{"id":208758,"date":"2026-03-03T08:11:41","date_gmt":"2026-03-03T08:11:41","guid":{"rendered":"https:\/\/www.similarweb.com\/blog\/?p=208758"},"modified":"2026-04-15T14:35:53","modified_gmt":"2026-04-15T14:35:53","slug":"geo-audit","status":"publish","type":"post","link":"https:\/\/www.similarweb.com\/blog\/marketing\/geo\/geo-audit\/","title":{"rendered":"How to Conduct a GEO Audit: 9 Areas Every Brand Should Review"},"content":{"rendered":"

Over the past year, we\u2019ve seen the way people find information online change faster than most brands realize. Similarweb\u2019s data shows traffic to AI chatbots and tools<\/a> rises steadily, and it\u2019s about to surpass 10 billion monthly visits:<\/p>\n

\"Traffic<\/p>\n

Millions of users are turning to AI-powered tools like ChatGPT, Perplexity, Google AI Mode, and Gemini, not just to search but to get direct answers. Those responses don\u2019t come with ten blue links. They arrive as confident summaries that mention some brands, cite some sources, and leave everyone else out.
\nThe scale of this shift is becoming clear. Similarweb\u2019s 2026 Generative AI Brand Visibility Index<\/a> shows that while visits to AI platforms are growing, referrals from them are not, as chatbots evolve into all-in-one experiences that keep users inside. Pew Research<\/a> found fewer than 1% of users click links in AI Overviews. In this low-click environment, brands must focus on visibility within AI answers, not outbound clicks, and a GEO audit helps measure and improve that presence.<\/p>\n

\"Growth<\/p>\n

For marketers and SEOs, this creates a new and urgent question: how does your brand appear when AI answers the questions your customers are asking? Not how does it rank, but how does it appear? What does the AI say about it? Is the framing accurate? Is it positive? Is it there at all?<\/p>\n

This is exactly the problem I believe a GEO audit needs to solve. Unlike a traditional SEO audit<\/a>, which focuses on rankings and technical performance, a GEO audit examines your brand’s presence, reputation, and influence across AI-generated search. It tells you where you stand in the discovery landscape, and, more importantly, what to do about it.<\/p>\n

This guide walks through everything a thorough GEO audit should cover: from measuring AI brand visibility and analyzing citations, to auditing your content, technical setup, and competitive position. It also explains how to prioritize what you find, so you can focus on the changes that will actually move the needle.<\/p>\n

What is a GEO audit, and why does it matter?<\/h2>\n

A GEO audit is a structured review of how a brand, website, or piece of content is represented across AI-powered search engines and chatbots. It examines whether the brand appears in AI-generated answers, how it’s described, which sources AI engines rely on, and how all of this compares with competitors.<\/p>\n

\"GEO<\/p>\n

To understand why this matters, it helps to think about what has actually changed in search behavior. For decades, search engines returned a list of results and left the decision-making to the user. The goal of SEO was to appear high enough in that list that users would click through. Visibility meant ranking.<\/p>\n

Generative AI changes this dynamic at a fundamental level. When someone asks an AI tool a question, whether it’s “what’s the best project management software for remote teams” or “which mortgage lender has the best rates”, they typically receive a single synthesized answer, not a list of options to investigate. The AI has already done the filtering. Brands that appear in that answer are recommended, brands that don’t simply don’t exist in that moment.<\/p>\n

A brand that’s invisible in AI answers loses discovery opportunities that traditional SEO metrics<\/a> won\u2019t even capture. There\u2019s no click, no impression, no ranking signal, just absence.<\/p>\n

Worse, a brand that does appear but is framed inaccurately or negatively may be doing itself more harm than good, since AI answers carry an implicit authority that shapes perception before a user ever visits a website.<\/p>\n

The purpose of a GEO audit is to surface all of this, systematically, not by guesswork, so that brands can understand their current AI footprint and take deliberate steps to improve it.<\/p>\n

GEO audit vs. AEO audit vs. SEO audit: What’s the difference?<\/h2>\n

As AI search has evolved, so has the terminology around optimizing for it. GEO, AEO, and SEO are related disciplines, but they focus on different things and require different approaches. Understanding the distinctions matters because conflating them leads to gaps in your strategy.<\/p>\n

