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AI Search Optimisation Agency — South Africa

AI Visibility on ChatGPT, Claude & Perplexity — Why Choose Us

ChatGPT. Google AI Overviews. Perplexity. Gemini. Grok. Claude. The next wave of search doesn't return ten blue links — it returns one answer. We make sure that answer mentions you.

● Author: Jaco Smit, GEO Researcher & Founder ● Updated: June 2026 ● 18,400-word proprietary research article ● Based on 100,000+ AI query dataset
48%
of Google searches now trigger an AI Overview (Feb 2026)
62.6%
of AI-referred B2B traffic comes from ChatGPT
29%
est. organic traffic lost to AI Overviews on affected queries
+120%
growth in SA AI search adoption over 24 months
100K
AI queries analysed in our proprietary visibility dataset

Search Is Being Rebuilt From Scratch

For twenty years, search engine optimisation meant ranking on page one of Google. Build authority, earn links, produce content — and ten blue links reward you with traffic. The model was predictable, measurable, and the entire discipline of SEO was built around it.

That model is ending. Not gradually. Rapidly.

Google's AI Overviews now appear on 48% of all searches as of February 2026, up from 31% in February 2025. When an AI Overview appears, it absorbs the user's attention and typically answers their question without a click. Studies tracking click-through rates on queries with AI Overviews show organic CTR dropping 35–45% compared to the same queries without one.

Meanwhile, a separate category of AI search has emerged. ChatGPT reached 400 million weekly active users in early 2025 and continues growing. Perplexity processes over 100 million queries per day. Google's own Gemini is integrated directly into Android, Chrome, and Workspace. These systems are not search engines in the traditional sense — they are answer engines. They don't send users to your website. They extract value from content across the web, synthesise it, and deliver a response.

For brands, the implication is severe. If AI systems don't know your brand exists, or don't trust your content enough to cite it, you are invisible in the next generation of search — no matter how well you rank on traditional Google.

Generative Engine Optimisation (GEO) is the practice of making your brand visible, trusted, and citable by AI systems. It's what we do.

AI Overview Coverage on Google
Percentage of queries triggering an AI Overview, 2024–2026. Source: GEO internal tracking + industry data.
0% 25% 50% 75% 5% 31% 48% Feb 24 Oct 24 Jun 25 Feb 26
South Africa: AI Search Adoption Rate
% of South African internet users actively using AI search tools. Calculated from StatsSA internet user base (~44.1M) and usage surveys.
H1 2024 (est.)
10.5%
Q4 2024
15.8%
Q2 2025
19.2%
Q1 2026
23.1%

+120% growth in 24 months. Based on ~44.1M SA internet users (ITWeb / StatsSA 2025), this equates to approximately 10.2 million South Africans now regularly using AI search tools.

What Generative Optimisation Does

We are South Africa's dedicated Generative Engine Optimisation agency. Our work is research-first: we track, measure, and engineer how AI systems perceive, cite, and recommend brands — and we build the authority structures that make citation happen at scale.

This isn't content marketing dressed up in new language. GEO requires a fundamentally different approach to how authority is built and measured. Traditional SEO optimises for crawlers. GEO optimises for language models — and language models evaluate authority differently.

Our five core service areas:

AI Visibility Auditing
We baseline where your brand appears (or doesn't) across ChatGPT, Perplexity, Gemini, Grok, Claude and Google AI Overviews. We track citation frequency, sentiment, accuracy of AI responses, and competitive share of voice in your category.
Entity Authority Engineering
AI systems build mental models of entities — brands, people, places, concepts. We construct and reinforce the entity signals (Wikipedia presence, Wikidata entries, structured data, consistent NAP, brand mentions) that tell AI systems your brand is real and trustworthy.
Citation Architecture
We identify the sources AI systems cite in your category, map the citation graph, and position your content as a reference point that LLMs turn to when answering queries about your industry, product, or service area.
GEO Content Strategy
Content written for AI citation has specific structural requirements: original data, quotable statistics, clear factual claims, expert authorship signals, and E-E-A-T depth. We architect content for AI consumption, not just human readability.
Competitive Intelligence
We reverse-engineer how competitors earn AI citations, identify gaps in their authority structures, and build strategies that outperform them in AI responses — even when they outrank you on traditional Google.
GEO Knowledge Graph Construction
We build structured knowledge graph entries for your brand, people, products, and categories — the same structures that search engines and AI systems use to understand what things are and how they relate to each other.
The Core Difference

Traditional SEO gets you on page one of Google. GEO gets you into the one answer AI systems give. We don't see these as competing — we see GEO as the next layer of authority that makes traditional SEO stronger. But if you ignore GEO, you're optimising for a search model that's already being replaced.

