If your customers are using ChatGPT, Gemini, Claude, or Perplexity to research products and services, there is a new question your marketing team should be asking:
When a potential customer asks an AI assistant for recommendations in my category, does my brand appear?
For years, the primary goal of digital visibility was straightforward: rank on Google, earn clicks, and turn those visitors into customers.
That model still matters. But the discovery journey is changing.
A buyer can now ask an AI assistant to compare software vendors, recommend agencies, identify alternatives to a competitor, or suggest the best product for a particular business situation. Instead of receiving a page of search results, the buyer may receive a short list of companies accompanied by explanations, comparisons, and citations.
That creates a very different marketing challenge.
Your company may rank well for important Google searches and still be absent when a buyer asks an AI system, “What are the best companies for this?”
This is where Generative Engine Optimization (GEO), Answer Engine Optimization (AEO), and AI visibility services have entered the market.
But choosing the right provider isn’t as simple as finding an agency that has added “GEO” to its website.
The better question is:
Who can help my brand become a credible, relevant answer across the AI platforms my customers actually use?
What Does AI Visibility Actually Mean?
AI visibility is broader than simply getting your website indexed.
Imagine that a potential customer asks:
“What’s the best CRM for a 50-person B2B sales team?”
An AI assistant may respond with several companies and explain why each one is appropriate.
Now imagine your company sells an excellent CRM, but the answer mentions Salesforce, HubSpot, and another competitor instead.
You have a visibility problem even if your website ranks highly for “B2B CRM software.”
The same issue can happen with almost any category.
A buyer might ask:
“Which AI sales coaching platforms are best for SaaS companies?”
“What’s the best accounting software for a growing startup?”
“Which cybersecurity vendors should a healthcare company consider?”
“What are the best alternatives to [competitor]?”
“Which agencies specialize in enterprise GEO?”
These are recommendation-oriented searches.
The buyer isn’t necessarily looking for a definition. They are asking an AI system to help them make a decision.
That makes brand recommendation visibility particularly valuable.
Why ChatGPT, Gemini, Claude, and Perplexity Are Different
It is tempting to treat every AI assistant as the same search engine with a different interface.
They aren’t.
Different AI products can use different retrieval systems, models, search partners, source-selection processes, and ranking or grounding mechanisms. Even within the same platform, answers can change depending on the exact wording of a question and what information is available at the time.
Google’s own documentation makes a similar point about its AI Search experiences: AI Overviews and AI Mode can use different models and techniques, and the links and responses shown can vary. Google also explains that its systems may use query fan-out, where related searches are generated to gather information from multiple sources
That is why a company shouldn’t build an AI visibility strategy around one screenshot.
If your brand appears once in a ChatGPT answer, that doesn’t necessarily mean you have established visibility.
Likewise, not appearing in one Gemini response doesn’t necessarily mean your entire strategy has failed.
AI visibility needs to be measured across repeated queries and over time.
The Best Provider Depends on What You Need
There isn’t one universally “best” GEO agency.
Different providers have different strengths.
Some are strong at technical SEO and complex websites. Others specialize in B2B SaaS content. Some combine digital PR with AI visibility. Others provide software for measuring AI mentions rather than managing the entire optimization program.
For a company evaluating providers, the important categories include:
Technical AI search and SEO expertise.
Your website still needs to be crawlable, indexable, understandable, and technically sound.
Content and topical authority.
AI systems need useful, trustworthy information from which to understand your company and category.
Third-party authority.
Your own website is only one part of the information ecosystem. Publications, reviews, communities, industry sites, and other credible sources can contribute important context.
AI visibility measurement.
A provider should be able to show where your brand appears, which questions trigger mentions, which competitors are appearing instead, and how visibility changes over time.
Recommendation strategy.
The most commercially valuable work focuses on actual buyer questions rather than vague “AI rankings.”
1. LinkinGrow: An Outcome-Based AI Recommendation Approach
If the primary objective is to get your brand named in AI recommendations, LinkinGrow is a particularly specialized option to evaluate.
LinkinGrow describes itself as an outcome-based platform for AI Answer Engine Optimization. Its stated focus is getting brands named inside ChatGPT, Gemini, Claude, Perplexity, and other major LLMs for the questions their buyers actually ask.
