How to Measure the Performance of GEO-Optimised Pages

How to Measure the Performance of GEO-Optimised Pages

Measuring GEO performance requires a fundamentally different approach from traditional SEO metrics. AI generated responses don't appear in Google Search Console, citation frequency isn't tracked by rank trackers, and a brand can earn hundreds of AI mentions without generating a single click.

Key takeaways:

• GEO performance measurement covers three layers: AI visibility, AI referral traffic, and brand authority signals in generative engines
• Traditional SEO tools miss the majority of GEO performance because they weren't built to track AI generated answers
• Only 30% of brands remain visible across back-to-back AI responses for the same prompt, making continuous monitoring non-negotiable
• AI referral traffic converts 31% better than non-AI traffic, making it a high-value channel regardless of current volume

The brands that measure GEO performance well share one habit: they stopped treating AI citations as a byproduct of SEO and started tracking them as a primary channel metric. We've seen this shift produce clearer, faster decisions at FirstMotion client organisations than any other single change in how they report on search. The AI search revolution created a measurement problem before it created a strategy problem, and this guide solves the measurement layer first.

What is GEO and why does measurement matter?

Generative engine optimization, or GEO, is the practice of making your content citation-worthy inside AI generated answers across ChatGPT, Perplexity, Google AI Overviews, Google AI Mode, and Google Gemini. In today's digital landscape, Gartner predicts a 25% search volume drop by 2026 as AI answer engines replace traditional search queries. McKinsey confirms more than 70% of organisations now regularly use generative AI in at least one business function.

6sense's 2025 buyer research found 94% of B2B buyers used generative AI tools during their most recent purchase process. Google's own data confirms AI Overviews now appear in roughly 50% of all searches globally. A brand appearing consistently in AI generated search results but not ranking in traditional Google search shows zero impressions in Search Console, producing a false picture of invisibility.

GEO investment without measurement is invisible by definition. Closing that gap makes the AI layer of discovery visible, actionable, and connected to the business goals that justify the investment.

Why traditional SEO metrics don't capture GEO performance

Unlike traditional SEO, GEO operates on three different measurement units. Visibility is measured in mentions rather than rankings. Authority is measured in citation frequency across AI platforms rather than backlinks. Success includes zero-click interactions where a brand earns influence in an AI generated answer without producing a session in Google Analytics 4.

Rankings, impressions, and click-through rates all assume visibility produces traffic. GEO breaks that assumption: AI responses frequently produce zero clicks even when a brand appears prominently, and that visibility doesn't register in any standard analytics tool. Traditional keywords, impressions, and sessions all undercount GEO's commercial contribution in ways that compound over time.

Paid media campaigns running during periods of strong AI citation activity also tend to see higher branded click-through rates, suggesting brands that are AI cited convert better across every channel. Building a parallel GEO measurement framework isn't an alternative to traditional SEO reporting. It's an addition that reveals the data-driven insights organic dashboards will never surface on their own.

The GEO measurement framework: three layers

GEO performance sits across three distinct layers. No single layer tells the full story, and all three need monitoring in parallel to build an accurate picture of GEO success.

A brand can score well on AI visibility metrics while generating almost no AI referral traffic. A brand can drive meaningful referral sessions without appearing in any GEO tool's citation tracking because traffic arrives via direct navigation after an AI conversation. Tracking all three layers together is the only way to build an accurate picture of GEO success.

Layer one: AI visibility and brand visibility metrics

AI visibility measures how often a brand appears in AI generated responses across AI platforms, in what position, and in what context. GEO performance varies significantly across multiple AI platforms and geographic markets, so tracking each separately is essential. The core AI visibility metrics to track are:

• Citation frequency: how often your brand appears in AI responses to prompts in your category, measured across a consistent prompt set on each platform. A steady increase in citation rates indicates effective content promotion and growing brand authority in generative search
• AI share of voice: the percentage of AI responses in your category mentioning your brand versus competitors, giving competitive positioning data that traditional SEO never surfaced
• Brand position: the position at which your brand appears in a response. First-position mentions carry significantly more weight with your target audience than trailing references
• Sentiment score: how AI powered search systems describe your brand and whether that description appears in positive context or with qualifying language that reduces buyer confidence
• Accuracy: whether AI generated descriptions of your product, pricing, and positioning are factually correct

Localised messaging and personalisation tailored to specific regions improves the probability of appearing in AI generated answers for that market. A brand with strong UK coverage but thin US media presence will see materially different AI visibility across those markets, which directly affects reach with the intended target audience.

Layer two: tracking AI generated referral traffic

Adobe Digital Insights analysed over one trillion visits to US retail sites during the 2025 holiday season and found AI referrals converted 31% better than non-AI sources. Visitors from AI platforms spent 45% more time on site and viewed 13% more pages per visit. A steady increase in AI referral traffic in GA4 is one of the clearest indicators of effective GEO efforts and improving content authority in generative search.

AI referral traffic arrives in GA4 via three routes:

• Direct referral links: when an AI platform provides a clickable link and the user visits your own site, the session appears in GA4 with the AI platform as referrer. ChatGPT referrals show as chat.openai.com, Perplexity as perplexity.ai, and Gemini as gemini.google.com
• UTM-tagged links: adding UTM parameters to key pages isolates AI driven traffic even when referral source data is inconsistent across enterprise platforms. Tagging links with an AI search source and referral medium lets you segment AI sessions cleanly in GA4 regardless of how each platform passes referral data
• Direct traffic uplift: brands cited frequently in AI answers see corresponding increases in direct traffic as users navigate to the site after encountering the brand in an AI conversation. Monitoring direct traffic trends alongside referral data captures the full commercial impact of AI citations, including zero-click interactions that never produce a referral session

Regional ROI adds a further dimension to AI referral analysis. Comparing AI referral conversion rates by geography reveals which markets produce the highest return on geo investment. Effective geographic measurement also helps optimise sales territory coverage and staffing by revealing where AI driven demand is growing fastest.