How AI Systems Decide What to Cite

Ranking on Google and being cited by an AI system require completely different things. Understanding why matters, because the mistake most agencies make is treating GEO as a content exercise rather than an authority and entity exercise.

When a language model generates a response, it draws on training data and, in systems with retrieval (Perplexity, GPT-4o with browsing, Gemini with Google Search integration), live web results. The factors that influence citation are different from traditional ranking signals.

Factor Traditional SEO Weight GEO / AI Citation Weight Implication
Backlinks Very High Moderate Links still matter for authority signals AI systems pick up, but citation graph position matters more
Entity Recognition Low-Medium Critical If the AI doesn't have a clear entity understanding of your brand, it won't cite you confidently
Original Research / Data Medium Very High AI systems preferentially cite original statistics and findings they can quote verbatim
Publisher Authority High High AI systems trust established publishers — this is why domain authority still matters for GEO
Structured Data / Schema Medium High Structured data helps AI systems parse entity attributes, product facts, and author credentials
Citation by Other Sources Indirect (via links) Very High Being cited by sources the AI already trusts is the fastest path to AI citation
Keyword Density Medium Low LLMs understand concepts semantically; keyword stuffing has no effect and may harm credibility
Page Load Speed High Negligible AI systems don't experience page load; speed matters for Google crawling but not LLM training

The five layers of AI citation authority — as identified through our research — are: Entity recognition (does the AI know this brand is a real, distinct thing?), Source trust (does the AI's training include reputable sources that mention this brand?), Content citability (does the brand publish data, research, and facts that AI systems can directly quote?), Citation graph position (is the brand cited by sources the AI already trusts?), and Recency and freshness signals (for retrieval-augmented AI systems, is the brand producing current, indexable content?). We measure and engineer all five.

Research Infrastructure Nobody Else Has Built

Most agencies claiming to offer GEO services are applying traditional content marketing principles and calling it AI optimisation. We don't. Everything we do is grounded in a research infrastructure that took two years and significant investment to build — and that we believe is unique in Africa.

The Proprietary Database

We maintain a private database of AI citation patterns that we do not share publicly. This database contains over 100,000 AI query observations, tracking which sources are cited, how frequently, in what context, and with what associated sentiment across ChatGPT, Perplexity, Gemini, and Google AI Overviews. We've been running queries and logging results since early 2024. No agency in South Africa has anything comparable.

This dataset allows us to answer questions that are otherwise unanswerable: Which South African publishers does ChatGPT trust most? Which query categories trigger Perplexity's retrieval mode? What structural patterns in content correlate with increased AI citation rates? We know, because we measured it.

The Split-Testing Network

We operate a controlled network of test websites across multiple subdomain environments. When we want to understand whether a specific signal — a schema type, an entity mention, a citation pattern — affects AI visibility, we test it in isolation. We don't theorise about what works. We build controlled experiments, run them for 60–90 days, and measure the result.

An Example Test Run in 2025

We isolated the effect of Wikidata entity entries on ChatGPT citation rates. Across 12 matched test entities — identical content, identical citation graphs, one group with Wikidata entries and one without — entities with complete Wikidata profiles were cited 2.3× more frequently in queries where the entity was a plausible answer. The Wikidata group also showed broader entity recognition across more query types.

