Generative Engine Optimization: B2B Playbook for Getting Cited by AI

Ask ChatGPT for the best link-building agency for a SaaS company and you'll get back four or five names. You won't see ads or page two, just a short list the model decided was worth sharing.

If your brand isn't on that list, that buyer probably never hears of you.

That's the problem generative engine optimization (GEO) solves. GEO is the work of getting your brand mentioned and cited in AI-generated answers, whether that's ChatGPT, Perplexity, Gemini or Google's AI Overviews. It borrows a lot from SEO, but the goal is different. You're not trying to rank a page. You're trying to become a source the AI trusts enough to repeat.

For B2B companies, the stakes are higher than most people realize. Your buyers are already using these tools to build vendor shortlists before they ever book a demo. Most don't click through to see where the answer came from. They just take the names and start emailing.

The good news is that this isn't a black box. AI engines pull from the same places your buyers trust: industry publications, review sites, comparison articles, Reddit threads and well-structured pages that answer questions clearly. You can influence all of them.

This guide is the playbook we use with our B2B clients. It covers how AI engines pick their sources, what actually gets you cited, and how to measure progress without guessing.

Key Takeaways

• GEO is about getting cited, not ranked. The aim is for ChatGPT, Perplexity, Gemini and Google's AI Overviews to name your brand when buyers ask about your category.

• Most of it still rests on SEO. Crawlable pages, topical authority and strong backlinks all carry over. GEO adds a layer on top rather than replacing anything.

• Both your website and your reputation count. AI engines cite brand websites more than any other source, but whether they mention you at all depends heavily on how often other sites talk about you.

• Format affects whether you get quoted. Clear definitions, specific numbers and answer-first paragraphs are easier for an AI to lift and cite.

• You can measure it. Track which prompts mention you, how often, and how much AI referral traffic shows up in GA4.

What is Generative Engine Optimization (GEO)?

Generative engine optimization (GEO) is the practice of shaping your content and your brand's presence across the web so AI tools mention you, quote you or link to you in their answers.

Traditional SEO puts a page into a list of results. GEO puts your brand inside the answer itself.

The term comes from a 2023 research paper by Pranjal Aggarwal and colleagues, including researchers from Princeton. It was later presented at KDD 2024. The team tested how different content changes affected a source's visibility in AI-generated responses, and found that the right adjustments could raise visibility by up to 40%. The tactics that worked best were fairly unglamorous: citing credible sources, adding relevant statistics and including quotes from experts. Old SEO habits like keyword stuffing did little or nothing.

That finding sums up GEO well. AI engines reward content that looks trustworthy and is easy to pull facts from, not content written to game an algorithm.

Which AI engines does GEO cover?

GEO applies to any tool that generates an answer instead of listing links. For most B2B companies, these are the ones that matter:

Each engine weighs sources a little differently, which we'll get into in section 4. The fundamentals are the same everywhere, though: be easy to find, easy to understand and backed up by other sites.

A quick note on the name

"GEO" causes some confusion because SEOs have long used "geo" to mean location targeting, as in geo-targeted pages or local SEO. When people search "geo SEO" today, they could mean either one. In this guide, GEO always means generative engine optimization. If you're after local rankings, that's a separate playbook.

Why GEO Matters for B2B Brands Now

Not long ago, a B2B buyer looking for a vendor would Google a few terms, open ten tabs, read some comparison posts and fill in a couple of demo forms. Your job was to show up in those tabs.

That journey is shrinking. More buyers now start with a question typed into ChatGPT or Perplexity, such as "What are the best SOC 2 compliance tools for a 50-person startup?" They read the answer, maybe ask a follow-up or two, and come away with a shortlist. The ten tabs never get opened.

Gartner saw this coming. In early 2024, it predicted that traditional search engine volume would drop by 25% by 2026 as people moved to AI chatbots and virtual agents. Whatever the exact number, the direction is obvious to anyone watching their own analytics: impressions holding steady while clicks quietly fall.

The shortlist is being built without you

This hits B2B harder than most industries, for three reasons.

Buying committees research quietly. A B2B deal can involve a handful of people, each doing their own homework. If the CFO asks an AI tool for alternatives to your product and you're not mentioned, you've lost a vote you never knew was being cast.

Sales cycles are long, and first impressions stick. The vendors named in that first AI answer become the benchmark everyone else gets compared to. Getting added to a shortlist later is much harder than being on it from the start.

"Best X for Y" queries are exactly what AI engines do well. Category questions, comparisons and use-case questions make up most of B2B research. They're also the prompts where AI tools give confident, tidy answers with named brands.