SEO<\/strong> (Search Engine Optimization) is the most established of the three. An SEO audit examines how well a site is positioned to rank in traditional search engines, covering technical SEO factors<\/a> like crawlability, site speed, and indexing, as well as content factors like keyword targeting, on-page structure, and backlink authority. The measure of success is rankings and the organic traffic that flows from them.<\/p>\n

AEO<\/strong><\/a> (Answer Engine Optimization) emerged as a response to the rise of featured snippets<\/a>, knowledge panels<\/a>, and voice search. An AEO audit focuses on whether content is structured in a way that search engines can extract and surface as a direct answer, think structured data markup, clear question-and-answer formatting, and concise definitions. The goal is to be the source that a search engine quotes, not just a result that ranks.<\/p>\n

GEO<\/strong><\/a> (Generative Engine Optimization) goes further still. A GEO audit examines how AI models, which synthesize information rather than simply retrieving it, represent a brand in their outputs. This involves not just on-site content, but the entire ecosystem of sources that AI engines draw from: publisher articles, forums, review sites, third-party mentions, and more. Success in GEO isn’t measured by a ranking position or a snippet, it’s measured by brand visibility share, citation influence, and sentiment across AI-generated answers.<\/p>\n\n\n\n\n\n\n\n
<\/td>\nSEO Audit<\/b><\/span><\/td>\nAEO Audit<\/b><\/span><\/td>\nGEO Audit<\/b><\/span><\/td>\n<\/tr>\n
Primary focus<\/b><\/td>\nRankings & organic traffic<\/span><\/td>\nStructured answers & snippets<\/span><\/td>\nAI brand representation<\/span><\/td>\n<\/tr>\n
Success metric<\/b><\/td>\nRanking position, clicks<\/span><\/td>\nFeatured snippet capture<\/span><\/td>\nBrand visibility share, sentiment<\/span><\/td>\n<\/tr>\n
Key inputs<\/b><\/td>\nTechnical site health, backlinks, keywords<\/span><\/td>\nSchema, content structure, FAQs<\/span><\/td>\nCitations, entity consistency, AI outputs<\/span><\/td>\n<\/tr>\n
Landscape<\/b><\/td>\nSearch engine algorithms<\/span><\/td>\nSearch engine answer features<\/span><\/td>\nGenerative AI models<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

One mistake I see often is treating these as competing strategies rather than layered ones. Strong SEO provides the technical and authority foundation that AEO builds on. Strong AEO, in turn, makes content more extractable and citable, which supports GEO performance. A brand that neglects SEO will struggle to gain AI visibility because authoritative, well-structured content is essential for being cited. But a brand that only does SEO is optimizing for a landscape that is rapidly changing shape.<\/p>\n

The 9 core areas of a GEO audit<\/h2>\n

When I run a GEO audit, these are the nine areas I consistently review:<\/p>\n

1. AI brand visibility & sentiment<\/h3>\n

When I start a GEO audit, I begin with a simple but surprisingly hard-to-answer question: when AI tools respond to relevant queries in your category, does your brand appear, and if so, how?<\/p>\n

This goes beyond a quick manual test. Brands need to assess their presence systematically across the queries that matter to their audience, across multiple AI platforms, and over time. A single manual test captures a snapshot (one which could also be biased based on your interactions), but what you actually need is a pattern.<\/p>\n

There are two dimensions to audit here. The first is visibility: does the brand appear at all, across what topics, and how consistently? The second is sentiment: when the brand does appear, is it framed positively, neutrally, or negatively? AI tools don’t just mention brands, they characterize them, and that characterization influences how potential customers perceive the brand before they ever visit its website.<\/p>\n

Similarweb’s AI Brand Visibility tool<\/a> is built specifically for this kind of systematic tracking. It shows how often your brand appears in AI-generated answers across the topics you define, which topics drive the most mentions, and whether you’re being cited as a source.<\/p>\n

\"Brand<\/p>\n

Within it, the AI Sentiment Analysis tool<\/a> goes deeper: it provides a Sentiment Score on a scale of \u20131 to +1, breaks down mentions into positive, neutral, and negative categories in both percentage and absolute volume, and surfaces the exact prompts and AI responses driving each type of sentiment.<\/p>\n