Our Research Methodologies

Citation Graph Reverse Engineering
We map which sources AI systems cite in a given category, then trace the citation lineage backwards. This reveals the upstream authority nodes — the sources you need to be cited by to enter the AI's trusted citation network.
Synthetic Authority Laboratories
Controlled environments where we create test entities with identical authority profiles but isolated variables. We use these to measure the causal effect of specific signals on AI citation rates.
Entity Injection Testing
We test how quickly AI systems can be updated to recognise a new entity, and which signal combinations produce the fastest recognition. This informs our onboarding strategy for new clients.
Memory Persistence Testing
We track how long entities persist in AI citations after active signal-building stops. Our data shows citation half-life varies significantly between engines — critical for maintenance planning.
AI Citation Farming Networks
Unlike traditional link farming (which is manipulative), our citation farming approach works by placing verifiable, accurate information about a client in the specific trusted sources that AI systems reference — earning genuine citations through real editorial relationships.
100K Query Space Mapping
For each client engagement, we map the query space — the full universe of questions AI users ask that are related to the client's category. We then identify where citations already exist, where they're absent, and which queries offer the best citation opportunity.
Trust Signal Attribution
We run multivariate analysis on our citation database to attribute which trust signals correlate most strongly with citation in each engine. The answer varies by engine — what works on Perplexity is not identical to what works on ChatGPT.
Multi-Agent Consensus Optimisation
When multiple AI systems are asked the same question, their answers often differ. We identify where a client receives consensus citations (mentioned by multiple systems) versus engine-specific citations — and we optimise for consensus.
GEO Digital Twin of the Internet
We maintain a continuously updated model of which web properties, publications, and sources each major AI engine appears to weight most heavily — effectively a map of the internet from each AI's perspective.
Influence Path Analysis
For a given query, we trace the influence path: which sources inform the AI's response, which sources informed those sources, and how many degrees of separation there are between a client and the AI's authoritative sources.
AI Citation Prediction Engine
Using our citation database, we've built a predictive model that estimates the probability of AI citation for a given entity, given its current authority signals. This guides investment decisions: where to spend budget for maximum citation return.
Authority Gap Decomposition
We break competitor authority into its component parts — entity authority, citation network position, content authority, trust signal coverage — and identify which gaps are easiest to close in 90 days versus which require longer campaigns.
Authority Arbitrage Mapping
We identify AI citation opportunities where the effort required to earn a citation is lower than its value warrants — typically in emerging query categories where AI systems haven't yet developed strong citation preferences.
Reality Signal Harvesting
AI systems increasingly weight "real world" signals — physical presence data, offline news coverage, regulatory registrations, verified reviews — more heavily than purely digital signals. We identify and amplify these for clients.
Competitive Simulation Engine
We model what would happen to a client's AI citation rates under various competitor actions, and pre-build defensive authority structures. We call this GEO War Gaming.
Authority Velocity Tracking
We measure how quickly authority signals accumulate and decay for different entity types in different engines. Velocity tracking tells us whether a campaign is on track before citation metrics themselves change — leading indicators, not lagging ones.

How We Approach Each AI Search Engine

There is no single GEO strategy that works equally across all AI systems. Each engine has a different architecture, a different training corpus weighting, and different retrieval behaviour. Our approach is engine-specific — built on what our 100,000-query dataset tells us about how each one actually works.

ChatGPT / GPT-4o
OpenAI · 400M weekly active users · 62.6% of AI-referred B2B traffic

How ChatGPT Builds Its World Model

GPT-4o's responses are informed by two sources: its training data (with a knowledge cutoff) and, when Browse is active, live web results via Bing. The key insight from our testing is that ChatGPT's training-data citations are remarkably stable — once a source is well-represented in training data, it tends to be cited consistently. This makes authority-building a long-term investment with durable returns.

For entity recognition specifically, our data shows ChatGPT requires a higher citation threshold than Perplexity before reliably recognising and citing a lesser-known entity. We've measured this at approximately 140–180 high-authority mentions before recognition becomes consistent across varied query phrasings.

Our ChatGPT GEO Strategy

Entity establishment: Wikipedia and Wikidata entries, structured data markup, and consistent brand mentions in high-authority publications. ChatGPT weights Wikipedia more heavily than any other engine in our testing.

Content positioning: Long-form, research-backed content on authoritative domains. ChatGPT consistently cites content that contains original statistics, named studies, and expert quotes — we produce this content and place it strategically.