Layer three: brand authority signals in generative search

The third layer sits outside owned analytics entirely. It covers the signals AI systems use to form their understanding of a brand's authority, accuracy, and reputation. These signals don't produce direct traffic data but determine citation rates at every other layer. Comparing your AI visibility against competitors reveals which specific authority signals they've built that you haven't.

Brand authority in generative engines builds from five categories of external signals:

• Third-party list appearances: industry rankings, expert roundups, and "best of" compilations across publications AI systems treat as authoritative
• Earned media coverage: mentions in trade press, major news outlets, and sector-specific publications with high domain authority
• Review platform presence: review volume, recency, and sentiment on G2, Capterra, and Trustpilot that AI systems actively draw from when forming brand assessments
• Community mentions: brand references in Reddit threads and LinkedIn posts that AI systems index as social proof signals
• Accuracy of brand information: whether the information AI systems surface about your brand is current, correct, and consistent with your actual positioning

Geographic Information Systems and regional data sources also feed into the authority signals AI systems draw from for localised queries. Brands with strong regional press coverage, local review presence, and geographically relevant case studies consistently outperform generic competitors in AI answers for location-specific informational queries.

AI generated sentiment: measuring how AI describes your brand

Sentiment analysis reveals whether AI systems describe a brand in positive context or with qualifying language that reduces buyer confidence. Understanding AI perception of your brand helps adjust content strategies before inaccurate or negative descriptions reach your target audience at scale.

Sentiment is scored across three dimensions in dedicated GEO tools:

• Descriptive accuracy: whether AI systems describe your product capabilities, use cases, and positioning correctly
• Competitive framing: whether AI responses position your brand favourably relative to named competitors when users ask for recommendations
• Tone and trust signals: whether AI generated descriptions include language such as "reportedly" or "some users say" that introduces doubt

Correcting negative AI sentiment requires sustained publishing of accurate, detailed content across owned and earned channels. AI sentiment shifts gradually as the weight of evidence across multiple sources changes, so paid media campaigns running alongside strong earned media coverage compound GEO authority signals more effectively than paid-only strategies.

GEO measurement tools: visibility metrics in practice

Traditional analytics tools including GA4 and Google Search Console remain essential for tracking the organic traffic and technical health that feeds GEO citation rates. The most effective measurement stacks combine one dedicated AI visibility platform with GA4 for referral traffic and a brand monitoring tool for earned media coverage.

What GEO metrics matter for business goals

The metrics that matter most connect to commercial outcomes, not just visibility dashboards. The GEO metrics that earn credibility with leadership teams are the ones that connect to revenue, pipeline, and brand preference.

Regional ROI measures the cost required to acquire a customer versus revenue generated in a specific location. Applying that framework to AI-referred sessions reveals which geographic markets deliver the highest return on geo investment. Brands that track this dimension allocate paid media and earned media budgets with significantly more precision than brands reporting on AI visibility at aggregate level only.

Today's digital landscape: what GEO measurement reveals

Traditional SEO measurement tells you how visible you are to users who search in a traditional search engine and click a result. GEO measurement tells you how visible you are to users who ask AI systems for recommendations, and how those systems describe your brand in response.

An industry leader in traditional search can be entirely invisible in AI generated answers if their content doesn't match the passage-level extractability and topical depth that AI systems reward. Natural language processing is the mechanism behind this shift: AI systems interpret queries, retrieve relevant passages, and generate answers grounded in the sources they find most credible. User behaviour in AI search is fundamentally different from keyword-driven search because users provide more context, ask follow-up questions, and engage in multi-turn conversations.

GEO measurement makes this new layer of discovery visible, actionable, and connected to business goals. Data-driven insights from consistent prompt testing, citation source analysis, and referral traffic tracking together produce the picture that organic dashboards will never surface on their own.

Building a GEO measurement cadence for measuring success

30% of brands remain visible across back-to-back AI responses for the same prompt, and 40 to 60% of cited domains change monthly across major AI platforms. Continuous monitoring is the only reliable way to detect citation gains and losses before they translate into competitive position changes.

A practical GEO measurement cadence looks like this:

• Weekly: run the core prompt set across primary AI platforms. Log citation rates, share of voice, and sentiment changes. A steady increase in citation rates week on week confirms GEO efforts are working
• Monthly: review AI referral traffic in GA4. Compare session volume, engagement, and conversion rates against the prior month and prior year. Cross-reference against GEO changes made in the period to build cause-and-effect understanding
• Quarterly: run a full competitive GEO audit. Map your citation footprint against named competitors. Identify authority gaps and content gaps explaining share of voice differences, and update your GEO strategy accordingly

Investing in GEO measurement infrastructure now builds the data history that makes future optimisation decisions faster. Brands that start measuring AI visibility today will have twelve months of baseline data before most of their competitors begin tracking it.

If you don't know where your brand stands in AI search, here's where to start

The most common finding in our FirstMotion audits is that a brand's AI citation footprint looks completely different from its Google rankings. Strong organic visibility and near-zero AI citations sitting side by side, on the same queries, for the same buyers. Our ContextualJourney™ platform maps exactly where that gap exists and why, so the first conversation we have is grounded in your actual data rather than assumptions.

