An evidence-based guide to SEO, AEO and GEO for pharmaceutical and biotech marketers.
Overview
SEO remains the foundation for AI visibility. AEO and GEO don't replace SEO. Strong technical foundations, clear site architecture and high-quality, accessible content remain essential for traditional and AI-powered search.
Make your pharmaceutical expertise explicit and evidence-led. Clearly communicate your capabilities, modalities, manufacturing scale, technologies, facilities and experience. Replace generic claims with specific information customers and AI systems can understand.
Optimise for understanding, not AI algorithms. With no proven GEO shortcut, focus on useful capability pages, connected expertise, accessible PDF content, SME insights and answers to prospective customers' real questions.
Subscribe for email insights
In this guide
For years, pharma and biotech companies have invested in SEO to ensure their websites appear when prospective customers search for their services, technologies and manufacturing capabilities. That requirement hasn’t disappeared. But search is changing. Prospective customers can now ask Google and AI-powered platforms detailed questions about potential suppliers, technologies and manufacturing approaches. The result is a synthesised answer without necessarily working through a conventional list of search results.
And instead of searching “biologics CDMO” a user asks: “What should I look for when selecting a CDMO for commercial biologics manufacturing?” These are fundamentally different search experiences. For pharmaceutical marketers, this creates a new challenge. So, the goal is no longer to rank. We need to ensure search engines and AI systems understand what the company does, recognise the expertise and confidently use our information when answering a user’s question.
This is where SEO increasingly intersects with Answer Engine Optimisation (AEO) and Generative Engine Optimisation (GEO). And despite some of the more dramatic predictions surrounding AI search, succeeding in this new environment doesn’t require pharmaceutical companies to abandon everything they know about SEO. I’d say it requires them to do many of the fundamentals considerably better.
SEO, AEO and GEO: What’s the difference?
SEO, AEO and GEO are interconnected approaches that help search engines and AI systems find, understand and use your organisation’s content.
There is already an expanding vocabulary surrounding AI search. In an attempt to simplify (even though, at present, the boundaries between the three aren’t particularly very tidy):
Search Engine Optimisation (SEO)is about improving the visibility of your website within traditional search engine results via websites such as Google or Bing.
Generative Engine Optimisation (GEO) refers to efforts to improve the visibility, citation or influence of content within AI-generated responses via tools such as ChatGPT or Claude.
Answer Engine Optimisation (AEO) is commonly used to describe the process of making information easier for search (Google or Bing) and AI systems (ChatGPT or Claude) to understand and use when answering specific questions.
In fact, Google now explicitly addresses both AEO and GEO in its own guidance. Its position is straightforward: Optimising for generative AI search is still SEO because features such as AI Overviews and AI Mode are rooted in Google’s core Search ranking and quality systems. Google also states that there are no additional technical requirements for appearing as a supporting link in AI Overviews or AI Mode. A page must already be indexed and eligible to appear within conventional Google Search. This is an important distinction: GEO is not a replacement for SEO.
For pharmaceutical manufacturers, it is more useful to think about SEO, AEO and GEO as different parts of the same visibility challenge. Your website needs to be technically accessible and your content needs to clearly communicate what you know and what you do. And your organisation needs to demonstrate sufficient relevance, expertise and authority to be useful to customers — and potentially to the search and AI systems helping them conduct their research.
Why this matters for pharmaceutical manufacturing websites
Pharmaceutical manufacturers often possess deep technical expertise, but their websites do not always communicate it clearly enough for customers or AI systems to understand.
Pharmaceutical manufacturing websites are unusual. They aren’t e-commerce websites with thousands of products. Neither are they conventional publishing businesses, such as our sister brand The Pharma Navigator, producing lots of articles every week.
These websites often represent highly complex organisations providing combinations of drug substance/product manufacturing, formulation development, analytical services, different modalities and dosage forms, manufacturing facilities across multiple countries… there is usually a lot (and a lot more to that list) and the expertise behind those services can be enormous. But there is often a disconnect between the expertise that exists within the organisation and the information presented on its website.