A citation is the new page-one ranking

In classic SEO, ranking third still got you clicks. In an AI answer, there's no third result to scroll to. You're either in the answer, or you're not.

And the brands that do appear get something a blue link never gave them: a neutral-sounding recommendation. When ChatGPT names your company as a strong option for mid-market SaaS teams, the buyer hears it as advice, not advertising.

Why it pays to start now

AI engines tend to repeat what's already established across the web. Brands that build up mentions, reviews and citable content today become the default answer, and defaults are hard to dislodge. Your competitors' SEO head start took years to close. In GEO, that gap is still small, but it won't stay that way for long.

GEO vs SEO vs AEO: What's Actually Different

Every few months the industry invents a new acronym, and most of them don't deserve one. GEO is a little different because the end goal really has changed, even if much of the work hasn't.

Here's the short version:

• SEO search engine optimization gets your pages ranking in traditional search results so people click through to your site.

• AEO answer engine optimization gets your content chosen as the direct answer to a question, as in featured snippets, voice assistants and "People also ask" boxes. [Internal link: /answer-engine-optimization/]

• GEO generative engine optimization gets your brand mentioned, quoted or cited inside answers that AI tools write from multiple sources.

AEO and GEO overlap a lot. Think of AEO as the earlier version, built around one engine pulling one answer from one page. GEO reflects the newer reality: an AI model reads many sources, blends them, and decides which brands deserve a mention.

Side-by-side comparison

What carries over from SEO

Quite a lot. If your SEO is solid, you're already partway there.

AI engines that search the web in real time rely on regular search indexes. Perplexity and ChatGPT pull results from the web, and Google's AI Overviews draw from Google's own index. If your pages can't be crawled, aren't indexed or don't rank anywhere, they're unlikely to be picked as sources.

Backlinks still matter too. Links from respected sites tell search engines and AI models that people trust you. Topical authority, page speed and clean site structure all stay important.

What's new with GEO

The biggest change is that your own website is only part of the picture. An AI model forms its view of your brand from everything it can find, including review sites, comparison articles, forum threads, podcast transcripts and news coverage. A brand that's talked about positively across fifty sites will often beat one with a better website but no outside presence.

A few other things shift as well:

• Mentions count even without a link. In SEO, an unlinked brand mention does little. For an AI model, being named on a credible page is a signal in itself.

• Passages matter more than pages. AI tools pull specific sentences, stats and definitions. A page can be cited for one strong paragraph even if the rest is average.

• Consistency becomes a ranking factor. If your pricing, positioning or product description differs from site to site, AI engines either pick one at random or leave you out.

• Success is harder to see. There's no Search Console for ChatGPT yet. You have to track prompts and mentions yourself, which we'll cover in section 7.

So which one should you focus on?

All three, but not as separate projects. Think of SEO as the foundation, AEO as the habit of writing clear answers, and GEO as the bigger job of making sure the wider web says the right things about you. A B2B team that treats them as one connected program will get more out of each than a team chasing every new acronym on its own.

How AI Engines Choose Which Sources to Cite

No AI company publishes a ranking algorithm for citations, so nobody can give you a definitive formula. But by testing prompts, watching which sources come up again and again, and reading what the platforms have shared, you can build a pretty reliable picture.

Two ways an AI "knows" about you

AI models learn about brands in two different ways, and GEO needs to cover both.

1. Training data. Large language models learn from huge amounts of text gathered up to a cutoff date. If your brand was widely and consistently discussed before that cutoff, the model may "know" you even without searching. This is slow to change. What the web said about you a year ago is shaping today's answers.

2. Live retrieval. When an AI tool searches the web before answering, it runs queries, reads the top results and builds an answer from them. This is where most citations come from, and it's the part you can influence fastest. Publish a strong page today and it could be cited within weeks if it ranks for the right searches.

In practice, the two work together. Training data shapes which brands the model expects to be relevant, and retrieval decides which pages back up the answer.

What tends to get a source cited

From what we see across client campaigns and our own testing, these factors come up most often.

It ranks for the underlying search. AI tools often break a prompt into several smaller searches behind the scenes. Google calls this "query fan-out" in AI Mode. If your page ranks for those sub-queries, it gets considered. If it doesn't, it usually isn't seen at all.

The answer is easy to extract. Pages that state things plainly get quoted. A sentence like "Most B2B link building campaigns take three to six months to move rankings" is easy for a model to lift. Three paragraphs of warm-up before the point is not.

It contains specific facts. Numbers, dates, named examples and original data give a model something concrete to cite. Vague claims like "we deliver great results" give it nothing.

Other sources agree. AI models look for consensus. If ten trusted sites list you among the top tools in your category, the model treats that as settled. If only your own website says so, it treats it as marketing.