Talk to the FirstMotion team to get started. We'll run your brand through ContextualJourney™, show you where you're being cited and where you're not, and give you a clear picture of what's driving the difference before we recommend anything.

Frequently Asked Questions

What is GEO performance measurement?

GEO performance measurement tracks how often a brand appears in AI generated responses, how it's described, what traffic those citations produce, and how visibility compares to competitors across generative engines. It requires different key metrics and tools from traditional SEO because AI citations don't appear in Google Search Console and don't always produce direct referral traffic.

How do you track AI referral traffic in Google Analytics 4?

AI referral traffic appears in GA4 under referral sources, with each AI platform showing as its own domain. Adding UTM parameters to key pages isolates AI driven traffic more precisely. Direct traffic trends should also be monitored alongside referral data, as many AI-influenced visits arrive as direct sessions after a user encounters your brand in an AI conversation.

What tools measure GEO performance?

Dedicated GEO measurement tools include Profound for enterprise citation tracking and sentiment analysis, Peec AI for multi-platform brand mention tracking, Otterly AI for GEO audits, Ahrefs Brand Radar for teams already using Ahrefs, and SE Ranking's AI Toolkit for teams managing traditional SEO and AI visibility together. Each platform tracks citation frequency, share of voice, and competitive benchmarking across ChatGPT, Perplexity, Google AI Overviews, and Gemini.

Why do traditional SEO metrics miss GEO performance?

Unlike traditional SEO metrics, GEO performance includes zero-click citations where a brand earns influence in an AI generated response without the user visiting the site. AI generated content about a brand doesn't appear in any standard SEO reporting tool, making citation frequency, share of voice, and AI sentiment scores entirely invisible to traditional analytics.

How does FirstMotion measure GEO performance for clients?

We build three-layer GEO measurement stacks covering AI visibility tracking, AI referral traffic attribution, and brand authority signal monitoring. We run consistent prompt sets across all major AI platforms, benchmark citation rates against named competitors, and connect AI visibility data to pipeline metrics. Our GEO agency work starts with measurement because you can't optimise what you can't see.

How often should GEO performance be measured?

Weekly prompt testing, monthly AI referral traffic review in GA4, and quarterly competitive GEO audits represent the minimum viable cadence for most B2B software brands. Citation rates change rapidly: 40 to 60% of cited domains change monthly across major AI platforms, meaning monthly-only measurement misses the gains and losses that drive GEO strategy decisions.

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How Google AI Mode and AI Overviews Select Sources

Google's AI search experiences, AI Mode and AI Overviews, select sources using fundamentally different criteria from traditional organic rankings. Understanding each one is the foundation of any AI visibility strategy in 2026.

Key takeaways:

• Only 14% of URLs cited in AI Mode also rank in the top 10 of traditional Google search results
• AI Overviews now appear in approximately 48% of all tracked queries, up from 30% a year ago
• 62% of AI Overview citations come from pages outside the organic top 10 as of early 2026
• AI Mode uses a query fan-out technique that selects sources at a granular level traditional SEO never needed to address

Most of the B2B software brands we work with at FirstMotion assume their Google rankings carry over to AI Mode and AI Overviews. The data says otherwise. The gap between organic and AI is now large enough to demand a separate strategy, and this guide explains exactly what drives citation selection on each platform.

What is Google AI Mode and how does it work in Google Search?

Google AI Mode is a dedicated tab within Google Search powered by Gemini 2.5. It generates synthesised, conversational responses to complex queries using more advanced reasoning than traditional search, interprets queries through text, images, or voice, and retrieves real-time information from the live web rather than a static index.

AI Mode reduces the need to reformulate searches and visit multiple websites, because it handles multi-part questions and performs multiple background searches simultaneously. Google confirmed in its August 2025 announcement that AI Mode now reaches 180 countries and territories in English, making it the most powerful AI search experience Google has ever deployed globally.

AI Mode also uses multimodal capabilities that go beyond text. Through Search Live, it lets users point their camera at real-world objects and ask questions about what they see, using computer vision to analyse environments in real time. Google's Agentic Vision within Gemini 3 Flash takes this further, using computer vision to improve image recognition accuracy, automating visual analysis tasks that previously required manual processes and delivering superior accuracy compared to manual inspection methods.

What are Google AI Overviews and how do AI Overview citations work?

Google AI Overviews is a separate product from AI Mode. It appears directly on the main Google search results page as an AI generated summary above traditional organic listings, without any tab switch required. AI Overviews launched officially on May 14, 2024, focusing specifically on increasing visibility in AI generated search summaries for informational queries.

A critical distinction: AI Overviews cite passages, not entire pages. The citation unit is a specific extractable answer within a page, not the overall authority of the domain. BrightEdge's year-over-year analysis confirms AI Overviews now trigger on approximately 48% of tracked queries, up from 30% a year ago.

For local businesses, this prevalence matters significantly. Queries about local services, healthcare providers, and professional services increasingly surface AI Overviews rather than traditional organic listings. Brands that earn an AI Overview citation see a 35% increase in organic clicks compared to competitors that don't appear in the overview, according to Seer Interactive's analysis of queries across 42 organisations.

How AI Mode works: query fan-out and AI generated responses

AI Mode's source selection starts before it retrieves a single page. Ahrefs' AI Mode guide confirms that AI Mode uses a query fan-out technique that takes the original query, divides it into multiple sub-queries, and sends each to Google's index independently. A single question in the AI Mode search bar can trigger dozens of parallel searches across different facets of the same topic.