Browse optimisation: For queries where ChatGPT uses its Browse function, we optimise for Bing indexation and high-quality meta descriptions, as Browse-mode citations appear to weight these signals similarly to traditional SEO.

ChatGPT: SA Brand Citation Frequency by Source Type (Internal Dataset)
Average citations per 1,000 queries in SA-related queries, by source type. n=28,400 queries, Jan–May 2026.
News24 / TimesLive
78%
Wikipedia (SA topics)
71%
IOL / Independent Media
54%
Stats SA / Government
47%
BusinessTech / Moneyweb
39%
University publications
28%
SME / Brand websites
7%

The 7% citation rate for SME and brand websites underlines the challenge: AI systems overwhelmingly prefer third-party, editorially independent sources. GEO is largely about getting your brand mentioned in the top tiers.

Google AI Overviews
Google · 48% of queries · Directly replaces organic traffic

How Google AI Overviews Work

AI Overviews pull from Google's index in real time, making them more amenable to traditional SEO signals than pure LLMs — but with important differences. Our testing shows AI Overview citations skew heavily towards pages with structured content (headers, tables, numbered lists), authoritative domain signals, and crucially, clear, quotable factual claims.

Pages that rank on page one do not automatically appear in AI Overviews. We've tracked hundreds of cases where a page ranking #2 on a SERP was ignored by the AI Overview, which instead cited a page ranking #8 — because the #8 page's content was structured as answers rather than prose.

Our Google AI Overview Strategy

Answer architecture: Content structured explicitly around questions, with clear answer-first paragraphs that AI can extract without context. We call this the "quotable paragraph" format.

Schema and structured data: FAQ schema, HowTo schema, and Article schema all increase AI Overview inclusion probability. We implement comprehensively.

E-E-A-T signalling: Author credentials, publication dates, cited sources, and institutional affiliations. AI Overviews heavily weight content that signals first-hand experience and expertise. We build all of this into content architecture.

Our testing shows that pages optimised with our AI Overview framework appear in AI Overviews at 3.4× the rate of standard SEO-optimised pages in the same query category.

Perplexity AI
100M+ daily queries · 7.3% B2B AI referral share · Retrieval-first architecture

Perplexity's Retrieval Architecture

Perplexity is primarily a retrieval-augmented system — it searches the web in real time and synthesises results. This makes it behave more like a search engine than a pure LLM, and it means freshness matters significantly. Our data shows Perplexity strongly preferences content published or updated within the last 90 days for most query categories.

Perplexity also shows the widest citation diversity of any engine in our dataset — it's more likely than ChatGPT to cite smaller but topic-specific authoritative sources. This creates opportunities for brands that may not appear on Wikipedia.

Our Perplexity GEO Strategy

Content freshness: Regular publishing cadence with clear publication dates. Perplexity's crawler prioritises newly indexed content for fast-moving topics.

Citation magnet content: In-depth, topic-specific content that Perplexity's AI can cite as the authoritative source for a particular factual claim. We've found that articles containing three or more original statistics are cited at 2.1× the rate of articles without original data.

Source proliferation: Perplexity's 11% citation overlap with ChatGPT means its source set is largely independent. We build citation authority specifically for Perplexity's crawler preferences, which differ meaningfully from Google's.

Google Gemini
10.6% B2B AI referral share · Google Search integrated · Android default AI

Gemini's Dual Nature

Gemini operates in two contexts that require different optimisation approaches. As a standalone assistant, it behaves similarly to ChatGPT — drawing on training data with Google Search integration. Embedded in Google Search, it powers AI Overviews and has direct access to Google's full index.

Our testing shows Gemini places significantly more weight on Google's own authority signals than other engines — PageRank derivatives, Google Business Profile completeness, and Google Knowledge Graph entries all show stronger correlation with Gemini citation rates than with ChatGPT citation rates.

Our Gemini GEO Strategy

Google ecosystem integration: Complete, accurate Google Business Profile, Google Knowledge Panel claiming, and YouTube presence all feed Gemini's entity understanding. We optimise the full Google entity graph for clients, not just web pages.

Traditional SEO as GEO foundation: For Gemini more than any other engine, strong traditional SEO signals translate directly into GEO authority. We treat Gemini optimisation as the intersection of GEO and technical SEO.

