If you run a B2B business in South Africa, your buyers are already searching inside Claude, ChatGPT and Microsoft Copilot. Not exclusively Google. Not in the way they used to.
These three LLMs have quietly become the default research tools for South African business users. Sales teams are using them to qualify suppliers. Procurement is using them to shortlist vendors. Marketing leads are using them to scope agencies. The shift in behaviour has happened, and most B2B websites have not caught up.
This is what Answer Engine Optimisation (AEO), also called Generative Engine Optimisation (GEO) sets out to fix. But to understand how AEO actually works, you have to understand something most articles on the topic miss: LLMs do not answer every question the same way. They change behaviour based on where the buyer is in the funnel.
The funnel changes how the LLM responds
Here is the distinction that matters.
When a user asks a top-of-funnel or early middle-of-funnel question, the LLM is in research mode. It pulls primarily from its training data. Things like "what is account-based marketing", "how does a CRM system work", and "explain RevOps" - the LLM is happy to answer these directly from what it already knows. Some models lean on training data more aggressively than others, but the pattern holds.
The further down the funnel you go, the more the LLM's behaviour shifts. Bottom-of-funnel and lower middle-of-funnel queries are where LLMs start to suggest specific providers. These types of queries trigger the LLMs' web search tools to find businesses that can actually solve the user's problem.
A query like "Who are the best AEO agencies in South Africa?" is not a research query. It is a buying query. The LLM treats it differently. It goes to the live web, evaluates sources, and surfaces providers it can cite as credible candidates.
This is the moment that matters for B2B revenue. And this is where most South African businesses are completely invisible.
How does your business stack up in the training data for Claude, ChatGPT and Google Gemini? Try our MO Agency’s AI Visibility Audit tool. It will detail how each LLM model’s training data presents your business, and where you need to improve.
Why training data alone will not save you
The majority of AEO advice fixates on getting your brand into LLM training data. That is useful for top-of-funnel mentions, but training data is a slow, indirect game. New training cycles only happen periodically. Your brand has to be cited often enough across the open web for it to register. And even then, you are competing with global brands that have decades of citation density behind them.
For South African B2B businesses, the bigger opportunity is the web search trigger. When the LLM goes looking for "the best AEO agencies in South Africa" or “who are the best property managers in South Africa” or "top divorce lawyers in Johannesburg", it is reading live pages. That is something you can directly influence.
What makes a page AI-readable
When LLMs trigger a web search, they are not browsing like a human. They are crawling pages, parsing the content into structured tokens, and assessing whether the page answers the question clearly enough to cite. The pages that win share a few characteristics.
These pages answer the question early and directly. They use a clear structural hierarchy that makes structured parsing easy. They include the kind of factual scaffolding LLMs trust: dates, locations, named clients, specific deliverables, and measurable claims. They are technically clean, with fast load times and minimal rendering complexity. They are linked to from sources that LLMs already trust.
Most B2B websites in South Africa fail on at least three of these. Pages bury the answer. Headings are decorative rather than structural. Claims are vague. Technical performance is poor. There is no entity-level consistency across the site.
How to approach AEO
We’ve been working on this for a while now, both for our own visibility and across our client base. The approach comes down to three areas.
First, tracking. We run AEO/GEO tools like Profound and HubSpot AEO, in addition to a few custom toolings to measure how businesses appear in LLM responses across prompt sets that map to their funnel. You cannot fix what you cannot see, and most businesses still can't put a metric on their AI visibility.
Second, content architecture. Restructure pages so that the answer is at the top, the supporting evidence is below, and the technical signals make the page easy to parse and trust. This is closer to technical SEO than to traditional content marketing, but with a different audience in mind: the LLM, not the human reader alone.
Third, the platform. AEO rewards fast, lightweight websites with low compute overhead. The same reason LLMs expect the answer at the top of the page is the reason they expect the page itself to load fast and parse cleanly: AI agents have compute budgets, and if your pages are heavy, the agent will not go deep enough to understand the full context of what you offer. It will read the surface, give up, and move on.
The fix is either very agile web development or a tool like getmd.ai, which renders your pages into clean Markdown and generates an llms.txt file for your site. That lets AI agents navigate your website and content with very low compute overhead, so they can crawl more of it, more often, and cite it more accurately. It’s the same principle as the answer-at-the-top rule, just applied to the speed and architecture of the site rather than the content of the page.
The takeaway for B2B leaders
If your buyers are using ChatGPT, Claude and Copilot to shortlist providers, and you are not measuring how you appear in those responses, you are running blind on what is now a core part of your demand funnel.
The shift is not coming. It has happened. The B2B businesses that move first will lock in citation density and entity recognition that becomes very hard to displace later. The ones who wait will spend the next two years trying to catch up to the brands that have now taken funnel insight seriously.
AEO leverages good SEO principles, but it is not simply rebadged SEO. The funnel logic is different. The success metrics are different. The technical playbook is different. But the commercial outcome is the same: when your buyer is ready to buy, you want to be the answer.
