There are both large and small websites on the web, and both can have a need for SEO. But working with a large website requires a different way of thinking. This is where concepts such as Enterprise SEO and large-scale SEO become important.
The same technical foundation is also becoming increasingly important for visibility beyond traditional search. If search engines and AI-driven search experiences are expected to discover, understand and surface content from a large website, the underlying technical structure needs to work first.
In this article, I’ll look at what large-scale SEO actually means and what changes when you work with SEO across tens of thousands, hundreds of thousands or even millions of URLs.
What is large-scale SEO?
There are many differences between working with a small website with only a limited number of URLs and working with a website containing tens of thousands, hundreds of thousands or even millions of URLs. The differences are both operational and strategic.
On a small website, you can often go through pages one by one and optimise them individually. On a large website with thousands of different pages, this is no longer sustainable. It would simply take too much time, and in many cases it would not even be worth doing.
Large websites also tend to involve people from several different departments, which means that even relatively simple SEO changes can turn into larger processes involving multiple stakeholders.
A good example of large-scale SEO is an e-commerce website with hundreds of thousands of product pages or a global website with separate websites targeting their own markets. It is not realistic to optimise every product page individually. By the time you have finished, if you ever finish, many of those products may already have disappeared from the assortment.
Examples of large-scale SEO
Instead of making small SEO adjustments here and there, large-scale SEO is about making changes that affect significant parts of the website at once.
For example:
- Creating a page title template using attributes from the page content that affects thousands of product pages at the same time.
- Updating ALT text in the DAM (Digital Asset Management system) by generating alt texts at scale with AI.
- Making a recommendation that improves loading performance across the entire website.
- Specifying an algorithm for developers that generates an internal linking block across all pages of a certain content type based on the most popular pages in that content type.
The important difference is that the optimisation is built into the system rather than applied manually to individual pages.
This becomes even more relevant as search expands into AI-driven experiences. You cannot realistically optimise hundreds of thousands of pages individually for every new search interface. The scalable approach is to make sure the website itself provides a strong technical foundation: accessible content, clear internal relationships, consistent templates and pages that machines can reliably discover and understand.
Large-scale SEO actions and recommendations
1. Prioritise scalable SEO over small adjustments
Large-scale SEO is primarily about scalable improvements rather than one-off changes that affect a single page.
Recommendations should therefore be designed so that they can affect multiple pages or entire segments of the website. A relatively small change to a template, component or underlying system can sometimes affect hundreds of thousands of URLs.
This also means that prioritisation becomes extremely important. On a large website, it is rarely possible or useful to fix everything.
2. Monitoring
Monitoring is important for any website, but on very large websites you need to go deeper.
You need to understand how search engine bots are crawling the site, whether important sections are being reached and whether different parts of the website are being indexed as expected. You do not want an entire product segment, for example, to be overlooked by search engine crawlers without anyone noticing.
Log file analysis, verifying that bots can reach all important sections of the website and monitoring the indexing of content across different topic clusters become particularly important when working with Enterprise SEO.
And this should come as no surprise, it is no longer only about ranking in Google Search. If important content cannot be reliably discovered, rendered or understood by machines, it also has a weaker foundation for being surfaced in AI-driven search. AI visibility does not remove the need for technical SEO. It makes the technical foundation more important.
3. Segment the website into smaller parts
Optimising a large website can be challenging not only because of the amount of content, but also because of the number of stakeholders involved.
Managing stakeholders can become just as important as choosing the right SEO strategy or more important than that. You may need a separate strategy simply for getting approval for the changes you want to implement and even if you are successful, other might not see the benefit of your recommendation.
To make both the work and the stakeholder dialogue more manageable, the website can be divided into logical segments. These might be based on site categories, content types, markets, business areas or stakeholder ownership.
Once the website has been segmented, it becomes much easier to identify problems, compare performance and prioritise which areas to work on.
4. Granular reporting
Reporting is always important in SEO because it shows stakeholders how the website is performing in organic search. In Enterprise SEO, reporting becomes even more important because there are more stakeholders involved and because aggregated numbers can hide problems within individual parts of a large website.
A site might appear stable overall while an important product category, market or content type is losing visibility.
Granular reporting makes these changes easier to detect and also makes ongoing SEO work easier to prioritise. A well-configured reporting setup that can handle a large website is therefore essential when working with large-scale SEO.
Conclusion
Large-scale SEO is less about optimizing individual pages and more about building systems that make entire sections of a website easier to crawl, understand and improve.
That technical foundation matters just as much for AI-driven search as it does for traditional search. If machines cannot reliably access, interpret and connect your content, visibility becomes harder regardless of whether the interface is Google Search or an AI-generated answer.
In that sense, AI does not replace technical SEO. It raises the value of getting the fundamentals right.