This architecture produces a very different AI response from what traditional search generates. A page ranking position one for the primary query can lose citation slots to candidate pages that answer sub-queries well, even when those exact URLs don't rank for the original question. AI Mode queries tend to be significantly longer and more conversational than traditional search queries, which means AI Mode selects content at a much more granular and intent-specific level.

AI Mode also provides a more detailed analysis of complex topics than any AI generated answer or featured snippet. When users want to dive deeper, they ask follow-up questions within the same session, and AI Mode performs additional query fan-out rounds to retrieve more specific context. This extended session behaviour means multiple brands can earn citations across a single conversation, creating citation opportunities that don't exist in any other Google search format.

How AI Mode selects sources: what the data shows

SE Ranking's August 2025 study analysed AI Mode responses across a large keyword set and produced three findings that fundamentally change how AI visibility needs to be measured.

The 14% URL overlap is the most strategically significant figure. It confirms that AI Mode rarely references the pages Google ranks highest in traditional search results, and operates on a fundamentally different approach to content relevance. For brands tracking AI visibility through organic rankings alone, these figures confirm that organic search results are almost entirely missing what AI Mode actually does with their content. User feedback signals, including follow-up question patterns and session dwell time, also influence which specific pages get selected over time.

Google's AI Overviews: AI Overview visibility data and citation patterns

AI Overviews and AI Mode share the same Google infrastructure but select sources differently. AI Overviews focus on informational queries, cite passages rather than entire pages, and correlate more strongly with organic rankings than AI Mode, though that correlation has weakened significantly in 2026.

Digital Applied's post-I/O 2026 analysis shows that in July 2025, 76% of AI Overview citations came from pages ranking in the organic top 10. By March 2026, that figure had fallen to 38%, a 50% relative decline in eight months. Ahrefs' March 2026 analysis confirms that 62% of AI Overview citations now come from pages outside the top 10 organic results, as top-10 citation rates fell from 76% to 38% in eight months.

AI Overviews also push traditional organic listings further down the page. The average overview now exceeds 1,200 pixels in height, displacing organic search results, blue links, and featured snippets significantly below the fold on AI Overview-triggered queries. Ahrefs' updated December 2025 study found that the presence of an AI Overview now correlates with a 58% lower average clickthrough rate for the top-ranking page, updated from their initial 34.5% finding in April 2025.

Generative AI in Google Search: AI Mode vs AI Overviews vs traditional search

The clearest way to understand how generative AI has changed source selection is to compare all three surfaces directly. Each operates on different signals, rewards different content properties, and delivers a different user experience.

The most important distinction is the citation unit. AI Overviews cite passages; AI Mode selects at the sub-query level. Both systems evaluate specific content within a page, not the overall authority of the page itself. That's why candidate pages outside the top 10 regularly earn AI citations when they contain the most directly answerable passage for a specific sub-topic.

How AI Overview visibility differs from AI Mode visibility

AI Mode visibility and AI Overview visibility are distinct metrics that require separate tracking strategies. Ahrefs' analysis of 540,000 query pairs found that AI Mode and AI Overviews cite the same URLs only 13.7% of the time. A brand can earn strong AI Overview citations without appearing in AI Mode responses at all, and vice versa.

AI Overview visibility aligns more closely with traditional organic rankings, topical authority, and content quality. Pages that rank well for informational queries, carry schema markup including Article schema and HowTo schema, and cover topics with genuine contextual understanding earn AI Overview citations at higher rates. AIO focuses specifically on synthesising helpful links and cited pages for the user's initial query, meaning content that directly and clearly answers common questions performs best.

AI Mode visibility requires a different approach because of the query fan-out architecture. AI Mode visibility depends on covering the full range of sub-topics a complex query generates, not just the primary keyword. A brand that answers one aspect of a query well but leaves adjacent sub-queries uncovered will see inconsistent AI Mode citation patterns, regardless of domain authority or traditional search results performance.

What drives AI Overview citations and AI generated answers across both platforms

Both AI Mode and AI Overviews reward the same underlying content properties, though they weight them differently. These signals consistently improve citation likelihood across both platforms:

• Direct answers first: content that answers the specific query in the opening paragraph gets extracted more reliably. An AI generated answer draws from the most immediately relevant passage, not the most comprehensive page
• Topical depth: covering all the sub-topics a query fan-out generates means more sub-queries find a citable passage within the same domain, keeping multiple brands from occupying citation slots your content should fill
• Schema markup: Article schema, HowTo schema, and FAQ schema all improve passage-level extractability for specific pages. Google Search Central confirms JSON-LD is the recommended implementation
• Content freshness: AI systems favour recently updated content with current statistics and contemporary references on cited pages
• Entity clarity: naming the brand, topic, and use case explicitly in titles, headings, and opening paragraphs helps Google's AI systems anchor AI citations accurately
• Technical SEO foundations: pages that load quickly and render correctly for AI crawlers pass eligibility requirements before any relevance evaluation begins
• Topical authority: domains that cover a topic area comprehensively build the citation trust AI Mode's query fan-out needs to return to the same domain repeatedly across multiple searches

Content quality has become the dividing line between brands that appear consistently in AI generated answers and brands that don't. AI systems automate relevance evaluation at scale, delivering superior accuracy compared to any manual content audit process.

How AI Mode personalisation affects source selection and where brand appears

AI Mode's personalisation layer adds a dimension to source selection with no direct equivalent in traditional SEO or AI Overview optimisation. When users opt in, AI Mode references past searches, location data, and activity from the Google app and Google Maps to generate an AI powered response tailored to their personal context.