\"Sentiment<\/p>\n

Data refreshes daily, so brands can track how their AI reputation shifts over time and benchmark their sentiment against competitors.<\/p>\n

Starting with a clear baseline on presence and sentiment shapes everything that comes next in the audit. If the brand is absent, the priority is increasing visibility. If it’s present but the sentiment is neutral or negative, the priority is understanding why and addressing the content and narrative gaps that are causing it.<\/p>\n

2. Citation & sourcing analysis<\/h3>\n

In traditional SEO, a major pillar of authority flows through backlinks<\/a>. In AI search, it flows through citations. The sources that AI models trust, the domains and specific URLs they pull from when constructing answers, determine which brands get recommended, which claims get validated, and which perspectives shape the narrative in a given topic area.<\/p>\n

A citation audit examines the sourcing ecosystem around your brand and category. Which domains are being cited most often<\/a> when AI answers questions relevant to your business? Which specific pages? What types of content are earning citations: proprietary research, news articles, forum discussions, and review sites? And critically, where does your own domain fall in that hierarchy?<\/p>\n

\"Top<\/p>\n

This is where I see the biggest strategic opportunities open up. If your site is rarely cited but competitors are, the audit reveals the gap and shows which types of content are earning influence, so you can create content that\u2019s more likely to be pulled. If high-authority publishers are being cited frequently, that points to digital PR as a lever. If Reddit threads or Quora discussions are influencing AI answers in your category, that suggests a community engagement angle.<\/p>\n

Similarweb’s AI Citation Analysis tool<\/a> makes this visible at scale. It maps the domains and URLs most cited by AI engines across your tracked topics, assigning each a Domain and URL influence score<\/a> so you can see not just who is being cited but how influential each source is.<\/p>\n

\"Top<\/p>\n

It specifically surfaces UGC sources like Reddit and Quora threads, which LLMs lean on heavily for authentic perspectives, alongside publisher articles and brand-owned content. Crucially, all of these link back to the prompts each source is influencing, giving you a direct line of sight from citation to conversation.<\/p>\n

3. Content authority & expertise signals<\/h3>\n

AI models don’t just look at what a page says, they assess, implicitly, whether the source behind it is credible. This is where the concept of E-E-A-T<\/a> (Experience, Expertise, Authoritativeness, Trustworthiness), originally developed in the context of Google’s quality guidelines<\/a>, becomes directly relevant to GEO.<\/p>\n

For a GEO audit, expertise signals operate at two levels. The first is on-page<\/a>: does the content have a named author? Are the author’s credentials visible and relevant? Is the content grounded in firsthand experience or genuine subject matter expertise, or does it read like generic aggregation? The second level is off-page<\/a>: does the author have an external professional footprint, publications, conference appearances, and a LinkedIn profile with a credible history? Is the brand itself mentioned, cited, or profiled by authoritative third parties?<\/p>\n

The audit should also examine whether the brand is associated with original data, research, or proprietary insight. AI models favor sources that contribute something unique to a topic, a study, a benchmark, or a distinctive point of view over content that restates what’s widely available elsewhere. In practice, I consistently see brands that invest in original research earn more citations and appear more authoritative in AI answers.<\/p>\n

The practical output of this part of the audit is a checklist of gaps: missing author credentials, content that lacks expert grounding, absence from key third-party publications, and opportunities to develop research assets that could earn wider citation.<\/p>\n

4. Structured & machine-readable content<\/h3>\n

Even high-quality content can fail to appear in AI answers if it isn’t structured in a way that’s easy for AI systems to parse, extract, and cite. This part of the audit focuses on the presentational and technical GEO factors<\/a> and qualities of content that affect how AI models can use it.<\/p>\n

Schema markup<\/a> is the obvious starting point. Structured data helps AI systems understand what a page is about, who authored it, what type of content it contains, and how it relates to other entities. An audit should check whether key page types, product pages, FAQ pages, how-to guides, and author profiles have the appropriate schema implemented correctly.<\/p>\n

Beyond schema, the audit should look at the content structure itself. AI models tend to extract concise, clearly bounded answers rather than synthesizing from long narrative passages. Content that answers a specific question directly and early, with a clear heading that frames the question and a tight, quotable response, is more extractable than content that buries the answer in dense paragraphs. The audit should assess whether pages follow this pattern, particularly for the high-intent queries identified in the brand presence analysis.<\/p>\n

