s room to expand in your marketing efforts.
Consider query fan-outs, as an example. If you ask ChatGPT the same question multiple times, the answers will vary slightly. Each variation shows how the model interprets your query and which sources it pulls from.
Instead of doing this manually, an LLM tracker automates the process. The AI technology runs defined prompts across tools like ChatGPT or Gemini, gathers the responses and logs where your brand or content is mentioned. From there, it can and should cluster the data to highlight which themes, phrases and sources appear most often.
If ChatGPT consistently references a client’s thought leadership articles on “sustainable packaging” but skips over their product or solution pages, it’s a cue to strengthen internal linking or optimize product content with more contextual authority. If a software company sees its brand cited for “AI integrations” but not for “data security,” that signals an opportunity to publish deeper content reinforcing credibility in that space.
The true value of LLM tracking comes from perspective. It’s a bird’s-eye view of where your brand fits within generative search: what AI tools are saying about you, what they’re not, and how that influences audience discovery. When folded into traditional reporting, these insights make your dashboards more comprehensive and your strategy more proactive.
An important note: Not all LLM trackers are created equal, and it’s important to understand how each tool gathers information. Asking questions about their data sources and overlap with Google results helps verify that insights are accurate and allows you to move with confidence.
AI can help turn marketing performance data into stories that reveal what’s really driving growth.
By exporting data from HubSpot, de-identifying it to remove personal information and asking AI to compare results quarter over quarter, we’ve uncovered insights traditional reports can miss. In one case, a client had slightly fewer leads in Q3, but AI revealed that the pipeline was healthier with over double the value. Leads were of higher quality, and deals were closing faster.
That’s the kind of context and competitive advantage that executives care about.
AI can also make reporting more digestible. With key findings identified, you can use AI tools to create data visualizations or infographics. For instance, you could use AI to build an infographic comparing channel performance across organic, paid and referral sources. A spreadsheet of numbers becomes a dynamic visual showing which channels drive the highest-value leads.
Of course, how we use AI technology matters just as much as what we use it for. Circling back to the point above, every analysis starts with responsible data handling: stripping out sensitive details, maintaining privacy and keeping human judgment at the center of interpretation.
Used thoughtfully, AI can enrich marketing reports, celebrating what’s working, uncovering what’s improving and pointing the way toward what’s next.
Yes, AI visibility is opening new doors for discovery, but SEO remains the foundation of marketing strategies. The goal, as we’ve highlighted before, is to build a system that protects the rankings you’ve earned while expanding your presence across emerging AI platforms.
At Kuno, we help clients focus on that balance. We focus on expanding your presence and impact across AI search while making sure your organic rankings stay in a strong spot.
It’s this mindset — growth with stability — that defines modern marketing enablement. You need to understand where the right opportunities lie, and how to measure their impact responsibly.
Our team partners with marketing leaders to make sense of complex data, uncover new opportunities and protect the results that matter most. Whether it’s integrating AI insights into your HubSpot reporting, building dashboards that connect visibility to revenue or refining your SEO efforts to align with search everywhere optimization, we help you move the needle forward.
If you want to stay visible and stay confident in where your marketing’s headed, let’s talk.