The same query from two different users can produce entirely different cited sources and different AI response content. Content that speaks to specific use cases, buyer stages, and geographic contexts, including local businesses and region-specific solutions, earns more citations in personalised responses for those segments. A brand that only publishes generic category-level content won't appear in personalised AI Mode responses, even when it ranks well in traditional organic search results.

For B2B brands, topical depth across the full buyer journey is essential. AI Mode needs enough relevant content across an entire topic area to construct personalised responses. Brands that publish at multiple depth levels, from overview articles to detailed technical guides, give AI Mode more citation options across different user contexts.

How to measure AI generated visibility and AI Mode citations

Measuring AI visibility requires different tools from traditional rank tracking. Organic rankings are a necessary but insufficient proxy for AI citation performance, and the gap between the two continues to widen across all search engines incorporating generative AI.

Platforms that now track AI visibility directly include:

• SE Ranking AI Search Toolkit: tracks AI Overview citations and AI Mode citations at keyword level, with volatility monitoring across multiple searches of the same query
• Ahrefs Brand Radar: indexes AI Mode responses and lets brands check citation frequency for exact URLs across a growing query dataset
• BrightEdge Generative Parser: monitors AI Overview presence and overview citations with year-over-year trends across industry verticals
• Semrush AI Toolkit: tracks AI Overview visibility alongside traditional organic results for comparison across SEO platforms

FirstMotion's AI search audit starts by mapping a brand's citation footprint across AI Mode and AI Overviews, comparing it against competitor citation rates, and identifying the specific content and technical gaps that explain the difference. Continuous monitoring of AI citation rates is the only reliable signal of AI search performance because organic visibility no longer predicts it.

Featured snippets, blue links, and what AI search replaces

AI Mode and AI Overviews don't just complement traditional search. For informational queries, they're actively replacing featured snippets and blue links as the primary way users receive answers. Understanding this displacement helps brands prioritise where to focus their SEO strategy and content investment.

Featured snippets were the first step in Google's transition from returning links to returning answers directly. AI Overviews took that further by synthesising answers from multiple sources. AI Mode goes further still, replacing the entire traditional search results experience with a conversational AI response that handles the full research session without requiring multiple clicks to individual websites.

The brands earning consistent AI citations treat this as a content architecture problem, not a keyword problem. Topical depth, structured data coverage, and passage-level clarity determine AI citation outcomes. The AI search revolution in B2B SaaS has already made these signals the primary competitive differentiator in organic visibility for informational queries.

If your brand isn't appearing in AI Mode or AI Overviews, here's where to start

Most of the brands we audit at FirstMotion aren't invisible in AI search because their content is low quality. They're invisible because their content strategy was built for a different citation system. A targeted audit of citation gaps, schema markup coverage, and topical depth usually reveals fixable issues within the first session.

If you want to understand exactly why your brand isn't being cited and what to prioritise first, talk to the FirstMotion team. We'll map your AI citation footprint and show you the fastest path to AI search visibility.

Frequently Asked Questions

What is the difference between AI Mode and AI Overviews?

AI Mode is a dedicated tab within Google Search that generates conversational, multi-part answers to complex queries using Gemini, with follow-up question capability and deep personalisation. AI Overviews appears on the main Google search results page as an AI generated answer above organic results, focusing on informational queries. Both cite sources but use different selection criteria and share only 13.7% URL overlap.

How does AI Mode select which sources to cite?

AI Mode uses a query fan-out technique that divides the original query into multiple sub-queries and retrieves sources for each independently. Only 14% of cited URLs overlap with the top 10 organic search results, confirming AI Mode uses fundamentally different selection criteria from traditional search rankings. Citation results are also highly volatile, with only 9.2% URL consistency across three repeated tests of the same query.

How many links does a typical AI Mode response contain?

SE Ranking's August 2025 research found that the average AI Mode answer contains 12.6 links. AI Overviews link to an average of 13.3 sources. Both figures are significantly higher than a traditional featured snippet, which typically cites one source.

Do top-ranking pages get cited in AI Overviews?

They're more likely to be cited, but it's no longer the norm. In July 2025, 76% of AI Overview citations came from pages ranking in the organic top 10. By March 2026, that figure had fallen to 38%, meaning 62% of AI Overview citations now come from pages outside the top 10. Ranking is still a positive signal but it no longer determines citation outcomes reliably.

How does FirstMotion measure and improve AI visibility for clients?

We audit AI citation footprints across AI Mode and AI Overviews, map citation gaps against competitor performance, and identify the specific content and technical issues causing invisibility. We then build targeted GEO programmes addressing topical depth, schema markup coverage, entity clarity, and content freshness across all key pages. Our GEO work explains the full approach.

Does AI Mode personalise results for individual users?

Yes, when users opt in. AI Mode references past search history, location data, and activity from the Google app and Google Maps to personalise responses. The same query produces different cited sources for different users based on their personal context, which is why content that speaks to specific use cases and buyer stages earns more AI Mode citations than generic overview content.

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Before FirstMotion, I built and exited two platforms, Obby and Baluu, and earned a Forbes 30 Under 30. Those years in founder circles gave me a close-up view of how badly search and AI discovery can be handled, even by companies with genuinely strong products.

When AI started reshaping how B2B buyers build shortlists, I launched FirstMotion with Alex Price, an exited agency founder and investor. We kept seeing the same problem: strong B2B software brands being underserved by agencies that hadn't adapted. So we built ContextualJourney™, combining audience intelligence, buyer journey mapping, and prompt mining into a single platform.

What follows covers 10 agencies in detail, the criteria we used to evaluate them, and a stage-by-stage framework to help you match your brief to the right type of partner.