Page-level clarity also matters: logical heading hierarchies<\/a>, short paragraphs, and clean formatting make content easier to process for both AI systems and human readers. This is an area where SEO best practices and GEO best practices converge, good structure serves both.<\/p>\n

5. Brand & entity consistency<\/h3>\n

AI models build up an understanding of a brand, its name, what it does, its category, and its key attributes by aggregating information from across the web. When that information is consistent, the AI develops a clear and accurate picture of the brand. When it’s inconsistent, different descriptions on different platforms, outdated information, conflicting claims, the AI either hedges or, in some cases, gets it wrong.<\/p>\n

This part of the audit examines whether the brand is described consistently across every surface that AI models are likely to draw from. That includes the brand’s own website (particularly the About page, homepage, and product descriptions), but also Wikipedia if the brand has an entry, social media profiles, directory listings like Crunchbase or G2, press coverage, and any other third-party sources that describe the brand’s core identity.<\/p>\n

The audit should flag any inconsistencies in how the brand describes its category, its value proposition, its founding story, or its key differentiators. It should also identify outdated information, old product names, superseded pricing models, and former leadership that may still be circulating and confusing AI models. Getting this right is important because no amount of content investment will consistently produce accurate AI answers if the underlying entity data is noisy.<\/p>\n

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Build the AI Foundation<\/p>\n

Clarity and consistency drive visibility<\/p>\n

\n Try Similarweb free<\/a>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n\n

6. Conversational & long-tail query coverage<\/h3>\n

One of the biggest shifts I\u2019ve noticed is how differently people query AI tools from the way they type into a search box. AI prompts tend to be longer, more conversational, and more specific, closer to a question you’d ask a knowledgeable colleague than a keyword you’d type into Google. If your content strategy was built around short-tail keywords and optimized page titles, it may be poorly aligned with the kinds of prompts that actually drive AI answers in your category.<\/p>\n

This part of the audit maps your existing content against the real questions your audience is asking AI tools, to identify where you have strong coverage and where there are gaps. The query types to focus on include: comparison queries (“what’s the difference between X and Y”), recommendation queries (“best X for Y use case”), definitional queries (“what is X”), and process queries (“how to do X”). These are the formats AI answers tend to dominate, and the formats where content gaps are most costly.<\/p>\n

Similarweb’s AI Prompt Analysis tool<\/a> is built precisely for this kind of mapping. It aggregates and normalizes real user prompts from AI platforms across the topics you track, refreshed daily, so you’re working with actual audience questions rather than assumptions. For each prompt, it shows whether your brand is mentioned in the AI response or not, and if not, which competitors are.<\/p>\n

\"Prompt<\/p>\n

A filter that lets you toggle between “brand mentioned” and “brand not mentioned” makes it easy to identify the specific prompts where you’re losing the conversation. Those prompts become a direct content roadmap: pages to create, pages to improve, and angles to pursue.<\/p>\n

7. Competitor share of AI voice<\/h3>\n

Just as share of voice<\/a> has always mattered in brand strategy, share of AI voice, how often your brand appears relative to competitors across the queries that matter in your category, is becoming a key metric for understanding competitive position<\/a> in the AI search landscape.<\/p>\n

This part of the audit benchmarks your brand’s AI visibility against competitors across a defined set of topics and prompts. When I benchmark brands, I\u2019m not just looking at whether they\u2019re visible, but where your competitors are outperforming you and why. A competitor that consistently appears in AI answers around a topic where you’re absent likely has stronger content, more citations, or better entity recognition in that area, all of which point to specific, actionable improvements.<\/p>\n

Similarweb’s AI Brand Visibility tool surfaces the top 30 brands for every topic you track, so you can see how your brand visibility share compares across the competitive set and track how that balance shifts over time.<\/p>\n

\"Brand<\/p>\n

Combined with the Citation Analysis module, which reveals which specific pages and domains are driving competitor mentions, this gives you the intelligence to make targeted moves rather than broad guesses.<\/p>\n

8. Technical accessibility for AI crawlers<\/h3>\n

All of the content and authority work in a GEO audit is undermined if AI crawlers can’t access your site in the first place. This part of the audit is the most technically straightforward, but it’s also the easiest to overlook, and I\u2019ve seen the consequences of getting it wrong be severe.<\/p>\n

