Someone asked ChatGPT for a recommendation, and your name was not in the answer
This is the moment that makes GEO real for a lot of South African business owners: a prospective client asks a generative AI assistant to recommend a supplier in your category, and the assistant confidently names two or three competitors — not because those competitors paid for placement, but because the model has absorbed more consistent, positive, citable information about them from across the web than it has about you.
Generative Engine Optimisation is the discipline of closing that gap. It shares real DNA with SEO and with Answer Engine Optimisation — covered in our companion pieces on AEO vs SEO and on Google AI Overviews specifically — but it operates on a meaningfully different mechanism. A Google AI Overview retrieves and summarises live web content in response to a specific query. A general-purpose chat assistant answering "who is the best X in South Africa" is drawing substantially on patterns learned during training, plus, in some cases, a live web search layered on top. That difference changes where the real GEO work actually happens.
This guide focuses specifically on that broader, assistant-spanning discipline: what genuinely moves the needle on how favourably and accurately generative AI systems describe your business, and what is simply a rebranded SEO invoice with "AI" added to the name.
Where generative assistants actually get their information
| Source type | What it means for visibility |
|---|---|
| Training data (historical web crawl) | Content, reviews and mentions that existed and were indexed before the model’s training cutoff shape its baseline "opinion" of who is credible in a category |
| Live web retrieval (where supported) | Some assistants search the live web for current queries, behaving more like an AEO problem — current page structure and freshness matter here |
| Third-party aggregated sources | Review platforms, directories, forums and "best of" articles are frequently over-represented in what a model has learned to trust |
| Direct brand content alone | Your own website is one voice among many — rarely enough on its own to shift how a model describes your category leaders |
Off-site reputation is the biggest lever, and the one most businesses ignore
Being named favourably and specifically on third-party platforms — genuine customer reviews, industry directories, "best agencies in [city]" roundup articles, forum discussions where real users recommend you by name — is very likely a stronger long-term GEO lever than anything you can change on your own website alone. These are exactly the kind of independent, aggregated sources that both training data and live retrieval tend to weight heavily.
This does not mean chasing every directory listing indiscriminately. Prioritise platforms your actual customers use and trust, and prioritise being included in genuinely earned roundup content — guest contributions, expert commentary, credible case narratives — over paid placements that read as advertising rather than independent recommendation.
Consistency across all of these sources matters as much as volume. A business described with the same core facts, specialisms and service area everywhere is easier for a model to represent confidently than one surrounded by conflicting, outdated or vague descriptions scattered across the web.
On-site work that still matters, as a complementary layer
- Keep an accurate, specific About page stating clearly who you are, what you do, and where you operate
- Maintain Organization and LocalBusiness schema with current, consistent facts
- Publish genuinely original frameworks, checklists and positions — generic content gives a model nothing distinctive to cite
- Keep pricing logic, service areas and specialisms stated plainly and kept current across every page that mentions them
- Consider a public llms.txt file as an emerging, low-cost signal of what you consider your most authoritative content, while treating it as experimental rather than essential
None of this replaces off-site reputation work — it simply ensures that when a model or a live retrieval layer does look at your own site directly, it finds a clear, consistent, specific picture rather than a vague or contradictory one.
Prioritise this, be sceptical of that
| Prioritise | Be sceptical of |
|---|---|
| Genuine reviews across platforms your customers actually use | Bulk-purchased or incentivised reviews — policy violations that damage trust everywhere, not just one platform |
| Earned mentions in credible industry roundups and directories | Paid "guaranteed AI visibility" placements with no transparency on method |
| Consistent, specific facts about your business across the web | A single-page "AI optimisation" add-on with no connection to your wider reputation work |
| Original, specific content a model or human would actually want to cite | Generic AI-written filler content produced purely for volume |
Measuring GEO honestly, because direct measurement barely exists
There is no reliable, universal dashboard showing "GEO performance" the way Search Console shows organic SEO performance — be wary of any tool or vendor claiming otherwise with total confidence. What is available are honest proxies: branded search volume (are more people searching your business name directly, possibly after hearing it from an AI assistant), direct website traffic with no obvious referral source, and manual spot-checks where you periodically ask several assistants the same category question and note who gets mentioned.
Manual spot-checking is unglamorous but genuinely useful. Once a quarter, ask two or three major assistants a handful of realistic buyer questions in your category, from a fresh session each time, and record who gets named. Trends over several quarters tell you more than any single answer, since these systems can vary noticeably between sessions and updates.
Treat GEO as a slow-compounding reputation investment rather than a campaign with a defined end date. The businesses most consistently named by generative assistants tend to be the ones with the deepest, most consistent public reputation over years — not the ones that ran a single optimisation sprint.
What not to do
A realistic South African starting point, not a global enterprise playbook
Most GEO advice online is written for large brands with dedicated PR teams and years of accumulated coverage. A South African SME does not need that scale to start closing the gap — it needs a focused, honest version of the same work, sized to its actual category and budget.
Start with the review platforms and directories your specific customers actually check before buying, not a generic global list. Fix any inconsistent facts — old addresses, discontinued services, outdated pricing language — across the ones that matter most. Then look for two or three realistic opportunities to be mentioned in genuine third-party content: an industry association listing, a credible guest contribution, a case study a client is willing to be named in. That short list, executed consistently over a year, moves the needle more than a scattershot attempt to be everywhere at once.
The Nexus take
GEO rewards the business that was already worth recommending, consistently, across enough independent sources. There is no shortcut that substitutes for actually being good and being talked about.
Nexus GEO principle
A worked example: what a focused reputation audit actually finds
A mid-sized accounting firm ran a simple two-hour audit across the platforms its actual clients use: Google Business Profile, two accounting-specific directories, a regional business chamber listing, and LinkedIn. The exercise found three separate versions of the firm's service area — one listing said "Johannesburg only," another said "Gauteng-wide," and the website itself said "nationwide, remote-friendly." None of these were dramatic errors individually, but together they gave any system trying to describe the firm three conflicting facts to choose from.
Fixing this cost nothing beyond the two hours of the audit itself and a handful of profile edits, but it removed exactly the kind of inconsistency that makes a model — or a human reader comparing tabs — less confident about which version of the business to trust. The firm also found one outdated directory listing from a previous office address, requested a correction, and identified two credible local business associations it qualified for but had never joined.
Run the same exercise on your own business this month: list every platform where your business is described, check the core facts against each other, and fix the mismatches before pursuing any new mentions. Consistency across what already exists is a faster, cheaper win than chasing additional coverage on top of an inconsistent foundation.
A starting list of places worth checking
- Google Business Profile and Bing Places
- Industry-specific directories relevant to your category (legal, medical, trade, professional bodies)
- LinkedIn company page and any team members’ individual profiles mentioning the business
- Review platforms your actual customers use — not a generic global list
- Any previous "best of" or roundup articles that may already mention your business with outdated facts
What to do next
Ask two or three AI assistants your own category question this week, in a fresh session, and note honestly who gets named and who does not. That single test tells you more about your current GEO position than any tool available today.
Audit your presence across the review platforms and directories your customers actually use, and prioritise consistency of facts over volume of listings.
Pair this guide with our companion pieces on AEO vs SEO and on Google AI Overviews for the fuller picture across all three related disciplines.