The source itself is trusted. Well-known publications, established review platforms like G2 and Clutch, popular Reddit threads and authoritative industry sites get cited far more than small, unknown blogs.

It's fresh. For anything time-sensitive, such as tools, pricing or "best of 2026" lists, engines prefer recently updated pages. A stale comparison post from 2023 quickly loses out.

How the main engines differ

The basics apply everywhere, but each engine has its own habits.

ChatGPT relies heavily on its training data for broad questions and searches the web when a question needs current information. When it does search, it tends to cite well-known sites and comparison content. Brands with a strong, long-standing web presence have an advantage here.

Perplexity searches on almost every query and always shows its sources. It cites more pages per answer than most engines and often includes smaller, niche sites if they answer the question well. That makes it one of the easiest places for a newer B2B brand to start appearing.

Google AI Overviews and AI Mode draw on Google's index, so your existing Google rankings matter a lot. Pages that already rank well, especially for long, specific queries, are the most likely to be cited.

Gemini and Microsoft Copilot follow similar patterns, using Google and Bing respectively. If you've ignored Bing until now, Copilot (and the fact that several AI tools use Bing data) is a good reason to check how you show up there.

The takeaway

AI engines don't pick sources at random, and they don't reward tricks. They pick sources that rank, that state things clearly, that include real facts, and that the rest of the web agrees with. That's good news, because you can control all of those things.

How to Increase (and Earn) AI Citations

The playbook above covers the full program. But most teams want to know where to start, and what will move the needle soonest. Here's how we'd rank the tactics by effort and impact.

Quick wins (first 30 days)

Rewrite your top pages for extraction. Take your five most important pages and add a clear, one- or two-sentence answer under every major heading. This takes a few hours per page and can change which pages get cited within weeks, especially on Perplexity and Google AI Overviews.

Add an FAQ section that mirrors real prompts. Use the exact questions from your prompt list in step 1. Answer each in two to four sentences. FAQs map very closely to how people talk to AI tools.

Fix your review profiles. Update your G2, Capterra or Clutch listings so descriptions, categories and features are accurate. Then ask a handful of happy customers for fresh reviews. Review pages are some of the most-cited sources for B2B category prompts.

Unblock AI crawlers. A five-minute robots.txt check can uncover a problem that's been costing you citations for months.

Medium-term moves (one to three months)

Get onto existing listicles. Pick the ten "best [category]" articles that AI engines cite most for your prompts. Pitch each author with something useful: a free trial, an updated screenshot, a short expert quote. Even three or four inclusions can change how often you appear in AI shortlists.

Publish comparison and alternatives pages. Create "[your brand] vs [competitor]" pages for your top three competitors and an "[competitor] alternatives" page for the biggest one. Be fair and specific. These pages are cited often because few sources cover these exact questions in depth.

Start contributing to communities. Spend a couple of hours a week answering questions on Reddit, LinkedIn or industry forums. Results take time, but these threads keep getting cited long after they're posted.

Long-term bets (three months and beyond)

Release original research. Plan one data study per quarter. It's the most reliable way to become the source AI engines quote, and it earns quality backlinks at the same time.

Build a steady flow of brand mentions. Digital PR, guest contributions and podcast appearances add up. Each one strengthens the consensus that your brand belongs in the conversation.

Develop topical authority. Cover your core topics thoroughly, with linked guides that answer the full range of buyer questions. AI engines, like search engines, trust sites that clearly know a subject inside out.

Writing Reddit posts that get cited

Reddit deserves a closer look because it shows up in so many AI answers. Threads that get cited usually share a few traits:

• They answer one specific question in detail. Long, practical replies get cited far more than one-liners.

• They include real numbers or experience. "We tried three tools over six months, and here's what happened" beats a general opinion every time.

• They're upvoted and discussed. Engagement signals that other people found the answer useful.

• They mention brands naturally. A balanced reply that compares several options, including yours, reads as genuine. A post that only praises your product reads as an ad and usually gets removed.

Always be open about where you work if you mention your own company. Subreddit moderators and readers spot undisclosed promotion quickly, and the backlash can follow your brand.

What doesn't work

Some tactics get passed around as GEO hacks. Most are a waste of time, and a few can backfire.

Stuffing pages with prompts or keywords. The original GEO research found keyword stuffing did little for visibility. AI models read for meaning, not repetition.

Hiding instructions for AI in your pages. Some sites have tried white text or hidden prompts telling AI tools to recommend them. Platforms treat this as manipulation, and it can get your pages ignored or flagged.

Mass-producing AI-written content. Hundreds of thin, similar articles won't make you an authority. They dilute your site and give engines nothing new to cite.