A CDMO might have decades of manufacturing experience, hundreds of successful projects, specialist technologies, sophisticated facilities and scientists with extremely deep expertise. And its website might state its “Innovative solutions that accelerate your molecule’s journey to patients”. Nothing wrong with that from a brand perspective.
But consider how much ChatGPT, or even a prospective customer, actually learns from it. Not too much, I don’t think. Compare that with a page that clearly communicates the manufacturing service provided, molecules or dosage forms or development phases supported, potentially the manufacturing scale and technologies used or even the facility locations and supporting technical evidence. I’d say the learning experience is greatly improved.
The difference can already be seen on some leading CDMO websites. Lonza, for example, explicitly states on its integrated biologics manufacturing page that it has supported more than 70 commercial large molecules and delivered more than 300 successful technology transfers. Those are concrete pieces of information that help a customer and machine understand the organisation’s experience at the same time.
This leads to what is likely one of the most important principles for pharmaceutical websites entering the AI-search era…
Claim less. Evidence more.
Replace broad marketing claims with specific capabilities, measurable experience, technical evidence and other information that demonstrates genuine expertise.
The pharmaceutical industry isn’t short of claims. It quite common to find that an organisation is innovative and flexible or leading and world-class. These phrases may have a place within brand communications, but they do little to establish the specific capabilities of an organisation. Evidence, on the other hand, does.
Consider the information a prospective customer might genuinely need to establish whether a CDMO is relevant. Information on manufacturing capabilities, modalities supported, development stages and scale and technologies etc. The more clearly your website answers related questions, the easier it becomes for customers and machines to understand your organisation. Whilst it’s still early days in the AEO/GEO games, there is emerging research supporting the value of this type of content.
A 2026 study examining 602 controlled prompts across ChatGPT, Google and Perplexity analysed 21,143 valid search-layer citations and 18,151 successfully fetched pages. The researchers found that pages exerting greater influence on generated answers tended to be longer, more structured, semantically aligned with the query and richer in extractable evidence such as definitions, numerical facts, comparisons and procedural steps. And whilst this doesn’t prove that adding stats or restructuring a page will automatically make a pharmaceutical company appear in an AI response, it provides useful evidence for a more fundamental principle: clear, relevant and evidence-rich information is easier for generative systems to use. For pharmaceutical marketers, that is significant. Much of this information already exists inside pharmaceutical organisations; the challenge is exposing it.
A Pharma AI Visibility Framework
Use this framework to assess whether customers, search engines and AI platforms can clearly understand who you are, what you provide and why you are credible.
When reviewing an important manufacturing capability page, I would encourage marketers to ask whether a customer, search engine or AI system can clearly determine the following.
Who are you? Is the organisation clearly identifiable and is its role within the pharmaceutical ecosystem obvious?
What do you do? Are the actual services explicit?
For what? What types of products, modalities or dosage forms does the capability support?
At what stage? Can customers understand where you operate within the product lifecycle?
At what scale? Can a customer determine whether the capability is appropriate for their requirements?
How? Which manufacturing processes, platforms or technologies are involved?
Where? Which facilities provide the capability?
With what experience? Can you substantiate your experience?
With what evidence? Are case studies, technical data, application notes, scientific publications or other evidence available?
Who are the experts? Are the scientists, engineers and technical specialists behind the capability visible?
It isn’t an algorithm for “ranking in ChatGPT”. It is a practical way of determining whether your website contains enough specific and accessible information for humans and machines to properly understand your organisation.
1. Build dedicated capability pages
Give commercially important services, technologies and manufacturing capabilities enough depth to be understood and discovered.
One of the first places to look when assessing a website is its information architecture.
Whereas a generic hierarchy might look like: 1. Services to 2. Manufacturing to 3. Drug Product, one that meets the needs of a prospective customer who frequently has much more specific requirements might look like: 1. Drug Product Manufacturing to 2. Sterile Fill-Finish to 3. Vials or 1. Biologics to 2. Mammalian Manufacturing to 3. Commercial Manufacturing.