Top GEO agencies in the UK: quick overview

What AI search optimisation means in 2026

The terminology is genuinely confusing. GEO, AEO, AI SEO, LLMO: agencies use these interchangeably, and some use all four simultaneously. Here's a quick breakdown:

Large language models select which sources to cite based on entity clarity, content structure, and third-party authority signals. Unlike ranking web pages in traditional search, generative AI platforms assess how well a source directly answers the query.

What separates a real GEO programme from rebadged SEO

A genuine AI search programme measures citation as a primary metric, runs real prompts through ChatGPT, Perplexity, and Google Gemini, and connects results to pipeline outcomes. GEO strategy can't be measured by organic traffic or search performance in traditional search engines alone.

The commercial case

• AI referral traffic to retail sites grew 693% year on year during the 2025 holiday season (Adobe Digital Insights, January 2026)
• AI referral sessions grew 700% across the full year 2025, the fastest-growing traffic source on the web (Previsible, 400+ tracked websites)
• AI referral traffic grew 340% year on year as of January 2026, based on Conductor's analysis of 21.9 million queries

Unlike traditional SEO, GEO focuses on how pages are retrieved and synthesised by generative engines, not just indexed and ranked. Our GEO vs SEO guide covers the full distinction.

How we selected the best generative engine optimisation agencies

No agency paid to appear. Every entry was assessed against three criteria. The right GEO agency depends on fit: your sector, your stage, and whether AI search visibility needs to stand alone or sit inside a broader programme.

Named methodology and prompt-level tracking

Structured data, entity optimisation, and content architecture for AI extraction are the baseline. Prompt-level tracking and citation reporting across ChatGPT, Perplexity, and AI Mode are the differentiators. Agencies without a named methodology are rebranding existing SEO services.

Citation outcomes, not traffic

Can they show citation results for clients, not just traffic improvements? Digital PR and GEO need to work as one: agencies that treat them as separate service lines consistently deliver weaker results in both.

B2B sector understanding

Consideration-stage queries like "best [category] software for [use case]" are where AI search is reshaping B2B pipeline. Agencies without B2B experience miss the nuances of multi-stakeholder buying cycles.

The 10 best UK agencies for AI search and GEO in 2026

1. FirstMotion

Best for: B2B SaaS and software companies at Series A-B stage with long sales cycles, complex buying committees, and pipeline goals.

FirstMotion's ContextualJourney™ platform was built around a gap most software companies don't know they have: their buyers are building shortlists through ChatGPT and Perplexity before ever visiting a website, and those shortlists often don't include them.

GEO for B2B software is not a category where a standard agency model holds up. Buying cycles are long, buying committees are senior, and the way a CISO or Head of RevOps uses AI tools to evaluate vendors is specific to the category, the moment, and the competitive set. The same senior people who set the strategy are in each FirstMotion engagement week to week, which means understanding of the client's buyers, category, and competitive position builds continuously rather than being interpreted by layers of the account team.

ContextualJourney™ is how FirstMotion structures that work. The team maps where clients appear across AI search platforms, using prompt data, ICPs and sales transcripts to build a precise picture of how buyers research and shortlist. Engagements are built around that: entity and schema audits, AI search monitoring, structured content development, and digital PR for citation authority, sequenced around the actual buying cycle. Reporting ties to pipeline from day one, with one question driving everything: is AI visibility generating opportunities?

In one B2B SaaS engagement, FirstMotion delivered a 200% improvement in AI visibility and shifted 40% of inbound enquiries to organic and AI search combined.

FirstMotion also runs digital due diligence for investors and PE firms, assessing how visible portfolio targets are across generative platforms before acquisition or growth investment. No other agency on this list offers that.

FirstMotion works with a focused number of clients at any one time. It's worth confirming availability before investing time in the process.

2. Rank4AI

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Best for: Businesses that want AI search visibility as a standalone programme, separate from traditional SEO or paid media.

One thing and one thing only is what Rank4AI does: dedicated AI search visibility. No traditional SEO retainer, no paid media, nothing else. Every engagement starts with an audit across six AI platforms, using a 17-section assessment that covers entity signals, content architecture, ecosystem presence, and cross-platform consistency. The methodology draws on data from over 1,400 UK business audits, which gives it a practical evidence base rather than theoretical frameworks.

Three service paths are available: Ecosystem (building AI presence outside your website, from £800/month), Full Agency (includes direct site work, from £1,500/month), and Advisory for teams that want to future proof their AI search strategy without full outsourcing. Founded by Adam Parker, the approach is systematic and the pricing is unusually transparent for a specialist generative engine optimisation agency.

Rank4AI's exclusive AI search focus is its clearest strength and its natural constraint. If your brief includes integrated SEO, content production, or digital PR, you'll need additional partners.

3. Found

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Best for: Larger brands that need AI search visibility tracked and reported as part of a broader performance marketing programme.

Everysearch™ is Found's trademarked framework for tracking brand visibility across generative AI platforms, social search, and traditional search engines in one place. The engine behind it is Luminr, their proprietary AI-powered platform, which maps how a brand appears wherever buyers are searching. As a full-service digital marketing agency, Found's SEO, digital PR, data, and paid media teams operate as a connected system rather than separate service lines, which is where they perform best: when AI visibility needs to sit inside a broader performance marketing agency brief. Clients include Puma, Toolstation, Fender, and House of Marley.

GEO work covers entity optimisation, schema and structured data implementation, metadata strategy, and content built for AI extraction. The infrastructure Found has built is genuinely substantial, and it's better suited to brands with the scale and budget to use it fully.