Fake reviews and sockpuppet accounts. Review platforms and Reddit actively remove these, and they're a fast way to damage the trust GEO depends on.

Paying for spammy listicles. A spot on a low-quality "top 10" page built purely to sell placements adds little. AI engines tend to favor established, editorial sources.

The pattern is the same as in SEO: shortcuts that try to fool the system stop working, and sometimes hurt you. What lasts is being genuinely worth citing.

GEO Tools Worth Using

You can do GEO with nothing more than a spreadsheet and some patience. Once you're tracking more than a few dozen prompts, though, a tool saves hours each month and spots changes you'd otherwise miss.

The market has grown quickly. One October 2026 roundup listed more than 20 AI visibility trackers, and new ones launch almost every month. Most fall into three groups.

Free tools to start with

Google Analytics 4. With the custom channel group from the previous section, GA4 shows how much traffic AI tools send you and how it converts. It won't show mentions without clicks, but it's the best free way to tie GEO to revenue.

Bing Webmaster Tools AI Performance report. Microsoft added this report in February 2026. It's still in public preview, but it's the first official, free data from a major AI platform about how your site gets cited. It shows how often Copilot cites your pages, which URLs get cited, and the "grounding queries" that triggered those citations. It doesn't cover ChatGPT or Gemini, show clicks, or show competitors. Even so, the grounding queries alone are useful for understanding what AI-driven searches lead to your content.

Manual prompt tracking. The spreadsheet method from the previous section. It's slow, but it costs nothing and teaches you more about how AI answers work than any dashboard will.

AI visibility inside SEO suites

If your team already pays for an SEO platform, check what's included before buying anything new.

Ahrefs Brand Radar tracks how your brand shows up in AI answers on ChatGPT, Gemini, and Perplexity, along with mentions on YouTube, TikTok, and Reddit. In January 2026, Ahrefs added custom prompt tracking, so you can monitor the specific, long-tail questions your buyers ask on top of its built-in prompt database. Its big advantage is that AI visibility sits right next to your backlink and keyword data.

Semrush AI Visibility Toolkit covers ChatGPT, Gemini, Perplexity, Google AI Overviews and Claude. It includes market share and sentiment reports, compares you with up to 50 competitors, and produces reports you can hand to clients or leadership. It's sold as a paid add-on to a Semrush subscription, priced per domain.

SE Ranking has added AI visibility tracking to its rank tracker, covering Google AI Overviews and AI Mode along with ChatGPT, Perplexity and Gemini. It suits teams that want traditional rankings and AI visibility in a single report.

Dedicated AI visibility trackers

These tools focus only on AI search, and they're usually ahead on features.

Otterly.AI is one of the easiest places to start. Plans begin at $29 a month for 15 tracked prompts and go up to 400 prompts on higher tiers. ChatGPT, Google AI Overviews, Perplexity and Copilot are included, and Claude, Gemini and AI Mode are available as add-ons.

Peec AI is built around prompt-level tracking, competitor benchmarking and share of voice. Standard plans let you pick three AI models from a list that includes ChatGPT, Google AI Mode, AI Overviews, Copilot and Gemini, with more engines available on enterprise plans. It's a good fit for teams managing several brands or markets.

Profound is aimed at large companies. It tracks up to nine answer engines, including ChatGPT, Perplexity, Gemini, Copilot, Claude and Google AI Overviews, and adds citation analysis and enterprise reporting. There's a free seven-day trial, and paid plans are priced on request.

Other names you'll come across include Scrunch, AthenaHQ, Hall, LLMrefs and ZipTie. They cover similar ground with different strengths and price points.

How to choose

Before you commit to any tool, check four things:

• Engine coverage. Make sure it tracks the AI tools your buyers actually use. For most B2B companies, that means ChatGPT and Google AI Overviews at a minimum, with Perplexity and Copilot close behind.

• Custom prompts. Generic prompt databases are useful for benchmarking, but you need to track the specific questions from your own prompt list.

• Citation detail. The best tools show which sources the AI cited, not just whether you were mentioned. That's what tells you where to focus outreach.

• How the data is collected. Every tool runs simulated prompts rather than seeing real user conversations, and AI answers vary from run to run. Look for tools that run each prompt several times and show trends over weeks, not one-off snapshots.

For a hands-on comparison of these tools, with real test results, see our guide to the best AI visibility tools. [Internal link: /best-ai-visibility-tools/]

What GEO Results Look Like: Two B2B Examples

It's easy to talk about GEO in theory. It's more useful to see what happened when real B2B companies put it into practice. Below are two published examples from fintech, a crowded category where buyers do heavy research before talking to sales.