The more commercially important a capability is, the stronger the argument for providing it with sufficient dedicated information. This doesn’t mean creating hundreds of near-identical pages targeting every possible keyword or AI prompt variation.
Google note that websites don’t need to rewrite content to target every possible way somebody might phrase a request to a generative AI system. And you certainly don’t need to create hundreds of pages for different AI prompts - AI systems can understand synonyms and different ways of expressing the same intent.
Instead, ask whether your most important services, technologies and capabilities have enough genuinely useful information to deserve their own pages. Good website architecture therefore benefits conventional SEO, AI discovery and, most importantly, prospective customers trying to navigate a complex service offering. Create pages because there is a genuine customer or information need, not because somebody has generated 500 long-tail AI prompts.
2. Make manufacturing capabilities explicit
Clearly connect each capability with the modalities, dosage forms, development stages, manufacturing scales, technologies and locations it supports.
Review your key pages to determine if somebody with no prior knowledge of the organisation can understand exactly what you provide the page. Not your brand proposition. More so what you actually do.
If you operate single-use bioreactors up to a particular scale, provide that information where commercially appropriate. If you support clinical and commercial programmes, make that clear. If a particular facility handles specific dosage forms, connect those pieces of information. This is particularly important because AI searches can be highly specific.
If a user asks: Which European CDMOs offer commercial-scale mammalian biologics manufacturing? To be relevant to that question, there needs to be enough information available to associate your organisation with: Europe + CDMO + mammalian biologics + commercial + manufacturing. (Almost like traditional long-tail SEO content writing!) The clearer those relationships are across your website, the better positioned your content is to answer that type of query.
3. Turn facility pages into useful resources
Move beyond addresses and corporate descriptions by providing the practical information prospective customers need to evaluate each manufacturing site.
We talk a lot about promoting facilities across a range of channels with our clients at Orientation Marketing. Facility pages represent a significant opportunity for pharmaceutical manufacturers. Too often they amount to a photograph of the building, an address and a few paragraphs describing state-of-the-art facilities.
Instead, think about what a prospective customer evaluating that site might actually want to know. Depending on what can appropriately be disclosed, that could include anything from this list (generated by a generative AI system):
Location
Manufacturing services
Modalities
Dosage forms
Manufacturing lines
Equipment
Capacity
Batch sizes
Development stages supported
Technologies
Containment capabilities
Certifications
Regulatory inspection history
Specialist expertise
Investments and expansions
Relevant technical resources
People responsible for the facility.
This turns a facility page from corporate information into something genuinely useful during supplier research which is both relevant to a scientific/technical person as well as a procurement/C-suite person. And it also establishes a much stronger relationship between location, capability/technology and expertise.
4. Bring technical expertise out of PDFs
Surface important findings, data and specialist knowledge within accessible web content rather than leaving valuable expertise solely inside downloadable documents.
Here is something that goes against much of the approaches we’ve seen in the space over the last 10 years.
Pharmaceutical companies produce huge quantities of valuable technical information. It sits within application notes, scientific posters, whitepapers, technical brochures, conference presentations, research papers and datasheets. I’ve probably missed a few. Much of it ends up as PDF files. PDFs can remain valuable, particularly when they are used as downloadable resources or sales enablement material. but important knowledge shouldn’t exist *only* inside them.
If your scientists have produced an application note containing original data about a manufacturing process, extract the important findings and create useful content around them. The objective isn’t to duplicate everything. It is to ensure that the expertise contained within the organisation is adequately represented within the wider website so it can be picked up by the generative and answer engines. This also creates stronger internal relationships between commercial service pages and technical evidence.
5. Answer real customer questions
Use insights from business development teams, technical specialists, RFPs and customer conversations to create content around the questions buyers genuinely ask.
Keyword research remains useful when identifying new keywords and phrases to target on web pages. But pharmaceutical marketers have another extremely valuable source of information within their own organisation.