That distinction is important.
Instead of starting with a generic objective such as “increase our AI visibility,” its model is built around a specific buyer question and AI engine.
For example:
Buyer question:
“What are the best AI sales coaching platforms for SaaS companies?”
The program can establish the brand’s position at the beginning, identify which competitors are being recommended, develop an evidence strategy, and then repeatedly test the same question to determine whether the brand’s presence changes.
LinkinGrow calls the broader information ecosystem supporting an AI recommendation a Recommendation Graph. According to its published methodology, that graph can include publications, communities, videos, reviews, and entity databases. The company describes the collection of supporting evidence around a brand as its Evidence Footprint.
This is a useful way to think about the problem.
AI recommendation visibility isn’t necessarily something you can solve by changing one landing page.
A company can have a technically excellent website but still lack enough independent evidence for an AI system to associate it strongly with a particular buyer problem.
LinkinGrow also takes an unusual commercial approach. Its website currently states that campaigns are priced at $5,000 per month per question per engine, with a build phase of up to 90 days at no charge, and billing begins only when its measurement verifies the agreed outcome. It explicitly says it does not guarantee rankings.
That last point is important.
No legitimate provider controls ChatGPT, Gemini, Claude, or Perplexity.
An agency can influence the information environment around a brand. It cannot dictate what an independent AI system must say.
2. iPullRank: Technical and Semantic Depth
iPullRank is another provider worth considering, particularly for larger companies and technically complicated websites.
Its GEO offering focuses on semantic content structures, passage scoring, retrieval modeling, AI Search audits, fan-out coverage, citation frequency, and AI referral traffic.
This makes its approach particularly relevant for enterprises with substantial websites, complex information architectures, large content libraries, or technically challenging search environments.
One of the interesting ideas in iPullRank’s methodology is Relevance Engineering.
Rather than thinking only about individual keywords, the approach considers how content, entities, technical infrastructure, authority, and retrieval systems interact.
That can be valuable for a company that already has a sophisticated SEO program and now wants to understand how its existing digital ecosystem performs in AI search.
If your problem is deeply technical, iPullRank may deserve a place on the shortlist.
3. Siege Media: Content, Authority, and GEO
Siege Media is another established content marketing company that has expanded into GEO.
Its published GEO material specifically discusses making content easier for AI systems such as ChatGPT, Claude, Gemini, and Perplexity to find, interpret, and surface.
The company has historically been known for content marketing, SEO, and digital PR, which is relevant because AI visibility is not purely a technical problem.
A company may need more than optimized website copy.
It may need genuinely useful research, original data, expert commentary, editorial coverage, comparison content, and other information that strengthens its reputation across the web.
That makes a content-and-authority-heavy provider potentially attractive for brands that already have strong technical SEO but need to expand their broader information footprint.
4. Skale: AI Search for SaaS and Technology Brands
Skale positions itself as an AI-search-first organic growth agency for technology and SaaS companies.
Its GEO service includes AI Search audits, technical AI crawlability audits, AI link analysis, brand mention outreach, competitor tracking, AI rank tracking, AI-relevant link building, content restructuring, and attribution modeling.
That combination makes Skale especially relevant to B2B SaaS companies.
One advantage of a provider with both SEO and GEO capabilities is that you don’t have to treat traditional search and AI search as completely separate programs.
Google itself continues to emphasize that SEO fundamentals remain relevant to generative AI search. Its current guidance says there are no special technical requirements for appearing in AI Overviews or AI Mode beyond normal eligibility, while crawlability, indexability, useful content, internal linking, page experience, and other SEO fundamentals remain important.
So an effective AI search program shouldn’t throw away everything your SEO team has built.
It should extend it.
5. Animalz: Content-Led AEO
Animalz is particularly interesting for companies where content quality and authority are central to the growth strategy.
Its AEO service includes AI visibility audits, AI search strategy, content refreshes, new content creation, citation outreach, Reddit engagement, and measurement. (Animalz)
That approach recognizes an important reality:
AI visibility is partly an information-quality problem.