One caveat first: both case studies were published by Profound, the AI visibility platform these companies used. Like most vendor case studies, the numbers are self-reported and focus on the wins. Still, both name the client, describe what was done and give specific figures, which is more than most GEO "case studies" online offer.

Ramp: from 19th to 8th in its category

The company. Ramp sells finance automation software, including an accounts payable (AP) product.

The problem. When buyers asked AI tools about accounts payable software, Ramp barely showed up. Its AI visibility for the category was just 3.2%.

What they did. Ramp's team looked at which content AI engines were already citing for AP-related prompts. Two patterns stood out: automation topics and software comparisons. Instead of rewriting the whole site, they built four pages aimed squarely at those gaps:

• Accounts payable software for small businesses

• Accounts payable software for large businesses

• A roundup of the top AP automation tools

• A guide to AI in accounts payable

The results. Between December 2024 and mid-February 2025, Ramp's AI visibility for accounts payable rose from 3.2% to 22.2%, roughly a 7x increase. The new pages earned more than 300 citations, and Ramp moved from 19th to 8th among fintech brands for AP-related answers.

Ashley Nguyen, an SEO strategist at Ramp, said the tracking "uncovered behavioral patterns traditional SEO tools couldn't capture."

Why it worked. Ramp didn't guess. It studied what AI engines were already citing, then created the exact type of content they favored: audience-specific pages and comparisons. That's steps 2, 3 and 6 of the playbook above, done on a small number of pages.

CRS Credit API: tying AI visibility to pipeline

The company. CRS is a mid-market fintech that provides credit data, fraud detection and compliance tools through a single API. It serves more than 1,000 fintechs, lenders and screening providers.

The problem. CRS relied mainly on paid advertising. As more buyers started using AI tools like ChatGPT to discover vendors, the company had no way to see whether it appeared in those answers, or whether it mattered for revenue.

What they did. CRS focused as much on measurement as on content:

• Connected AI visibility data to its existing Google Analytics and Looker setup

• Built a full-funnel view that linked AI answers to MQLs and closed deals

• Set up a repeatable process for spotting new opportunities in AI answers

• Created FAQ-style content designed to be easy for AI models to pick up

• Got guidance on Reddit strategy as part of its off-site work

The results. CRS reports a 20x increase in AI search visibility, an 8% rise in weekly traffic from AI citations, and 15% pipeline growth attributed to AI search traffic. The case study doesn't give an exact timeframe.

Why it worked. The standout lesson from CRS is the measurement. Plenty of companies track mentions. Far fewer connect them to pipeline. By tying AI visibility to MQLs and deals, CRS could show leadership that GEO was a revenue channel, not just a vanity metric. That's section 7 of this guide in action.

What these examples have in common

Neither company published hundreds of new pages or relied on tricks. Both followed the same basic pattern:

1. They measured first. Each started by finding out where they stood in AI answers and which sources AI engines preferred.

2. They created focused content. Ramp built four targeted pages. CRS leaned on FAQ-style content. Both matched the formats AI engines were already citing.

3. They tracked results against business goals. Ramp tracked category ranking against competitors. CRS tracked pipeline.

The numbers will look different for every company, but the approach carries over to almost any B2B category.

The B2B GEO Playbook: 9 Steps

This is the process we follow with B2B clients. The steps are roughly in order, but don't wait to finish one before starting the next. Steps 3 to 7 usually run in parallel once the groundwork is in place.

Step 1: Map the prompts your buyers actually ask

Keyword research tells you what people type into Google. GEO needs a different list: the questions people ask AI tools when they're looking for a solution like yours.

These prompts are usually longer and more conversational than keywords. Someone might search "CRM for real estate" on Google but ask ChatGPT, "What's the best CRM for a real estate team of 10 that integrates with Gmail and doesn't cost a fortune?"

Build a list of 30 to 50 prompts across these groups:

• Category prompts: "What are the best [category] tools for [audience]?"

• Problem prompts: "How do I fix [pain point your product solves]?"

• Comparison prompts: "[Your brand] vs [competitor]" and "Alternatives to [competitor]"

• Use-case prompts: "Best [category] for [industry, team size or specific need]"

• Brand prompts: "Is [your brand] any good?" and "What does [your brand] do?"

Your sales team is the best source here. Ask them what prospects say on first calls and which competitors come up. Those exact phrases are often what buyers type into AI tools too.

Step 2: Audit where you're cited today

Run each prompt through ChatGPT, Perplexity, Gemini and Google's AI Mode. For each answer, note:

• Whether your brand is mentioned at all

• How it's described, and whether that's accurate

• Which competitors are named

• Which sources are cited

Do this in a clean browser session with no logged-in history, because personalization can skew results. AI answers also change from one run to the next, so run each prompt a few times before drawing conclusions. A simple spreadsheet works fine to start.