Talk to business development. Talk to technical teams. Look at RFPs. Review questions asked during webinars. What questions repeatedly appear during supplier evaluation? Those questions can reveal some of your best content opportunities.
“What should I consider when selecting a sterile fill-finish CDMO? When should commercial technology transfer begin? What are the advantages of integrating drug substance and drug product manufacturing? How does manufacturing scale affect process development?”
These questions are useful because they reflect the conversational way people can interact with AI systems. But they are also useful independently of AI. They are the questions prospective customers genuinely need answered. That is what good AEO should ultimately be about.
6. Structure content for quick answers
Organise information with descriptive headings, direct answers, evidence and clear formatting so that individual sections can be easily understood and retrieved.
A common misconception about GEO is that every piece of content needs to be completely rewritten into tiny “AI-friendly” chunks. There doesn’t seem to be any evidence to support this at this present moment.
What does matter is clarity. An interesting test is to take an individual section of a page and ask: Could somebody understand this section without having read the entire page? If the answer is yes, it is likely to be useful to both customers and systems retrieving information from that page. Some pointers (again, provided by my artificial companion) might be:
Use descriptive headings.
Answer the question being asked.
Define specialist terminology where necessary.
Use lists when a list genuinely makes information clearer.
Use tables for meaningful comparisons.
Include numbers and evidence.
Avoid unnecessarily hiding an answer beneath hundreds of words of introduction.
Use FAQs selectively
Give pages a clear introductory summary.
Link relevant concepts together
Make important information available as HTML.
7. Make subject-matter experts visible
Connect technical content with identifiable scientists, engineers and specialists to demonstrate the genuine expertise behind your organisation.
Pharmaceutical manufacturers possess something many industries would love to have - genuine experts. Scientists. Engineers. Regulatory and manufacturing professionals. Yet corporate websites often make these people almost invisible. (Granted, other political reasons can prevent the SMEs from being featured on the website also.) And that is a missed opportunity.
Where appropriate, technical content should have identifiable authors or contributors that can explain experience and qualifications, as well as content from webinars and technical articles. In doing this, a stronger connection between the SME and organisation is created. But perhaps more importantly for increasing visibility on AI search, it also makes the content more credible for the human reader.
In an environment increasingly filled with inexpensive AI-generated content, demonstrating that genuine expertise sits behind your information is only likely to become more important.
8. Strengthen your technical SEO foundations
Maintain strong crawlability, indexation, internal linking, page experience and structured data so that your content remains discoverable across conventional and AI search.
With so much attention being given to GEO, it can be tempting to start looking for entirely new technical solutions to improve AI visibility. But don’t neglect the fundamentals.
Google’s guidance is clear: Conventional SEO best practices remain foundational to visibility in its generative AI search experiences. And you can assume that the generative engines lean towards this principle (unless we are explicitly told otherwise by those generative engines).
For a page to be eligible as a supporting link in Google AI Overviews or AI Mode, it must be indexed and eligible to appear in Google Search with a snippet.[2]
That means pharmaceutical websites should continue to practice SEO and conduct conventional SEO techniques. So, for example, crawlability, internal linking, page experience and structured data where appropriate. A technically poor website doesn’t become AI-ready simply because somebody adds FAQs to it.
9. Build authority beyond your website
Strengthen your wider industry presence through credible publications, media coverage, expert contributions, research, associations and conference participation.
Improving your website is only part of the challenge. One of the most interesting areas of emerging AI-search research concerns wider brand mentions.
Ahrefs analysed 75,000 brands and millions of AI responses across ChatGPT, Google AI Mode and AI Overviews. It found that branded web mentions had a relatively strong correlation with AI visibility across the platforms studied. The same study found almost no relationship between simply having a larger number of pages on a website and AI visibility. So, the research suggests that wider brand mentions are associated with greater AI visibility, but it doesn't prove that increasing brand mentions alone will improve AI visibility.