Knowledge Graph entries: We pursue Google Knowledge Graph inclusion as a first-priority action for Gemini visibility — an entity with a Knowledge Panel is significantly more likely to be cited in Gemini responses.

Grok / xAI
Grok
Elon Musk's AI, with unique X/Twitter integration. Our strategy prioritises X presence, X posts from authoritative accounts, and mainstream news that's been heavily discussed on X. Grok weights real-time social signals more than any other engine.
Claude / Anthropic
Claude
18.5% of AI-referred B2B traffic. Claude is highly cautious about citations and strongly preferences established, editorially rigorous sources. Our strategy focuses on major publication placement and avoids low-authority shortcuts that may work on other engines.
Microsoft Copilot
Copilot
Powered by GPT-4 with Bing integration, Copilot is embedded in Microsoft 365 — meaning it surfaces answers in Outlook, Teams, and Word. Our strategy targets Bing indexation quality and entity presence in Microsoft's knowledge graph.
You.com
You.com & Others
Emerging AI search engines including You.com, Meta AI, and Apple Intelligence are tracked in our dataset. We monitor citation patterns across all emerging players — early positioning in new AI systems is often easier than fighting for position after patterns are established.

Studies We've Conducted — With Findings We Haven't Published Until Now

Research is the backbone of credible GEO. Below are five studies we've conducted using our proprietary dataset and methodology. Some findings confirm what the industry suspected. Others contradict the conventional wisdom entirely.

Study 01 · Published June 2026 · 24-Month Dataset
The South African Search Demand Shift: 24 Months of AI Impact on Organic Query Volume

We tracked query volume changes across 847 keywords in ten South African industry verticals from January 2024 to May 2026, cross-referencing Google Search Console data from client and partner accounts with Semrush and Ahrefs trend data to construct an aggregate picture of how AI search is changing query behaviour in the South African market.

SA Organic Click Loss: Informational vs. Transactional Queries
Average organic CTR change on queries with AI Overviews active, by query intent. Jan 2024 baseline vs. May 2026.
0% -10% -20% -30% -42% -31% -18% -9% Informational Commercial Transactional Navigational
  • Informational queries — "what is", "how to", "why does" — showed the steepest organic CTR decline: average -42% on queries where an AI Overview appeared, compared to the same query without one.
  • Transactional queries ("buy X", "X price", "X near me") showed the smallest decline — -18% — consistent with the hypothesis that users with purchase intent continue to click through rather than accept AI answers.
  • SA-specific query patterns show a lag of approximately 4–6 months behind US trends, suggesting strategies proven in the US market have predictive value for South Africa.
  • Verticals most impacted in SA: legal information (-53%), financial advice (-48%), medical/health (-44%), how-to guides (-41%). Verticals least impacted: product purchase (-12%), local services (-14%), news (-8%).
  • Our calculated aggregate organic traffic loss across all query types, weighted by volume, is approximately 29.3% — derived from the 48% AI Overview coverage rate multiplied by the average 61% CTR reduction on affected queries.
Study 02 · Ongoing · 100,000+ Query Dataset
The 100,000 AI Query Study: Citation Patterns Across Engines

Beginning in January 2024, we began systematically querying the major AI search engines with a structured set of prompts across 200+ categories, logging which sources were cited, how frequently, and with what context. The dataset now exceeds 100,000 individual query observations. This is the largest AI citation dataset we're aware of being maintained in South Africa.

Citation Overlap Between AI Engines (Internal Dataset)
% of citations that appear in both engines for equivalent queries. Based on 34,000 paired query observations.
ChatGPT Perplexity Gemini Grok Perplexity Gemini Grok 11% 28% 19% 23% 14% 31% N/A N/A N/A Low overlap (<15%) Moderate (15–25%) High (>25%)
  • Only 11% of citations overlap between ChatGPT and Perplexity for equivalent queries — they draw on fundamentally different source sets, meaning you must optimise for each engine separately.
  • Gemini and Grok show the highest citation overlap (31%) — both draw heavily on Google's index and mainstream media respectively, creating a shared citation pool.
  • The average citation overlap across all engine pairs is 21% — meaning 79% of a given engine's citation set is unique to that engine. Multi-engine GEO is not optional for brands that want comprehensive AI visibility.
  • Sources that achieve cross-engine citation (appearing across three or more engines for equivalent queries) share three characteristics: strong Wikipedia presence, high domain authority (>70 DR), and recent original data publication.
Study 03 · Completed Q1 2026 · Controlled Experiment
Entity Recognition Threshold Study: How Many Mentions Does It Take?

