“What KPIs do I use to measure success in AEO, GEO, or AI search?” ← I’ve been hearing this question non stop lately. And if you’re leading marketing at a B2B SaaS company, I’m sure you have too.

Let me reassure you. At the end of the day, some metrics absolutely are not changing when it comes to knowing your GEO strategy is moving in the right direction.

Pipeline, closed won deals, ARR, profit. Nothing else matters if you’re not seeing incremental lifts in those areas from your spend over time.

But that’s no excuse to throw money blindly at the latest shiny object or tactic you see on LinkedIn.

Right now, GEO and SEO mostly overlap, with a few shifts in which tactics matter most and some new considerations. But there are early signals that can tell you you’re headed in the right direction.

These are the new KPIs that matter when measuring success with generative engine optimization.

GEO KPIs TL;DR

Traditional SEO KPI Modern GEO KPI Notes on Evolving Role Tools to Track How Different from Traditional SEO KPI?
Organic Traffic (sessions from search) LLM Referral Traffic (visits from AI answers) Still critical, but now includes site visits originating from tools like ChatGPT, Gemini, Site Copilot, and Perplexity. GA4 can filter by referrer or use UTMs for links embedded in AI. GA4, Adobe Analytics, log analyzers Somewhat Different
Impressions (SERP appearances) Prevalence in AI Overviews (appearance in Google’s AI-generated summaries) Instead of a blue-link impression, showing up in AI Overviews (Google), Gemini, or Perplexity means you’re part of a zero-click answer. This is brand exposure even without clicks. Useful in both B2B and B2C. Manual checks, Scrunch, Profound Very Different
Click-Through Rate (CTR) Zero-Click Presence Rate (how often your brand appears but isn’t clicked) CTR matters less when users get answers directly from the AI. This new KPI captures presence even when there is no user action. Prevalent in Perplexity and Google AI Overviews. Scrunch, Profound, manual tracking Very Different
Average SERP Position AI Prominence (where and how early you appear in AI answers) No fixed rank, but prominence matters. Being the first brand cited in an AI Overview or LLM output gets the most trust and attention. Prompt testing, manual analysis, Profound Very Different
Backlinks AI Citations (how often you’re named or linked as a source by an LLM) These are the “backlinks” of GEO—citations in AI answers validate credibility. Especially useful in B2B and high-consideration spaces. Bing Chat, Google Overviews, Profound Somewhat Different
Share of Voice (SERP visibility) Brand Mentions in LLMs (share of answers that reference your brand) Tracks how often your brand is mentioned by Gemini, ChatGPT, or Perplexity vs competitors. Great proxy for visibility even without clicks. Scrunch, Profound Very Different
Bounce Rate / Time on Site Conversational Engagement (user follow-up actions within the LLM) Shift from on-site behavior to in-AI behavior. Did the user ask a follow-up question? Search your brand after seeing it in an AI? This signals interest without a visit. Experimental: prompt replay, LLM plugins Completely New
Conversions from Organic Search Conversions from Generative AI Referrals Still a core KPI. Track form fills, demo requests, or purchases from LLM-linked traffic (e.g. ChatGPT or Perplexity referrals). Can be captured with custom UTMs, campaign source fields, or post-lead surveys. GA4, CRM tagging, form attribution Somewhat Different

Organic Traffic → LLM Referral Traffic

Notes on Evolving Role Still critical, but now includes site visits originating from tools like ChatGPT, Gemini, Site Copilot, and Perplexity. GA4 can filter by referrer or use UTMs for links embedded in AI.

Tools to Track GA4, Adobe Analytics, log analyzers

Difference from Traditional KPI Somewhat Different

Impressions → Prevalence in AI Overviews

Notes on Evolving Role Instead of a blue-link impression, showing up in AI Overviews (Google), Gemini, or Perplexity means you’re part of a zero-click answer. This is brand exposure even without clicks. Useful in both B2B and B2C.

Tools to Track Manual checks, Scrunch, Profound

Difference from Traditional KPI Very Different

Click-Through Rate (CTR) → Zero-Click Presence Rate

Notes on Evolving Role CTR matters less when users get answers directly from the AI. This new KPI captures presence even when there is no user action. Prevalent in Perplexity and Google AI Overviews.

Tools to Track Scrunch, Profound, manual tracking

Difference from Traditional KPI Very Different

Average SERP Position → AI Prominence

Notes on Evolving Role No fixed rank, but prominence matters. Being the first brand cited in an AI Overview or LLM output gets the most trust and attention.

Tools to Track Prompt testing, manual analysis, Profound

Difference from Traditional KPI Very Different

Backlinks → AI Citations

Notes on Evolving Role These are the “backlinks” of GEO—citations in AI answers validate credibility. Especially useful in B2B and high-consideration spaces.

Tools to Track Bing Chat, Google Overviews, Profound

Difference from Traditional KPI Somewhat Different

Share of Voice → Brand Mentions in LLMs

Notes on Evolving Role Tracks how often your brand is mentioned by Gemini, ChatGPT, or Perplexity vs competitors. Great proxy for visibility even without clicks.