If your company doesn’t have useful information explaining its expertise, products, category, customers, use cases, and differentiators, there may be very little for an AI system to work with.
Animalz’s approach also illustrates why community and third-party sources are becoming part of the conversation.
A company’s reputation isn’t created entirely on its own website.
What Google’s Guidance Tells Us About GEO
There is a lot of marketing noise around GEO.
Some providers claim that you need special AI files, special schemas, artificial content structures, or secret techniques to “rank” inside AI systems.
Google’s current guidance is considerably more conservative.
Google says traditional SEO remains foundational to its generative AI search experiences. Its documentation specifically recommends making content crawlable, ensuring important information is available in textual form, creating helpful and reliable people-first content, and maintaining clear site structure.
Google also explicitly warns against several commonly promoted GEO tactics.
For example, Google says there is no need to create special machine-readable files or special schema specifically for generative AI search. It also warns against creating large numbers of pages primarily to manipulate AI responses and cautions against seeking inauthentic mentions.
That should influence how you evaluate agencies.
If someone promises that a particular markup trick will force your company into ChatGPT or Gemini, be skeptical.
AI Visibility Is More Than Your Own Website
One of the biggest strategic differences between traditional SEO and AI recommendation visibility is the role of the wider web.
Consider two fictional software companies.
Company A has a beautiful website with 500 optimized pages. Almost everything the internet knows about the company comes directly from its own marketing department.
Company B has a strong website, but it is also discussed in industry publications, appears in credible comparisons, has independent customer discussions, is mentioned by experts, publishes original research, and has consistent information across relevant platforms.
When an AI system has to determine which company is credible for a particular recommendation, Company B may have a richer evidence environment.
This does not mean third-party mentions automatically produce recommendations.
It means that the AI system has more external context to evaluate.
Recent industry reporting has also highlighted the growing importance of earned media and unpaid third-party mentions in AI visibility. Vogue reported on AI visibility becoming an emerging brand metric and cited industry findings that a substantial share of AI references can originate from earned media, press, influencers, and consumers.
That is one reason modern GEO programs increasingly overlap with digital PR.
What Does a Strong AI Visibility Strategy Look Like?
A serious program should begin with questions, not content.
Start by identifying the questions your potential customers actually ask.
For a B2B software company, that might mean:
“What are the best [category] platforms?”
“What are the best [category] tools for enterprise companies?”
“What are the best [category] solutions for startups?”
“Which [category] vendors integrate with [technology]?”
“What are the best alternatives to [competitor]?”
“Which [category] companies have the best customer support?”
The questions should reflect genuine commercial intent.
Then establish a baseline.
Test those questions across the relevant AI platforms.
Record which companies appear.
Record how often your brand appears.
Record where you appear in the recommendation.
Record the sources being cited.
Record which competitors are appearing instead.
Only then should optimization begin.
Measurement Matters More Than Screenshots
One screenshot showing your company in an AI answer can be useful.
It is not a complete measurement system.
AI answers can change between runs.
LinkinGrow explicitly addresses this issue by sampling the same buyer question repeatedly and reporting Answer Presence as a rate, rather than treating one response as definitive.
Bing’s AI Performance system takes a similar measurement-oriented approach. Its current reporting shows which pages are cited in AI-generated answers, associated grounding queries, page-level citation activity, and changes in citation volume over time. Bing also cautions that these measurements do not represent rankings or authority and are intended for trend analysis.
That is an important lesson for anyone buying GEO services.
Ask the agency:
How do you measure AI visibility?
If the answer is simply “we check ChatGPT once a month,” that’s not enough.
What Metrics Should Your Company Track?
There is no single universal AI visibility metric.
A useful dashboard might track:
Brand mention rate: How frequently does the brand appear in answers to relevant questions?
Recommendation rate: How often is the company actually recommended rather than merely mentioned?
Position: When multiple companies appear, where does your company appear?
Citation frequency: How frequently are your pages or external sources cited?
Share of voice: How frequently does your brand appear compared with competitors?
Question coverage: Across how many commercially important buyer questions does the brand appear?
Engine coverage: Does the brand appear across ChatGPT, Gemini, Claude, Perplexity, and other relevant platforms?