The most useful column is the last one. The sources AI engines cite for your prompts are your target list. If the same G2 category page, Reddit thread and industry roundup keep appearing, those are the places you need to be.

Step 3: Structure your content so AI can quote it

AI models pull passages, not whole pages. Make your best content easy to lift.

• Lead with the answer. Put the direct answer in the first one or two sentences under each heading, then explain.

• Write headings as questions where it makes sense. "How long does link building take?" matches a prompt better than "Timelines."

• Use tables for comparisons and short lists for steps or features. Models handle structured information well.

• Define terms clearly. A clean, one-sentence definition is one of the most frequently cited formats.

• Keep each section self-contained. A paragraph should make sense even if you pull it out on its own.

Start with the pages that matter most for revenue: your main service or product pages, comparison pages and your most popular guides.

Step 4: Publish data nobody else has

This is the most underused step in B2B, and probably the most powerful.

AI engines love specific facts, especially facts they can't find anywhere else. If you're the only source of a number, you're the one that gets cited.

You likely already have useful data:

• Benchmarks from your customer base (average results, timelines, costs)

• Survey results from your audience or community

• Analysis of your own campaigns or product usage

• Pricing research across your industry

Publish it with clear headline stats, a short methodology note and a date. One solid original study can earn citations, backlinks and press mentions for years.

Step 5: Get mentioned on sites AI engines trust

This is where GEO moves beyond your own website. Remember the sources from your audit in step 2. Your goal now is to show up on them, and on others like them.

That means:

• Industry publications that cover your space

• Expert roundups and contributed articles from your team

• Podcasts and interviews, since transcripts get indexed and read

• Partner and integration pages where your brand is listed

Unlinked mentions still help here, but a mention with a link does double duty: it supports both your GEO and your traditional rankings. Quality matters far more than quantity. Ten mentions on respected sites will do more than a hundred on sites nobody reads. [Internal link: /brand-mentions/]

Step 6: Earn a spot on "best of" and comparison lists

Ask any AI tool for the best options in a B2B category, look at the sources, and you'll see that a big share are listicles and comparison articles. "Best X for Y" content drives much of how AI engines build shortlists.

So go after those lists directly:

• Find the top-ranking "best [category]" and "[competitor] alternatives" articles for your space.

• Reach out to the authors with a clear reason you belong. Offer a free account, a demo, an expert quote or updated data.

• Create your own honest comparison pages. Yes, AI engines can see that you wrote them, but a fair, detailed comparison still gets cited, especially for "[you] vs [competitor]" prompts.

Keep it honest. If your comparison page claims you win on every point, readers and models will both discount it.

Step 7: Show up where buyers talk to each other

AI engines lean heavily on community and review content because it reflects what real users think. For B2B, that mostly means:

• Review platforms: G2, Capterra, Clutch and TrustRadius. Keep your profiles complete, current and active with fresh reviews.

• Reddit: Threads in relevant subreddits are cited constantly. Take part as a real person with real expertise. Promotional posts get removed and do more harm than good.

• LinkedIn: Posts and articles from your founders and team members help build the association between people, your brand and your topics.

• Niche communities: Slack groups, forums and Q&A sites in your industry.

You can't fake this one. What works is a steady effort to be helpful where your buyers already spend time.

Step 8: Get the technical basics right

None of the above matters if AI crawlers can't access your content.

Check your robots.txt and CDN settings. Make sure you aren't accidentally blocking the bots AI tools use, such as OAI-SearchBot and ChatGPT-User (OpenAI), PerplexityBot, ClaudeBot and the bots behind Google and Bing. Some companies blocked AI crawlers years ago and forgot about it. Cloudflare has also blocked AI crawlers by default for new domains since July 2025, so check your settings there too. If you want to stop your content from being used for model training but still appear in AI answers, you can usually allow search bots while blocking training bots, such as GPTBot.

Don't hide key content behind JavaScript. Research by Vercel found that AI crawlers from OpenAI, Anthropic and Perplexity don't run JavaScript. If your important text only appears after scripts run, those crawlers see a blank space. Server-side rendering or static generation solves this.

Use schema markup where it fits. Organization, Product, Article and FAQ schema help search engines understand who you are and what a page covers. Google no longer shows FAQ rich results, though, so don't add FAQ schema expecting a visual boost in search. Google also says no special schema is needed to appear in AI Overviews or AI Mode, so treat it as good housekeeping rather than a GEO shortcut.