Tools to Track Scrunch, Profound

Difference from Traditional KPI Very Different

Bounce Rate / Time on Site → Conversational Engagement

Notes on Evolving Role Shift from on-site behavior to in-AI behavior. Did the user ask a follow-up question? Search your brand after seeing it in an AI? This signals interest without a visit.

Tools to Track Experimental: prompt replay, LLM plugins

Difference from Traditional KPI Completely New

Conversions from Organic Search → Conversions from Generative AI Referrals

Notes on Evolving Role Still a core KPI. Track form fills, demo requests, or purchases from LLM-linked traffic (e.g. ChatGPT or Perplexity referrals). Can be captured with custom UTMs, campaign source fields, or post-lead surveys.

Tools to Track GA4, CRM tagging, form attribution

Difference from Traditional KPI Somewhat Different

Key GEO KPIs and How To Measure Them

If SEO gave us impressions, backlinks, and SERP position, GEO hands us an entirely new playbook. You’re not just trying to rank anymore. You’re trying to be remembered, cited, paraphrased, and maybe, if the LLM likes you, linked.

Here’s a breakdown of the GEO KPIs that actually matter, how to measure them today, and why they’re worth your time.

1. Brand Mentions in AI Responses

This is your new “share of voice” in the AI world. If ChatGPT, Gemini, or Perplexity keeps mentioning your brand when users ask about your category, you’re already winning. No click required. Just consistent visibility.

Tools to use: Scrunch AI, Profound

How this helps you:

  • Tells you if your brand is even part of the conversation.
  • Helps you compare visibility against competitors inside AI tools.
  • Gives you a measurable way to validate your GEO efforts beyond web traffic.

How this compares to SEO:

  • Equivalent to Share of Voice or SERP impression share.
  • But in this case, users don’t see a blue link. They just hear your name. And that still matters.

2. AI Citation Count and Quality

Mentions are good. Citations are better. When an LLM credits your content with a link or named source, that’s the AI version of a backlink. It brings traffic and authority.

Tools to use: Bing Copilot, Google AIOs, Perplexity, Ahrefs AI Overviews Tool, Scrunch AI, Profound

How this helps you:

  • Shows which of your pages are being credited by LLMs.
  • Helps you catch outdated or incorrect attributions before they spread.
  • Tells you whether your structured data and authority signals are working.

How this compares to SEO:

  • Equivalent to backlinks.
  • But here, the citation happens in an AI response, not another website. Still builds authority. Still drives traffic.

3. Content Relevance (Embedding Similarity)

Generative engines don’t care about keywords the same way anymore. They rely on vectors. Your content has to match the meaning of a user’s query, not just the phrasing.

Tools to use: Screaming Frog, Go Fish Digital AI Extension, MarketMuse, Clearscope, Weaviate

How this helps you:

  • Confirms whether your content “speaks the same language” as LLMs.
  • Identifies which pages are likely to show up in generative answers.
  • Helps guide content creation that aligns with how AIs process queries.

How this compares to SEO:

  • Equivalent to keyword optimization and semantic coverage.

4. Pages Indexed in AI or Vector Presence

If an AI hasn’t seen your content, it can’t use it. This KPI tracks how much of your site is actually visible to LLMs and vector-based search tools.

Tools to use: Weaviate, GPTBot Crawler Logs, Common Crawl, server log analyzers

How this helps you:

  • Confirms which pages are being seen by AI crawlers.
  • Helps identify content that needs better structure or visibility.
  • Surfaces crawl issues that may block inclusion in AI-generated results.
  • Supports decisions around page prioritization and metadata improvements.

How this compares to SEO:

  • Equivalent to index coverage in Google Search Console.
  • Just like unindexed pages can’t rank, un-ingested pages can’t show up in AI answers.
  • Requires similar technical hygiene, but across multiple platforms and AI systems.

5. LLM Traffic and Conversions

This is where GEO meets ROI. If someone visits your site after interacting with an AI, that’s GEO working as a pipeline channel.

Tools to use: Google Analytics 4, Adobe Analytics, HubSpot, CRM lead source tagging, UTM tracking

How this helps you:

  • Captures traffic from AI tools like ChatGPT, Perplexity, and Bing AI.
  • Links awareness in generative answers to direct business impact.
  • Uncovers attribution gaps where AI influence leads to late-stage conversions.
  • Validates whether GEO is worth investing more time or budget.

How this compares to SEO:

  • Similar to tracking conversions from organic search.
  • But instead of users clicking from a Google result, they arrive from AI references.
  • Often part of multi-touch journeys, so it’s more indirect than search traffic.

6. Brand Sentiment in AI Outputs

Not all mentions help. If ChatGPT tells users your platform is “fine but limited,” that’s a reputation problem, not a win.