Found's model is built for scale. Brands with more focused briefs or tighter budgets will get more specialist attention from smaller partners.

4. Impression

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Best for: B2B and SaaS brands that want GEO integrated with digital PR, technical SEO, and genuine senior engagement across the team.

B Corp certified and independently owned since its founding in 2012 by Aaron Dicks and Tom Craig, Impression operates across Nottingham and London with dedicated sector teams for B2B, SaaS, and fintech. That vertical depth shapes how GEO gets done: knowing how buyers in those sectors research and shortlist is what determines which prompts to target and which content formats earn AI citations. Their 2024 Digital Agency of the Year win at the Global Agency Awards and a 4.5-day working week both point to an agency that's thought carefully about how it operates.

GEO services are built around earning citations through authority: digital PR and brand mention outreach sit alongside entity optimisation, schema implementation, and authoritative content structured for AI extraction. The combination of strong technical SEO and earned media capability gives them a genuinely joined-up approach to the two things AI systems assess: content quality and source credibility.

Impression is multi-channel by design. If you need a GEO-only brief or a boutique engagement model, this isn't the natural fit.

5. Passion Digital

Best for: Brands wanting GEO alongside paid media, content, and cross-channel performance, particularly B2B and professional services.

Four consecutive years as a Google Premier Partner (2023 to 2026) puts Passion Digital in the top 3% of Google's agency partners globally. The 2025 acquisition by Pixis.ai, a US AI technology firm, accelerated their AI capability: they now operate as part of Stellar, an AI-native global agency network, with access to AI forecasting tools and real-time optimisation infrastructure most independent agencies can't replicate. Named clients include Nutanix, OneTrust, Octopus Investments, Knight Frank, and Moore Kingston Smith.

The GEO offering covers entity optimisation, AI Overview optimisation, LLM performance tracking via their proprietary Deep Research methodology, semantic enhancement, and cross-platform AI search monitoring. Separating those workstreams rather than bundling them makes reporting more honest and makes it easier to see what's moving across AI search platforms and traditional search.

Passion Digital's broad service range works well for brands that want everything handled in one place. For focused GEO specialist work, you may find more depth elsewhere.

6. Blue Array

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Best for: Established brands and scale-ups that want the depth of a specialist organic search consultancy with a growing GEO capability built on top.

Simon Schnieders built Blue Array in 2015 after leading SEO at Zoopla, MailOnline, and Yell. What he created is deliberately different from a standard SEO agency: the Consulgency® model (trademarked) blends senior consultancy strategy with agency-scale execution. Clients include RAC, Simply Business, Funding Circle, and GoCardless. Schnieders runs the LondonSEO Meetup and authored the In-House SEO book series, which Amazon lists as a bestseller. The agency is B Corp certified, has strong technical SEO expertise, and operates from Reading and London.

Generative engine optimisation services cover AI sentiment analysis, citation gap analysis, and structured reporting across major AI models. Their technical expertise in organic search strategy underpins the GEO delivery. The Ignite package for startups gives Blue Array a broader entry point than most at this level.

Blue Array's model is strongest for brands that want senior strategic direction alongside delivery. It's less suited to a narrow AI-search-only brief.

7. Tilio

Best for: Brands that already have SEO covered and need specialist AI search measurement, tracking, and practical optimisation as a distinct programme.

A UK AI search agency based in Exeter, Tilio starts where most GEO agencies finish: measurement. Work begins by building a prompt set around your services, buyers, competitors, and decision-stage searches, then tracking how your brand appears across the major AI search platforms. Profound is the primary AI visibility data source, with Peec AI, Ahrefs, and Semrush feeding into a client dashboard that shows citation signals, competitor movement, and content recommendations in one place. Pricing is published from £499/month.

The focus is understanding whether your brand is being mentioned, cited, accurately described, and fairly compared in AI-generated responses, then improving the specific signals most likely to influence each of those factors. It's a future-proof approach for brands that want AI search visibility to compound over time.

Tilio isn't a full-service agency. Content production, link building, and technical SEO at scale are outside what they're built for.

8. Varn

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Best for: In-house SEO teams and technically minded marketers with complex websites who need GEO built on solid information architecture.

Where most GEO agencies lead with content strategy, Varn starts with structure. A Bristol-based Google Premier Partner, the approach to generative engine optimisation (GEO) treats it as an architectural problem first: auditing how AI systems interpret a site, then rebuilding the foundations so AI crawlers can accurately parse and cite the brand. That sequencing, structural work before content, is what separates GEO that compounds from GEO that stalls.

Services cover entity modelling, schema markup, content structuring for AI clarity, digital PR for citation authority, and AI visibility tracking across AI-powered search engines and generative search environments. Varn publishes a free guide to AI visibility that reflects a transparent, education-led approach to the discipline.

Varn's strength is technical depth. Brands that also need high-volume content production alongside structural work may need a broader partner.

9. Buried Agency

Best for: Scale-ups and growth-stage brands wanting an ROI-led approach that treats GEO and traditional organic search as a single integrated programme.

Among the first UK agencies to position explicitly around generative engine optimisation as a core organic search strategy rather than an add-on, Buried is a Bristol-based agency covering GEO, SEO, digital PR, and link building under one roof. The founding conviction is that AI search visibility and traditional organic performance aren't separate problems: brands need visibility across both traditional search and ai driven search engines to future-proof their discovery. GEO services focus on entity clarity, structured data, and content architecture for AI extraction, while digital PR and link building build the third-party citation footprint that AI systems use to assess credibility.

