What metrics should you use for SEO/AEO?
How should SEO be measured in 2026? Revenue.
This week’s newsletter is sponsored by North Star Inbound and Semrush Enterprise
Paid subscribers can download my AEO+ SEO Playbook, presented at Google
In every podcast, presentation, and webinar I have done over the last year, I have received a variation of the same question: What is the best way to measure SEO/AEO impact? (Check out some of these appearances: CapitalG, Greylock, Airops) To me, this answer has remained unchanged throughout my entire SEO career, but I have realized that not everyone has viewed SEO through the same lens.
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To many, SEO success was about “rankings,” clicks, or other metrics closer to vanity than actual performance. With AI-driven search engines now dominating conversations on the future of SEO, those metrics are outdated. If you are still measuring SEO by keyword positions or total organic visits, you are optimizing for irrelevance.
Rank checking is obsolete
The old playbook of measuring your SEO success by where you appear on search is obsolete and has been for a long time, but many were unaware. The AI shift now demands it. Even better, it now requires thinking like a product manager, where SEO drives real revenue and retention rather than fleeting visibility.
Today’s SEO requires thinking of the user journey. For example, a user asking for the best travel website wants an actual travel site, not just a website about travel. Not an article about the best websites. Your article might “rank” on that, but it doesn’t meet the user’s intent.
Clicks are plummeting, and traditional metrics crater because they are detached from user intent. Even worse in the travel example above, ranking first means nothing if AI scrapes your content and serves it without attribution. You will have done the work to create the list, and the LLM will showcase it.
SEO strategists must think like product managers instead, where SEO effectiveness should be measured by how well it contributes to the business, whether that’s acquisition or retention. In a product-led world, SEO isn’t siloed. It’s woven into the entire customer journey and is part of a holistic marketing function. SEO is the first, second, or sometimes even the last hand guiding users into your product’s value loop.
Revenue tracking
The foundation of organic search traffic, whether from traditional search or LLM measurement, is revenue attribution. This is hard, but not impossible. Some can use multi-touch attribution to credit organic discovery throughout the funnel. Tools like GA4 or Amplitude let you track organic-assisted revenue, identifying dollars from users who first found your brand via search, even if they converted later.
The reality of multi-touch attribution is even messier than it sounds. Modern users touch multiple channels on multiple devices before converting. They might discover you through organic search, return via a paid ad, and convert via email. Which channel gets credit?
This isn’t just a technical question; it’s a political one. The paid team will fight for their share of the attribution. Your email team wants their credit. You need to establish upfront rules for how credit is split and secure buy-in from leadership that this will be the way everyone is measured.
Even if you don’t have the budget or capabilities to integrate a tool like this, you should know, directionally, whether your efforts are working. Without knowing the revenue from this channel, how could you even know whether it’s something you should continue investing in?
Perfect models aren’t required
I’ll be honest about how hard this actually is, and to be even more honest, I have never seen it done in a way that everyone in an organization likes. Setting up proper revenue attribution requires engineering resources, data infrastructure, and cross-team coordination that most companies simply don’t have. You need your analytics team, engineering, marketing, and product all aligned on tracking parameters. You need clean data pipelines and someone who can write SQL or work with your data warehouse. For smaller teams or companies without a dedicated analytics function, this can be impossible.
Don’t aim for perfect, just start where you are. If you can’t implement full multi-touch attribution right now, begin with last-touch attribution in whatever analytics tool you have. It’s imperfect, but it’s better than nothing. Track organic as a source and see what revenue you can definitively attribute to it.
From there, work backward to build more sophisticated tracking as resources allow. The key is to start measuring something today rather than waiting for the perfect setup. For LLMs, they will not appear as organic-sourced traffic; therefore, they should be evaluated like any referral site. On many sites, I have seen Reddit drive significantly more traffic and conversions than all LLMs combined.
The metrics to use CAC + LTV
As I wrote a few weeks ago, SEO should have a defined Customer Acquisition Cost (CAC) for the channel. (Paid subscribers download the template here). Cost calculations need to be thorough to support ROI calculations. On the “R” side of ROI, the revenue number should ideally be LTV, not just the value of the first sale.
Measure how long they stick around and how much they spend, compared with other cohorts. Use cohort analysis to segment organic users and track activation rates. Organic LTV often exceeds other channels because these users are self-qualified through intent-driven discovery.
This means you also need to track conversion rates within the product from users who came from search, because the goal of SEO isn’t just conversions on the first touch. This works great with products that have free aspects or trials. Monitor sign-ups, feature trials, or upgrades triggered by organic entry points. If content funnels users into an interactive tool, measure the drop-off from landing to action.
Indirect impact
Most of the benefits of AI visibility will impact brand channels. Use surveys to quantify increases in brand recall. If your content consistently appears in AI-generated answers, it will correlate to brand search. Track branded organic traffic as a proxy for authority.
Share of Voice in AI responses is the new frontier, and this is fundamentally a brand metric. Measuring Share of Voice in responses is still evolving, and honestly, the tooling isn't great yet. Right now, your best approach is manual spot-checking combined with tools like those from Semrush or similar platforms that track AI citations.
Set up a list of your key topics and queries, then regularly check ChatGPT, Claude, and Google's AI Mode/Gemini to see if you're being cited. Track the percentage of times you appear and in what context. It's labor-intensive, but until better automated solutions exist, this manual tracking gives you a baseline. Pair this with branded search volume in Google Search Console. If you're appearing in AI responses consistently, you should see branded searches increase over time.
The downstream effects of brand visibility will lead to more direct visits and other dark traffic. While you cannot track non-visits directly, you can infer them through halo effects by monitoring spikes in direct traffic, social mentions, or app downloads correlated with high-impression queries. These new visits should eventually convert into revenue; if they don’t, the top-of-funnel message is incorrect.
Measure what matters
Measuring organic performance in 2026 boils down to business impact, not vanity. Yes, proper analytics for a channel like SEO will always be a challenge, but don’t use that as an excuse to not report on the metrics that matter. By focusing on revenue attribution and user value, you will turn SEO into a scalable growth engine as you discover the levers to pull.
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