What about llms.txt? It's a proposed file that gives AI models a curated summary of your site. Google has said you don't need to create new AI text files or special markup to appear in its AI features, and no other major AI company has confirmed using llms.txt for citations. It's cheap to add and won't hurt, but don't expect it to move results.

Step 9: Keep everything fresh and consistent

AI engines get confused when sources disagree. If your pricing page says one thing, your G2 profile says another and an old press release says a third, the model may repeat the wrong version or leave you out.

Set a recurring check, quarterly works for most teams, to make sure these match everywhere:

• Company description and positioning

• Pricing and plans

• Key features and integrations

• Customer numbers and headline results

• Founder and leadership details

At the same time, update your most important pages with current data and a new "last updated" date. For time-sensitive prompts, a refreshed page will often beat a stronger but outdated one.

How to Track and Measure GEO Results

This is where many teams get stuck. With SEO, Search Console tells you your rankings, clicks and impressions. AI engines offer very little of that, for now. You won't get a neat dashboard handed to you, so you have to build your own view from a few sources.

The good news is that it's very doable, and a simple setup is enough to show whether your work is paying off.

The five metrics that matter

1. Mention rate. Of your tracked prompts, what share of AI answers mention your brand? If you track 50 prompts and appear in 12 answers, your mention rate is 24%. This is your headline number.

2. Share of voice. How often are you mentioned compared with your competitors across the same prompts? This puts your mention rate in context. Showing up in 24% of answers is great if your top competitor is at 15%, and less great if they're at 60%.

3. Citation count. How often is one of your pages linked as a source? A mention means the AI named you. A citation means it pointed buyers to your content. Both count, but citations can also send traffic.

4. Accuracy. When an AI tool mentions you, is the description right? Check pricing, features, positioning and who you serve. A mention with outdated pricing can cost you a deal. Don't spend much time on where you appear in the list, though. A January 2026 SparkToro study found that AI tools almost never give the same list of brands twice, let alone in the same order, so position changes from one run to the next mean very little.

5. AI referral traffic. How many visitors arrive from AI tools, and what do they do once they land? This metric connects GEO to pipeline.

How to find out where AI cites your website

You have two options: track manually or use a tool.

Manual tracking works well for getting started. Each month, run your prompt list from step 1 through ChatGPT, Perplexity, Gemini and Google AI Mode. Use a logged-out or incognito session to limit personalization. Record the results in a spreadsheet with these columns:

One thing to know: AI answers vary a lot. Ask the same question twice and you'll often get a different list. That's why a single check tells you very little. Run your most important prompts several times each and track how often you appear across all runs. The more runs you do, the more reliable your numbers become.

Tracking tools take over once your prompt list grows beyond what you can check by hand. They run prompts automatically, track mentions over time and benchmark you against competitors. We cover the options in the next section.

Tracking AI referral traffic in GA4

Most AI tools pass referral data when someone clicks a cited link, and ChatGPT also adds a utm_source=chatgpt.com tag to many of its links. So these visits do show up in Google Analytics 4. By default, though, they're scattered across "Referral" with everything else.

To group them together, create a custom channel group:

1. Go to Admin, then Data display, then Channel groups.

2. Click Create new channel group. It starts as a copy of GA4's default group, so your existing channels stay in place. Give it a name like "Channels with AI."

3. Click Add new channel and name it "AI Search."

4. Click Add condition group, choose Source, set it to matches regex, and paste in:

5. Save the channel, then click Reorder and drag AI Search above Referral. GA4 assigns each session to the first channel it matches, so if Referral sits higher, it will catch these visits first.

6. Save the group. It applies to past data too, so you'll see historical AI traffic right away.

Standard GA4 properties allow two custom channel groups, so check whether one is already in use before creating a new one.

Now you can see AI traffic as its own line, compare it with organic search, and check how it converts. AI visitors have often already done some of their shortlisting, so watch demo requests and contact form submissions from this channel, not just sessions.

Two blind spots to keep in mind. Clicks from Google's AI Overviews and AI Mode currently show up as regular Google organic traffic, so you can't separate them. And many people read an AI answer, then search your brand name directly. That shows up as branded search or direct traffic, not AI referrals. A rise in branded searches after GEO work is often a sign it's working.

A simple monthly GEO report

Keep reports short so they actually get read. One page per month covering:

• Mention rate and share of voice, compared with last month and your top three competitors

• Prompts won and lost, meaning new prompts where you now appear and any where you dropped out

• Top cited pages on your site, plus top third-party sources that mention you

• Accuracy issues, such as wrong pricing or old descriptions that need fixing at the source

• AI referral traffic and conversions from the GA4 channel

• Branded search trend from Search Console

• Next month's priorities based on the gaps you found

Setting expectations

GEO results build gradually. Quick fixes like restructuring pages and updating review profiles can show up within weeks on engines that search live. Changes in how a model talks about your brand from memory take much longer, because they depend on the wider web shifting and models being updated.

