In the AI-first customer journey, website clicks and session counts aren't as relevant. Instead, practitioners need to understand metrics such as visibility, citation frequency and AI referral traffic – then link it all back to customer acquisition cost (CAC) and business impact.
This article draws on insights from CX Network's AEO Masterclass featuring Anish Singhal, VP of product management for Sprinklr, and Melanie Mingas, editor-in-chief at CX Network. The masterclass covered how organizations can measure the impact – and benefits of – their AEO and GEO programs.
This article examines how brands should select and use metrics for agentic commerce, the existing metrics that should remain in the toolkit and the additional metrics that are required to effectively measure an AEO and GEO program.
Watch the conversation in full via this link.
Measuring AI-mediated influence in the invisible journey
When consumers use AI assistants to initiate their customer journey, they can bypass a retailer's website entirely. Singhal says the resulting, compressed buyer journey, is essentially invisible to the brand.
"Buyers are comparing, shortlisting, and making decisions without ever leaving the LLM interface in most cases," he explains. "If we only measure traffic, we miss a huge part of AI mediated influence," he adds.
This means brands need to measure AEO across two outcomes: visibility and business impact.
Outcome 1: Brand visibility and closing the gaps
The first thing to consider is how to improve brand visibility inside LLMs. Singhal explains: "It's pretty straightforward. The metrics around this are share of voice, sentiment around your brand, and prompt coverage, which is also very important."
Even more important, however, is the prompt closed gap rate, i.e. how quickly your team is closing visibility gaps in high intention prompts.
"These metrics help you understand whether AI knows you, it trusts you and recommends you in the moments that matter," Singhal says.
Outcome 2: Downstream business impact
The second outcome is downstream business impact. Singhal says relevant metrics in this respect include LLM referral sessions, citation to click rate, AI traffic growth and the conversion quality of AI referred users.
Linking AI journeys to sales volume
Practitioners must then start correlating these insights with sales volumes.
Singhal says: "I hear skeptics says if AI traffic is only two or five percent of overall traffic, why do I need to build a discipline around AEO? My answer to them is that when you're looking at that traffic, you need to realize it's very high intent traffic."
"If brands are able to measure the conversion for that particular cohort, they will start understanding that AEO is here to stay and that they have to start investing there," he adds.
The most important mindset shift Singhal says is that AEO is not about traffic. "It is about visibility and influence. A brand may not get the click but it may still win the recommendation inside the elements itself," he explains. "In AI search, that recommendation can shape consideration earlier and it can be even more decisive than a website visit could have ever been," he adds.
In short, measurement is about shifting from a mindset of channel performance to influence performance. Singhal says the goal should not simply be to rank, but to be recommended, trusted and chosen inside the AI mediated journey.
Linking the metrics of AI search to customer acquisition costs
Everybody in CX knows that lifetime value to acquisition should comfortably sit at a ratio of 3:1. That means a customer generates US$3 in lifetime value for every $1 spent to acquire them.
Because AI search generates high-intent leads that more often convert into sales, AEO – technically – can reduce CAC. AEO can also reduce ad spend, although the economics of this are expected to alter rapidly. The companies behind the LLMs are introducing in-chat adverts and organizations must still direct time and resources to site optimization. All this comes at a cost.
However, a study published by Adobe monitored websites in March 2026 and found AI traffic converted to sales 42 percent better than non-AI traffic. AI-driven revenue per visit was 37 percent higher than traffic from other sources.
The rise in AI conversion is reinforced by Adobe's data on engagement and bounce rates. Data from the same month showed that once an individual lands on a US retail site from an AI source, the engagement rate is 12 percent higher compared to non-AI traffic.
These shoppers are essentially spending more time on the website, by around 48 percent, and browsing 13 percent more pages per visit.
The stats speak for themselves: If managed correctly through AEO and GEO and measured accurately, AI search can become a hugely lucrative and quantifiable opportunity. The benefits, however, will not be reaped automatically. CX practitioners must work closely with marketing and operations to ensure their full proposition is customer centric and machine readable.
Quick links
- The invisible shelf: How GEO is revolutionizing customer experience perceptions
- When your customer is a machine: Rethinking service design for AI agents
- The human-machine translator: CX's most important new role