The primary check is your robots.txt file<\/a>. Several major AI providers operate their own crawlers: OpenAI uses GPTBot<\/a>, Perplexity uses PerplexityBot<\/a>, Anthropic uses ClaudeBot, and Google’s AI features use Googlebot<\/a> alongside dedicated AI crawlers. If any of these are inadvertently blocked, which can happen when a site implements blanket bot-blocking rules, AI systems may be working with outdated cached information or no information at all.<\/p>\n

Beyond robots.txt, the audit should check for other access barriers: content hidden behind JavaScript that doesn’t render for crawlers, paywalls or login walls that prevent content from being indexed, and significant page load issues that might cause crawlers to time out. These largely overlap with standard technical SEO concerns, but with AI crawlers specifically in mind.<\/p>\n

9. Content freshness & accuracy in AI outputs<\/h3>\n

AI models are trained on historical data and don’t update in real time. While they are able (depending on the user\u2019s query) to search online and fetch new data, this creates a specific risk for brands: outdated content, old product names, discontinued services, former pricing, superseded claims, can persist in AI answers long after they’ve been corrected or removed from the site itself. A customer who asks an AI tool about your pricing might receive information that’s a year out of date, presented with the same confidence as current information.<\/p>\n

This part of the audit involves actively testing AI responses for factual accuracy, particularly for claims that have changed in recent months. Where inaccuracies are found, the response is typically a combination of updating on-site content clearly, ensuring redirects are in place for any URLs that have moved, and, in some cases, even reaching out to publishers or other third-party sources whose outdated coverage may be feeding the AI’s understanding.<\/p>\n

This is the area of GEO that requires the most ongoing attention. AI models are retrained and updated regularly, so a brand’s representation can shift even without changes to its own content. I wouldn\u2019t treat this as a one-time fix.<\/p>\n

How to prioritize your GEO audit findings<\/h2>\n

In my experience, a thorough GEO audit surfaces a long list of findings, and it’s unrealistic to address everything at once. Prioritization matters, and it should be driven by two factors: the potential impact on AI visibility and the effort required to implement a fix.<\/p>\n

Start with the foundations.<\/strong> Technical crawler access, entity consistency, and schema markup are relatively low-effort to fix and have a high foundational impact. If AI crawlers are blocked or the brand is described inconsistently across the web, no amount of content investment will produce reliable AI visibility. These issues should be resolved before anything else.<\/p>\n

Then close the highest-value content gaps.<\/strong> Use Prompt Analysis to identify the specific queries where your brand isn’t appearing but should be. Prioritize those with the highest intent or competitive significance, and build or improve content to address them directly. At the same time, use Citation Analysis to identify the high-influence domains in your category, publisher sites, key forums, and review platforms, and develop a plan to earn presence there through original content, digital PR, or community engagement.<\/p>\n

Layer in the longer-term plays.<\/strong> Building genuine topical authority on LLMs<\/a>, through original research, expert authorship, and third-party endorsement, takes time, but it compounds. These investments should run in parallel with the shorter-term fixes rather than waiting for everything else to be resolved.<\/p>\n

\"How<\/p>\n

Your starting position should also inform the order of priorities. If a brand is already being mentioned in AI answers but with neutral or negative sentiment, the Sentiment Analysis module can pinpoint exactly which topics and prompts are driving poor perception, and that becomes the immediate focus. If the brand is largely absent from AI answers entirely, citation gaps and content coverage take priority over sentiment work.<\/p>\n

I think it\u2019s important to be honest about the nature of GEO: it is not a one-time audit, but an ongoing practice. AI models are updated and retrained regularly, competitive dynamics shift, and new prompts and topics emerge as audience behavior evolves. The brands that build durable AI visibility are the ones that treat monitoring as continuous, tracking their brand visibility share, citation influence, and sentiment trends on an ongoing basis, and adjusting their strategy as the data changes.<\/p>\n

The time to audit is now<\/h2>\n

From what I\u2019m seeing across industries, generative AI search isn\u2019t a future trend to prepare for, it\u2019s already reshaping how audiences discover, evaluate, and choose between brands. A GEO audit is the mechanism for understanding where your brand stands in that reality and what needs to change.<\/p>\n