The point here is clear (and it hasn’t changed since the sole SEO days): Your brand exists beyond your domain and that’s why trade media, publications and industry associations are important. A pharmaceutical manufacturer wanting to establish authority around continuous manufacturing, for example, shouldn’t expect its own continuous manufacturing web page to carry the entire burden.
Its scientists should be discussing the subject. Its data should be published. Its experts should appear at relevant conferences. Its company should be referenced by relevant third parties. Its technical expertise should exist across the wider industry ecosystem. This is where GEO increasingly overlaps with SEO, digital PR, thought leadership and media planning and buying.
But don’t chase artificial brand mentions. Industry research gives us reasons to take wider brand presence seriously, but that doesn’t mean manufacturing mentions at scale. Google explicitly cautions against seeking inauthentic mentions and says its ranking and spam systems continue to apply to generative search. The objective should be genuine industry authority, not manufacturing signals designed to look like authority.
10. Measure AI visibility over time
Track brand mentions, citations, associated capabilities and competitor visibility across relevant AI platforms as patterns rather than fixed ranking positions.
SEO reporting has traditionally focused on metrics such as keyword rankings, impressions and organic sessions which still remain useful. But AI introduces another dimension of measuring coverage and mentions (not just click-throughs) from generative AI engines. For measurement, I would approach it two-fold.
Pharmaceutical marketers can begin building a representative set of questions relating to their most commercially important capabilities.
Example include:
“What should I look for when selecting a CDMO for biologics manufacturing?”
“Which companies provide commercial-scale spray drying services”
“What should I consider when transferring an injectable product to a CDMO?”
Run these questions across the AI/search environments relevant to your customers and record whether your brand appears, sourced/pages cited and the competitors mentioned.
Secondly, if you are conducting GEO/AEO activities and are committed to increasing visibility, you will need to utilise a specialist tool to monitor in addition. Specialist AI visibility platforms are also emerging to make this easier. Tools including Ahrefs Brand Radar, Semrush, Profound, Peec AI, Otterly and Scrunch can monitor brand mentions, citations and competitor visibility across AI-powered search and answer platforms.
Rather than checking individual prompts manually, pharmaceutical marketers can use these tools to establish a representative set of commercially important questions and monitor visibility over time. The objective shouldn't be to establish a single 'ChatGPT ranking', but to understand patterns: how frequently your organisation appears, which capabilities it is associated with, which pages and third-party sources are being cited, and where competitors are achieving visibility that you are not.
Over time, this can develop into an AI Share of Voice measurement alongside conventional organic search reporting.
However, don’t overreact to individual results. The latest academic review of GEO research describes generative visibility as a stochastic, multi-stage process and highlights substantial variability between systems and individual runs. GEO should therefore be measured as a pattern over time rather than treated like a single conventional ranking position.
The foundational GEO paper by a group of researchers reported that optimisation methods could improve source visibility by up to 40% within the experimental generative-engine environment. However, there is an important qualification.
A 2026 critical review of 45 GEO studies concluded that the original result is valid **within its experimental setting**, but that it was conditional on a source already being present within a fixed context. It therefore does not establish that implementing those techniques produces a 40% increase in organic discoverability across live AI platforms. The same review concluded that, across the studies examined, no technique had yet demonstrated a stable, longitudinal, cross-platform causal effect on organic discoverability or downstream behaviour.
That distinction matters. GEO is a young discipline. There are useful signals emerging, but marketers should distinguish between what we know, what the evidence suggests and what the marketing industry currently assumes.
AI is also changing what search visibility means
As AI-generated answers reduce the need to visit individual websites, marketers must evaluate visibility and influence alongside conventional rankings and traffic.
There is another reason pharmaceutical marketers should pay attention to this shift in how users are searching online. Search visibility may no longer translate into website traffic in quite the same way.
