SEO & GEO for SaaS

A corporate site has ten pages and one promise. A SaaS has product pages, documentation, a blog, comparisons, use cases and integrations, and each block plays a different game. The usual mistake is treating all of it the same way. And if your sale is consultative and decided by a committee, the approach changes again: we cover that in B2B SEO and GEO.

The demand is not where it looks either. Almost nobody searches for your product category. They search for the problem, for your competitor, or for alternatives to something they already use and dislike. That is the way in, and it is almost always long tail: low-volume searches with very high commercial intent.

And there is one asset only SaaS companies have: the documentation. It is usually the most honest and most cited content in the company, and it is almost always outside the SEO plan. We bring it in, with its own architecture, structured data and internal linking.

First, the demand map. What is searched around the problem you solve, what is searched around your competitors, and what someone asks right before trying a tool. That is where the plan comes from, not from a tidy keyword list: what gets grouped is search intent, and each group becomes a content cluster that builds topical authority around your problem.

Then product-led SEO: pages that show how to solve something with the product in front of you, not generic articles with a button at the end. That is what converts, and what AI can cite.

And the technical work across three layers: the marketing site, the documentation and the app. Crawling, indexing, crawl budget, Core Web Vitals, structured data and URL architecture. A growing SaaS piles up thousands of URLs that nobody is watching. It is the same work we do in SEO & GEO, applied to a product.

“Which tool would you recommend for this?” is now one of the most profitable questions there is, and it happens outside Google. The answer does not come from your website: it comes from what the internet says about you. That work is called GEO (generative engine optimization); when the focus is answering specific questions precisely it is called AEO (answer engine optimization), and when the target is Google's AI Overviews, AIO. Different labels for the same goal: being the source.

What weighs most for a model to cite you is brand mentions and authority as an entity, not the number of links. So GEO work includes things classic SEO does not: reviews, third-party comparisons, forums, public documentation and original data worth citing. On the technical side it is about making the model's job easy: well-defined entities, structured data, an llms.txt that says what to read, and content chunked so a retrieval system (RAG) can cite it in a single paragraph.

It is also where a mid-sized SaaS can beat a large one. Around 60% of the sources AI cites are not in Google's top 10, so the order of the SERP does not decide the answer. That is why we measure AI share of voice separately: how often you show up, and how often everyone else does, in the answers for your category.

Comparison pages convert better than almost anything else in SaaS, and they are usually done badly. When they are written so you always win, the reader can tell, and they leave feeling sold to.

Our rule is simple: say who each tool is better for, with verifiable facts, and never invent flaws in the other one. An honest comparison gets cited, gets linked and lasts for years. A rigged one lasts until someone reads it carefully.

A SaaS has families of pages that repeat with one variable inside: integrations, alternatives, comparisons, use cases by industry, templates. That is programmatic SEO: building the whole family from a template and a data source instead of writing each page by hand.

It is one of the most profitable levers a SaaS has, and the one that has sunk the most domains. If the pages come out empty — the same sentence with the name swapped — Google treats them as low-value content, and the problem does not stay on those URLs: it drags the rest of the site down with it. The rule is simple: every generated page has to carry something only that page can carry.

We build the template, the data model, the internal linking between families and the quality gate that decides what ships and what does not. And it goes out in batches, checking indexing and performance on each batch before releasing the next.

It is the question we get asked most, and the one plenty of people now put to an AI before they email anyone. It is worth looking at how the models answer it: when you ask one to recommend an agency, the sources it cites are almost never the agencies' own websites. They are third-party studies, press releases, roundups in trade media, forum threads and LinkedIn profiles. We track this ourselves, and it comes out the same way every month.

That tells you two things. First, that to get named you have to exist outside your own website — which is as true for your SaaS as it is for us. Second, that a good share of those lists are written by the agencies themselves or lifted from a press release, so a ranking is not a reference.

These are the questions we would ask. They work on any agency, and we answer them the same way if you put them to us.

In SaaS, traffic is a weak signal. What matters is which pages bring signups and which queries bring someone who is already deciding. We separate that from day one.

In parallel we track the AI side: we ask the models what your buyer would ask, in the languages that matter to you, and record whether you appear, which sources they cite you from, and who you are up against in that answer. If you also sell in several countries, that crosses over with international SEO, because every language returns a different answer.