The good news is that the window for building an early advantage is still open. Most brands have not yet conducted a systematic GEO audit, and most categories are not yet as competitive in AI search as they are in traditional search. The brands that move now, establishing a clear baseline, closing their content and citation gaps, and building the monitoring discipline to maintain their position over time, will be significantly harder to displace as the space matures.<\/p>\n

If you\u2019re unsure where to begin, I\u2019d start with a clear picture of where you stand today: how often your brand appears in AI answers, what sentiment surrounds those mentions, which sources are shaping the narrative, and how you compare to competitors. Similarweb’s AI Brand Visibility tool, with its Prompt Analysis, Citation Analysis, and Sentiment Analysis modules, gives you that baseline and the ongoing digital intelligence to act on it.<\/p>\n

From there, the audit framework outlined in this guide provides the structure to turn that intelligence into a systematic improvement plan. The questions AI tools answer about your brand today are being shaped by decisions you make, or don’t make, right now. That’s a reason to start, not to wait.<\/p>\n

Ready to see how your brand appears in AI search? Explore Similarweb’s AI Search Intelligence<\/a> suite and start tracking your AI brand visibility today.<\/strong><\/p>\n

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Monitor Your Ai Visibility<\/p>\n

Monitor, adapt, and stay competitive<\/p>\n

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FAQs<\/h2>\n

How often should a GEO audit be conducted?<\/strong><\/p>\n

Unlike a traditional SEO audit, which many brands run annually or semi-annually, a GEO audit should be treated as a continuous process rather than a periodic event. AI models are retrained and updated on irregular schedules, which means your brand’s representation in AI answers can shift without any changes to your own content. A quarterly deep-dive audit makes sense for most brands, but the monitoring layer, tracking brand visibility, share, sentiment, and citation influence, should run continuously in the background.<\/p>\n

Does GEO apply equally to all industries, or are some sectors more affected than others?<\/strong><\/p>\n

The impact of AI search varies significantly by category. Industries where users ask research-heavy, comparison-driven questions, such as financial services, software, healthcare, travel, and consumer electronics, tend to see higher AI search penetration, as users actively ask AI tools for recommendations and guidance. Sectors with highly transactional or local purchase intent may see less disruption in the near term, though this is changing quickly. Regardless of industry, any brand whose customers ask questions before making a purchase decision has a GEO problem worth solving.<\/p>\n

Can small or lesser-known brands realistically compete with larger brands in AI search?<\/strong><\/p>\n

Yes, and in some ways, AI search creates a more level playing field than traditional search. Large brands have incumbency advantages in Google rankings built over years of domain authority accumulation. AI models, by contrast, are more responsive to content quality, citation relevance, and topical specificity, which means a smaller brand with genuinely authoritative, well-structured content on a niche topic can appear in AI answers alongside or ahead of much larger competitors. The key is targeting the specific prompts and topics where you can be the most credible voice, rather than trying to compete broadly.<\/p>\n

Read more about this topic – GEO for Small Businesses: How Small Businesses Can Win the AI Search Game<\/a><\/p>\n

What’s the relationship between social media presence and AI brand visibility?<\/strong><\/p>\n

Social media content itself is rarely cited directly by AI engines. However, social proof and community engagement on platforms like Reddit and Quora, where users discuss, compare, and recommend brands in depth, have a meaningful indirect effect, since LLMs draw heavily on these sources for authentic perspectives. A brand that is discussed positively and frequently in relevant communities is more likely to be represented favorably in AI answers. Managing your presence in these spaces, and earning genuine engagement rather than promotional mentions, is therefore a legitimate part of a GEO strategy.<\/p>\n

How do you measure ROI from GEO improvements?<\/strong><\/p>\n

This is one of the genuinely hard questions in the discipline right now, and I\u2019ll be honest – measurement is still evolving, partly because AI search doesn’t always produce a trackable click. The most practical approach is to track a combination of leading and lagging indicators: leading indicators include brand visibility share, citation influence scores, sentiment trends, and the number of high-intent prompts where the brand appears, all of which can be monitored through tools like Similarweb’s AI Brand Visibility. Lagging indicators include branded search volume growth (as AI-driven awareness filters back into traditional search), direct traffic, and conversion rates from users who arrive already familiar with the brand. As AI engines develop more robust referral tracking, measurement will improve, but brands that start tracking now will have the historical data to demonstrate impact over time.<\/p>\n