Pew Research Center analysed browsing behaviour from 900 US adults and a dataset containing 68,879 unique Google searches. When users encountered a Google AI summary, they clicked a traditional search result in 8% of visits. When an AI summary was absent, users clicked a traditional result in 15% of visits. Links within the AI summary itself were clicked in just 1% of visits where an AI summary appeared.
There are limitations to this research. It relates to Google searches from US users during a defined period in 2025, rather than specifically to pharmaceutical B2B buying behaviour. Nevertheless, it demonstrates an important shift. A company could influence a potential customer’s research without necessarily receiving a website visit at that exact moment. That means search reporting may need to look beyond GA4 and conventional reporting and look deeper at the journey from AI mention to visit, rather than search rank to click.
Wrapping up: The opportunity for pharmaceutical manufacturers
Manufacturers can improve their AI visibility by making their capabilities, evidence, technical knowledge and specialist expertise clearer and more accessible online.
There is understandable anxiety about how AI will affect organic search. Trust me, I feel it. But pharmaceutical manufacturers may also have an advantage. The industry possesses enormous quantities of exactly the type of information that can make a website genuinely useful and authoritative. The problem often isn’t that pharmaceutical companies lack expertise. It’s that their websites don’t expose enough of it.
That is where I believe the biggest opportunity lies. Don’t approach GEO by asking how you can manipulate an AI system into mentioning your company.
Ask a better question: Does our website provide the clearest, most useful and best-evidenced representation of our expertise that it possibly can? Herein lies the new set of optimisations if AI visibility is the goal: 1. Make your capabilities explicit, 2. Replace vague claims with evidence, 3. Connect capabilities with facilities, 4. Connect technical information with commercial services, 5. Bring expertise out of PDFs. 6. Make your scientists visible, 7. Answer the questions customers genuinely ask and 8. Build your reputation beyond your own domain.
And always ensure the technical SEO foundations allow all of that information to be discovered. SEO, AEO and GEO may have different names. But for pharmaceutical marketers, who want awareness, website visitors and leads, the objective is increasingly the same: Make it as easy as possible for customers, search engines and AI systems to understand who you are, what you do, what you know, and why your organisation should be considered a credible answer.
-
Generative Engine Optimisation (GEO) is the process of improving the likelihood that a company, brand or its content is visible, referenced or cited within responses generated by AI platforms such as ChatGPT and other generative search experiences. For pharmaceutical manufacturers, this means making it easier for AI systems to understand your capabilities, technologies, facilities, expertise and supporting evidence.
-
SEO focuses on improving visibility within traditional search engine results. AEO focuses on making information easier for search and AI systems to understand and use when answering questions. GEO focuses more specifically on visibility and influence within AI-generated responses. There is considerable overlap between all three. In particular, strong SEO foundations remain important for AI visibility.
-
No. GEO should be viewed as an extension of search optimisation rather than a replacement for SEO. Google has confirmed that its existing SEO principles remain relevant to its generative search experiences. Websites still need to be crawlable, indexable, well structured and populated with useful, accessible content.
-
Start by making your company's expertise as explicit as possible. Important capability pages should clearly communicate what you manufacture, the modalities and dosage forms supported, development stages, manufacturing scale, technologies, facilities, experience and supporting evidence. Technical SEO, clear website architecture, strong internal linking, useful technical content, visible subject-matter experts and authoritative third-party mentions should form part of the wider strategy.
-
Content should primarily be created because it is useful to prospective customers rather than specifically for AI. For pharmaceutical manufacturers, particularly valuable content can include detailed capability and facility pages, technical articles, application note summaries, case studies, FAQs, manufacturing data, technology information and content answering questions that regularly arise during supplier evaluation. Where possible, support claims with specific facts, technical evidence and first-hand expertise.
-
Where appropriate, yes. Pharmaceutical companies often hold valuable expertise within application notes, scientific posters, whitepapers, presentations and technical brochures. PDFs can remain useful downloadable assets, but important information should not necessarily exist only within them. Publishing key findings and technical information as accessible HTML content can make that expertise easier for customers, search engines and AI systems to discover and understand.