Small by design, which means direct access to senior practitioners rather than account management layers. A free GEO audit is available before committing to a retainer.

Being a smaller agency is a genuine advantage for some clients and a real constraint for others. Capacity during busy periods is worth discussing early.

10. ClickSlice

Best for: Ecommerce and retail brands wanting a well-established London agency that has built GEO, AEO, and LLM optimisation into its core search offering.

Joshua George's ClickSlice is a london based seo agency with unusually public credentials: a UK government commission to deliver SEO training to digital teams, a Udemy SEO course with over 100,000 students, and coverage in Forbes and Entrepreneur. Search marketing services are published from £2,500/month, making ClickSlice one of the top GEO agencies at this profile level to be transparent about pricing. GEO, AEO, and LLM optimisation are offered alongside traditional SEO, combining structured data implementation, AI-aligned content workflows, and entity optimisation.

ClickSlice appears consistently in ChatGPT and Perplexity responses when buyers search for GEO agencies in the UK, which is a proof point worth noting: they've applied the discipline to themselves. Their generative engine optimisation (GEO) and AEO capability is built on top of a heritage of strong technical SEO. Their strongest documented results are in ecommerce SEO.

B2B SaaS buyers with long sales cycles and complex buying committees should ask specifically for sector-relevant case studies before committing.

Four questions to ask any GEO agency before signing

More than simply process questions, these separate agencies that genuinely work in AI search from those that have added "GEO" to a service list.

1. Can you show us a brand appearing in ChatGPT or Perplexity for a query they don't rank for on Google?

This is the most direct test of genuine GEO capability. Organic rankings and AI citations use different signals. An agency with real GEO expertise should be able to show a client appearing in AI-generated answers for a prompt where their Google rankings wouldn't explain the citation. If they can't, the programme is likely traditional SEO with updated language.

2. How do you measure share of voice in AI answers, and which tools do you use?

The honest answer involves named tools. Peec.ai and Profound are the primary platforms in 2026 for tracking how often a brand appears in AI-generated responses across a defined prompt set. Vague references to "monitoring AI search" without specifying how are a red flag. AI search visibility is now a distinct reporting category from Google Search Console data and needs to be treated as such.

3. What's your approach to building citation authority through third-party sources?

Authority signals significantly impact AI citation selection. Brands appearing consistently in authoritative third-party publications, directories, and review platforms earn far more AI citations than brands optimising only their own content. Ask whether digital PR and citation building is part of the programme or sold separately, and ask to see examples of the third-party placements they've secured for clients.

4. Have you worked with companies in our specific vertical, and what did success look like?

GEO for a B2B SaaS company with a nine-month sales cycle is different from GEO for an ecommerce brand. The prompts buyers use, the buying committee structure, and the AI platforms they rely on all vary. Generic case studies showing traffic improvements without connecting to pipeline or revenue aren't sufficient evidence for a business-critical investment.

What separates GEO-native agencies from SEO shops with a new name?

There are now dozens of UK agencies offering AI search optimisation services. Most are applying traditional SEO thinking to a different surface, rebranding existing SEO services as GEO, and calling it generative engine optimisation. Three tests separate the genuine ones.

1. They report on AI citations as a primary metric

Not as a derivative of organic rankings. A genuinely GEO-native agency can tell you a brand's share of citations in ChatGPT for a specific prompt cluster, how that share has changed over 90 days, and which structural changes drove the movement. A digital marketing agency that's rebranded its existing SEO services can't.

2. They understand digital PR differently

In traditional SEO, digital PR builds backlinks that influence ranking web pages in Google. In generative search, it builds brand mentions in authoritative content that AI systems retrieve from and are trained on. The mechanism is different. GEO agencies that haven't made that distinction in their thinking haven't made it in their delivery either.

3. They can produce an AI visibility report

Not a screenshot of a ChatGPT response. A structured document showing which prompts were tested, which AI search platforms were checked, where the brand appeared and where it didn't, and what changed between reporting periods. That's the clearest evidence a GEO agency is running a genuine AI search programme across both AI-powered platforms and traditional search.

How to match your growth stage to the right agency

Company stage is the most reliable guide to which type of GEO agency will deliver best. Generative engine optimisation services vary significantly by scope, from foundational audit work through to full programmes covering content strategy, digital PR, and technical infrastructure.

Our lane is Series A to B, B2B SaaS and software, UK and European markets. If your brief falls here and pipeline depends on AI-mediated research, that's the context the ContextualJourney™ platform was built for.

For benchmarks on what good AI search visibility looks like at each stage, our AI search benchmarks for B2B SaaS sets out what to measure and what to aim for.

Ready to build your AI search strategy?

If your B2B software brand isn't showing up when buyers run shortlisting prompts in ChatGPT or Perplexity, you're losing pipeline at the earliest stage of the ai driven search research cycle, before a competitor's website has even been visited.

Every FirstMotion engagement starts with a ContextualJourney™ audit: mapping the prompts your buyers actually use across AI search engines and AI-driven search, identifying where you appear and where you don't, and building a prioritised organic search strategy to close the gap. Measurable from day one and tied to pipeline from the outset.

Request a GEO audit or strategy workshop to see exactly where your brand stands in AI search and what it'll take to move.

About the author

Tom Batting

Founder, FirstMotion

Tom Batting is the founder of FirstMotion, an AI Search consultancy helping B2B brands win visibility as discovery shifts from Google to AI. A Forbes 30 Under 30 entrepreneur and multi-exited founder, Tom specialises in GEO, AEO, and AI-driven organic growth for disruptive brands.

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