Since clicks from LLMs are low, proving AEO ROI is tricky. Track three key metrics: your brand's share of voice for key prompts, direct customer feedback via "How did you hear about us?" forms, and any referral traffic from the LLM platforms themselves.

Generative AI tools like ChatGPT disproportionately cite customer review platforms, such as Gartner Peer Insights, over traditional analyst reports. This means a company's visibility in AI-driven search now depends more on user reviews than direct analyst engagement, forcing a strategic shift.

To show ROI beyond declining organic traffic, use a three-layer model. 1) Direct attribution from GA4 organic/AI traffic. 2) Influenced attribution via increases in branded search, direct traffic, and shorter sales cycles. 3) AI visibility, measuring share of voice in LLMs against competitors.

AI models often cite a brand's content as a source while recommending its competitors in the same answer. This means the cited brand did the work while a competitor got the benefit. Focusing on citation volume is a vanity metric; the only goal is direct recommendation.

Traditional metrics like reach are becoming obsolete. The new imperative is to measure how AI models interpret and present your brand. This involves tracking a 'share of influence' across earned media, analyst reports, and reviews, as well as monitoring AI prompt results and citations to gauge brand authority and message consistency.

Tracking success in LLMs isn't about UTMs, as it's top-of-funnel discovery. Instead, use three key metrics: Share of Voice (% of time you appear vs. competitors), Mention Rate (% of time your brand is mentioned), and Citation Rate (% of time your site is linked in an answer).

For the first time, tools tracking "AI Visibility"—how often a brand is cited in LLM responses—can directly measure the impact of brand-building activities. This allows CMOs to finally prove the ROI of brand investments, treating brand as a quantifiable performance engine rather than an abstract concept.

To properly measure brand presence in AI, use specialized tracking tools (like Profound or Ahrefs) that systematically run hundreds of prompts across various LLMs. These systems track website citations and ranking changes, providing a more reliable, directional view of performance than individual, personalized searches can offer.

To determine if your AI visibility efforts are working, move beyond guessing. Establish a fixed set of prompts (probes) and run them on a regular cadence against target AI engines like ChatGPT and Perplexity. Track which engines cite, paraphrase, or hallucinate to create a data-driven performance benchmark.