Tools to use: Scrunch AI, Profound, ChatGPT, Claude, manual prompt testing

How this helps you:

  • Detects harmful, outdated, or misinformed content inside AI responses.
  • Helps you clean up how your brand is being interpreted or paraphrased.
  • Identifies patterns in perception that may be dragging on trust or conversions.
  • Acts as a feedback loop for brand messaging and content clarity.

How this compares to SEO:

  • Similar to monitoring review snippets or sentiment in branded SERP results.
  • But AIs blend multiple sources into a single response, so poor representation can be amplified.
  • No review stars to buffer it—tone and phrasing are everything.

Emerging and Experimental GEO KPIs to Watch

The usual metrics are a good starting point, but there are a few new ones that might matter more than we think. These are the ones people are starting to play with. Some are rough around the edges, some are hard to measure today, but all of them have potential if you’re serious about staying ahead.

1. Conversational Engagement Rate (CER)

This tracks whether users take an action after an AI mentions you. If someone asks about the best tools in your category, and the AI mentions you, does the user ask more about your brand? Do they click through? Do they search for you next? That’s CER. It’s like a conversion rate inside the conversation.

Tools to use: Manual prompt testing, LLM plugin analytics (if available), in-app event tracking, OpenAI API, Claude API

How this helps you:

  • Tells you if your brand mention is just filler or actually drives interest.
  • Helps you evaluate how persuasive your content is when summarized by an AI.
  • Pushes you to improve brand positioning and phrasing inside AI responses.
  • Becomes a leading indicator for future traffic or conversion trends.

How this compares to SEO:

  • Closest match is click-through rate (CTR).
  • But instead of SERP impressions, the action happens mid-conversation.
  • It’s about interest, not just visibility.

2. Query Coverage Gap Score

This is the other side of coverage. Instead of counting where you show up, this tracks where you’re missing. If you’ve got 100 high-value prompts in your space and your brand shows up in 30 of them, the other 70 are your gap.

Tools to use: SearchMorph, internal prompt banks, LLM prompt testing workflows, Google Sheets

How this helps you:

  • Shows the blind spots in your current content or brand presence.
  • Helps prioritize content production around high-value missing topics.
  • Provides a quantitative goal: reduce the gap over time.
  • Tells you if competitors are winning the AI mindshare in areas you care about.

How this compares to SEO:

  • Equivalent to keyword gap analysis tools like Ahrefs or Semrush.
  • Instead of SERPs, this maps gaps in generative engine results.
  • Useful for mapping AI blind spots against your actual keyword strategy.

3. Positioning Score (AI Prominence Index)

This tells you where in the answer your brand shows up. Are you the first name mentioned? The first source cited? Or are you buried at the bottom? That positioning can make a big difference.

Tools to use: Manual prompt testing, response parsers, OpenAI API, custom scripts with GPT-4 or Claude

How this helps you:

  • Helps you measure how often your brand leads versus trails.
  • Provides clarity on whether you’re seen as the authority or just one of many.
  • Identifies competitive gaps in prominence even if mentions are equal.
  • Pushes you to optimize not just for inclusion, but for lead positioning.

How this compares to SEO:

  • Closest match is average SERP position.
  • But in AI results, there’s no rank number—just placement in narrative flow.
  • Being the first mentioned often equals higher trust and influence.

4. Semantic Content Fitness (SCF) Score

This is a rough measure of how AI-friendly your content is. It pulls together a bunch of signals like structure, markup, facts, and clarity. The idea is to score how well your content is set up to be used by LLMs.

Tools to use: MarketMuse, Clearscope, Schema.org validators, internal SCF checklists

How this helps you:

  • Makes sure your content has the elements AIs prefer: structure, citations, clear formatting.
  • Helps your team focus on content quality, not just keyword density.
  • Encourages the use of schema and markup to make your content more digestible.
  • Builds a consistent internal standard for content that serves both SEO and GEO.

How this compares to SEO:

  • Similar to content optimization scores (like Surfer SEO or TF-IDF tools).
  • But the focus here is on readability and utility for machines, not just rankings.
  • Helps close the gap between “good blog” and “usable by an LLM.”

5. LLM Accuracy Audit Rate

This one’s simple. How often does an AI get the facts right about your brand? Are they pulling the right data from your content or just making stuff up?

Tools to use: ChatGPT, Claude, Bing Chat, internal brand fact sheet

How this helps you:

  • Prevents misinformation about your brand from spreading via AI.
  • Gives you a list of facts to reinforce across your content and metadata.
  • Helps you proactively fix gaps before they turn into bad AI summaries.
  • Especially critical in regulated or high-stakes verticals.

How this compares to SEO:

  • Most like brand reputation monitoring or rich snippet accuracy.
  • But instead of Google pulling bad data, the AI is misrepresenting it in conversation.
  • No search result to correct—so it’s on you to feed the right info upstream.

Want Help With Your GEO Strategy?

You don’t have to figure this out all by yourself.

We’re experimenting with visibility inside of generative AI tools and seeing success for ourselves and our clients each and everyday.

Book a call for a GEO strategy session, on me.

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