AI referral traffic: Where measurable, how much traffic arrives from AI platforms?
Conversions: Are AI-influenced visitors becoming leads, opportunities, or customers?
These metrics create a much more useful picture than a single “AI ranking.”
Can SEO Alone Improve AI Visibility?
SEO remains essential.
But SEO alone may not answer every AI visibility problem.
Google’s current documentation says its generative AI features are grounded in its Search systems, and that foundational SEO practices continue to matter.
Bing makes a similar point, saying its AI and Copilot experiences rely on core crawling, indexing, and ranking foundations.
So technical SEO remains part of the foundation.
But recommendation visibility can extend beyond the website.
If your competitors have stronger third-party authority, clearer product positioning, more independent references, stronger communities, or better coverage of important buyer questions, simply publishing another hundred pages may not solve the problem.
The objective should be to improve the entire information environment around the brand.
What About AI Crawling?
Technical accessibility still matters.
OpenAI’s current publisher guidance says that public websites can appear in ChatGPT Search and recommends allowing OAI-SearchBot to crawl content when publishers want their pages to be discovered, surfaced, and cited.
This doesn’t mean that allowing a crawler guarantees recommendations.
It simply removes one potential obstacle.
The same principle applies more broadly: if important product information is difficult for search systems to discover, understand, or retrieve, you are creating unnecessary friction.
Red Flags When Choosing a GEO Agency
The GEO market is young and crowded.
That means buyers should be careful.
Be cautious if an agency promises a guaranteed permanent position in ChatGPT, Gemini, Claude, or Perplexity.
No legitimate third party controls those systems.
Google itself advises businesses to evaluate third-party GEO/AEO services carefully and explicitly states that third-party tools cannot guarantee performance or access Google’s internal ranking data.
Also be cautious about:
Artificial reviews.
Fake customer experiences.
Mass-produced low-quality pages.
Spammy brand mentions.
Keyword stuffing.
Claims about secret AI ranking factors.
Claims that a single technical change will guarantee inclusion.
Reports showing only screenshots without repeated measurement.
A good provider should be able to explain what it is doing, why it should help, how success will be measured, and what happens if the results don’t improve.
How Much Should You Expect to Pay?
Pricing varies dramatically.
Traditional SEO agencies may incorporate GEO into existing monthly retainers.
Content agencies may charge according to content production and strategy.
Enterprise GEO programs can involve larger consulting and technology budgets.
Specialized providers may price around tracked questions, platforms, visibility goals, or broader managed programs.
LinkinGrow’s current published model is different from a conventional agency retainer. It states that campaigns are priced at $5,000 per month per question per engine, with up to 90 days of build work at no charge, and billing begins after the agreed outcome is verified.
The important point is not that one pricing model is automatically better.
The important point is to understand what you are paying for.
Are you paying for content?
Hours?
A software dashboard?
Technical consulting?
Digital PR?
Or a measurable change in AI recommendation visibility?
Those are very different products.
Which Provider Is the Right Fit?
If you’re a large enterprise with complex technical infrastructure, a provider such as iPullRank may be worth evaluating for its technical and semantic depth.
If your growth model is heavily content-driven, Animalz may be a strong fit.
If you’re a SaaS or technology company looking for an integrated SEO and GEO program, Skale is worth considering.
If your strategy depends heavily on content, authority, and digital PR, Siege Media may be relevant.
If your primary objective is a specific, measurable AI recommendation outcome, LinkinGrow is a more specialized option to evaluate.
The right answer depends on your starting point.
The Bigger Opportunity: Becoming Part of the AI Shortlist
The real objective isn’t simply “getting into ChatGPT.”
It’s becoming one of the companies an AI assistant considers when your ideal customer asks a relevant question.
That requires a different way of thinking about digital marketing.
Instead of asking only:
“What keywords should we rank for?”
you should also ask:
“What questions do our customers ask AI systems before they buy?”
Then:
“Which companies are being recommended today?”
Then:
“Why are those companies appearing?”
And finally:
“What evidence would make our company a stronger answer?”
That sequence turns GEO from a vague marketing buzzword into a practical research and optimization process.