For most B2B brands, expect a clear trend within three to six months rather than overnight jumps. Track consistently, compare month to month, and judge the program on direction rather than any single answer.

Should You Hire a GEO Agency?

Not every company needs outside help with GEO. Plenty of B2B teams can handle the basics themselves, especially if they already have solid SEO and content in place. But GEO touches many areas at once: content, technical SEO, PR, reviews, community, and measurement. That's often more than a small marketing team can cover well.

Here's how to decide, what it typically costs, and how to tell a good partner from a risky one.

When you can do it in-house

You probably don't need an agency yet if most of these apply:

• Your SEO is already in good shape, with pages that rank for your main category terms

• You have someone who can own a prompt list and check it every month

• Your team can produce clear, well-structured content on a steady schedule

• You have existing relationships with publications, partners or communities in your space

• You're still testing whether AI search matters for your buyers

In that case, start with the quick wins from section 6, set up the tracking in section 7, and revisit the decision in three to six months.

You're not alone in taking this route. Forrester's 2026 B2B Brand and Communications Survey found that marketers are becoming more selective about agency spend as they adopt AI. The share planning to increase spending on digital marketing agencies fell from 51% to 31% in a year, as teams look at which work they can bring in-house.

When an agency makes sense

The same Forrester survey points to where outside help still earns its keep. Over half of marketing leaders now rank data strategy and AI readiness as a top priority when picking an agency, yet only a small share are satisfied with what agencies deliver there. Specialist expertise is the gap.

An agency is usually worth it when:

• You're starting from a weak position. If AI engines rarely mention you and competitors dominate the answers, catching up takes more than a part-time effort.

• Off-site work is the bottleneck. Earning brand mentions, listicle placements and editorial coverage takes relationships and outreach time that most in-house teams don't have.

• Your category is crowded. In competitive B2B categories, the brands that win AI shortlists tend to have consistent, sustained work behind them.

• You need proof for leadership. A good partner brings tracking tools and reporting that ties AI visibility to pipeline, not just screenshots.

What GEO services typically cost

There's no standard price list yet, and most published figures come from agencies' own pricing guides rather than independent surveys. Still, they give a useful sense of the 2026 market.

Most agencies work on monthly retainers rather than one-off projects, because GEO needs ongoing monitoring and adjustment. When comparing quotes, compare like-for-like. An audit-only fee and a full program with content and outreach aren't the same thing, even if both are called "GEO services."

Questions to ask before you sign

Google's long-standing advice on hiring an SEO applies almost word for word to GEO. Add a few AI-specific questions and you have a solid vetting list:

1. Which AI engines do you track, and how? Look for named tools and a clear method, ideally one that runs each prompt several times rather than relying on single snapshots.

2. Can you show me examples of your previous work? Ask for before-and-after data on AI visibility, not just traditional rankings.

3. How do you define success? Good answers mention share of voice, citation trends, accuracy and AI referral traffic tied to leads.

4. What will you do off-site? If the plan is all on-page tweaks with no mention building, PR or review work, it's missing half the picture.

5. What results do you expect, and when? Realistic partners talk about trends over three to six months, not overnight jumps.

6. What's your experience in my industry? B2B buying cycles and prompts look very different from consumer ones.

7. How will we communicate, and what will I see each month?

Red flags to watch for

Walk away if an agency:

• Guarantees AI citations or a spot in ChatGPT answers. Nobody controls what AI models say. Google has warned for years against anyone who guarantees a #1 ranking, and the same logic applies here.

• Claims a special relationship with OpenAI, Google or any AI company.

• Won't explain its methods clearly. "Proprietary AI optimization" with no detail usually means there's nothing behind it.

• Has no tracking in place. If they can't show you how they measure AI visibility, they can't show you results.

• Pushes shortcuts. Hidden prompts, fake reviews, sockpuppet Reddit accounts or mass-produced content can backfire and damage the trust GEO depends on.

• Cold-emails you out of the blue with a too-good-to-be-true offer. Google flags this as a warning sign for SEO firms, and it holds for GEO too.

How Marketing Lad can help

If you'd rather not build all of this alone, our Brand Mentions & LLMO service is built for B2B companies that want to show up in AI answers. We handle the off-site work that's hardest to do in-house, including earning editorial mentions, getting you onto the lists AI engines cite and keeping your brand information consistent across the web. We document every placement and report on AI visibility alongside the rankings and links you already track.

Frequently Asked Questions