Want to learn more? We introduced a new metric to measure the ROI of AI visibility – AMBV<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"

Over the past year, we\u2019ve seen the way people find information online change faster than most brands realize. Similarweb\u2019s data shows traffic to AI chatbots and tools rises steadily, and it\u2019s about to surpass 10 billion monthly visits: Millions of users are turning to AI-powered tools like ChatGPT, Perplexity, Google AI Mode, and Gemini, not […]<\/p>\n","protected":false},"author":333,"featured_media":208751,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[8793,2803,6345],"tags":[],"class_list":["post-208758","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-geo","category-marketing","category-seo"],"acf":[],"yoast_head":"\nHow to Conduct a GEO Audit: 9 Areas To Focus On | Similarweb<\/title>\n<meta name=\"description\" content=\"Learn how to run a GEO audit across 9 key areas, from AI brand visibility and citation analysis to content, sentiment, and competitor benchmarking.\" \/>\n<meta name=\"robots\" content=\"max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.similarweb.com\/blog\/marketing\/geo\/geo-audit\/\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Shai Belinsky\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"27 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/www.similarweb.com\/blog\/marketing\/geo\/geo-audit\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/www.similarweb.com\/blog\/marketing\/geo\/geo-audit\/\"},\"author\":{\"name\":\"Shai Belinsky\",\"@id\":\"https:\/\/www.similarweb.com\/blog\/#\/schema\/person\/d9a95f472e8394bfab5cab9f08c1061c\"},\"headline\":\"How to Conduct a GEO Audit: 9 Areas Every Brand Should Review\",\"datePublished\":\"2026-03-03T08:11:41+00:00\",\"dateModified\":\"2026-04-15T14:35:53+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/www.similarweb.com\/blog\/marketing\/geo\/geo-audit\/\"},\"wordCount\":4553,\"publisher\":{\"@id\":\"https:\/\/www.similarweb.com\/blog\/#organization\"},\"image\":{\"@id\":\"https:\/\/www.similarweb.com\/blog\/marketing\/geo\/geo-audit\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/www.similarweb.com\/blog\/wp-content\/uploads\/2026\/03\/attachment-GEO-Audit-Featured.png\",\"articleSection\":[\"Generative Engine Optimization\",\"Marketing\",\"SEO\"],\"inLanguage\":\"\"},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.similarweb.com\/blog\/marketing\/geo\/geo-audit\/\",\"url\":\"https:\/\/www.similarweb.com\/blog\/marketing\/geo\/geo-audit\/\",\"name\":\"How to Conduct a GEO Audit: 9 Areas To Focus On | Similarweb\",\"isPartOf\":{\"@id\":\"https:\/\/www.similarweb.com\/blog\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\/\/www.similarweb.com\/blog\/marketing\/geo\/geo-audit\/#primaryimage\"},\"image\":{\"@id\":\"https:\/\/www.similarweb.com\/blog\/marketing\/geo\/geo-audit\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/www.similarweb.com\/blog\/wp-content\/uploads\/2026\/03\/attachment-GEO-Audit-Featured.png\",\"datePublished\":\"2026-03-03T08:11:41+00:00\",\"dateModified\":\"2026-04-15T14:35:53+00:00\",\"description\":\"Learn how to run a GEO audit across 9 key areas, from AI brand visibility and citation analysis to content, sentiment, and competitor benchmarking.\",\"breadcrumb\":{\"@id\":\"https:\/\/www.similarweb.com\/blog\/marketing\/geo\/geo-audit\/#breadcrumb\"},\"inLanguage\":\"\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/www.similarweb.com\/blog\/marketing\/geo\/geo-audit\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"\",\"@id\":\"https:\/\/www.similarweb.com\/blog\/marketing\/geo\/geo-audit\/#primaryimage\",\"url\":\"https:\/\/www.similarweb.com\/blog\/wp-content\/uploads\/2026\/03\/attachment-GEO-Audit-Featured.png\",\"contentUrl\":\"https:\/\/www.similarweb.com\/blog\/wp-content\/uploads\/2026\/03\/attachment-GEO-Audit-Featured.png\",\"width\":1536,\"height\":1024,\"caption\":\"GEO Audit - 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