We investigated the relationship between the number of high-authority mentions an entity has across the web and the consistency of its recognition by major AI systems. Using 40 test entities (brands in the R20M–R200M revenue range, none with Wikipedia entries), we tracked citation consistency as we systematically built out their mention footprint across authoritative sources over a 6-month period.

Entity Recognition Rate vs. High-Authority Mention Count
% of varied query phrasings that trigger correct entity recognition (ChatGPT). n=40 test entities, controlled experiment.
0% 20% 40% 60% 80% 100% 9% 32% 61% 93% 10 50 100 200 High-authority mentions
  • Entities with fewer than 25 high-authority mentions show recognition rates below 20% — meaning ChatGPT fails to confidently identify the entity in more than 80% of query phrasings that should trigger a citation.
  • The steepest improvement occurs between 50 and 150 mentions — this is the "authority acceleration zone" where each additional mention has maximum marginal impact on recognition rates.
  • At 200 high-authority mentions, recognition rates plateau at approximately 93% — suggesting diminishing returns after this point, and that investment above ~200 quality mentions is better directed at citation placement rather than entity establishment.
  • Quality versus quantity: in a separate test arm, 50 mentions in domain rating 70+ publications produced higher recognition rates than 200 mentions in domain rating 20–40 publications. Authority of the mentioning source matters more than volume.
Study 04 · Ongoing Since 2024 · ChatGPT Citation Tracking
SA Brand ChatGPT Citation Tracking: Two Years of Visibility Data

We've tracked ChatGPT citation frequency for a panel of 120 South African brands across 15 industry categories since Q1 2024. This longitudinal dataset allows us to see how citation rates evolve over time, what interventions accelerate them, and which categories are most competitive in AI search.

SA Industry Category Avg ChatGPT Citation Rate (2024) Avg ChatGPT Citation Rate (2026) Change Competition Level
Financial Services (FSCA regulated) 12% 38% +217% High
Legal & Professional Services 8% 29% +263% Medium
E-commerce & Retail 15% 41% +173% High
Healthcare & Medical 9% 24% +167% Medium
Technology / SaaS 21% 57% +171% Very High
Tourism & Hospitality 18% 44% +144% Medium
Automotive 11% 28% +155% Medium
Education / EdTech 14% 36% +157% Low-Medium
  • Every category in our panel showed significant growth in citation rates — AI search is not a niche phenomenon but is penetrating across all South African industry verticals.
  • Technology and financial services are the most AI-visible sectors, partly because they have more content published about them in authoritative English-language sources, and partly because their queries are more commonly informational.
  • The correlation between traditional SEO ranking and AI citation rate is 0.43 — moderate, but not strong. Plenty of brands ranking #1 on Google have low AI citation rates, confirming GEO requires separate investment.
Study 05 · Completed Q4 2025 · A/B Content Test
GEO Content Format Study: What Structure Increases AI Citation Rates

Building on Princeton University's 2024 GEO paper (which identified a +40% uplift from quotation-rich content and +30% from citation-heavy content), we ran our own content format A/B test across 180 content pairs — identical topics, different structures — measuring AI citation rates over 90 days.

Content Feature Control Group Rate Test Group Rate Uplift Statistical Confidence
Original statistics (3+ per article) 14% 29% +107% 94%
Expert quotes with credentials 14% 23% +64% 91%
Answer-first paragraph structure 14% 24% +71% 88%
Cited external sources within content 14% 20% +43% 83%
Structured author byline with credentials 14% 19% +36% 79%
FAQ section with direct answers 14% 18% +29% 76%
  • Original statistics are the single most powerful content feature for AI citation — articles with three or more original, specific statistics are cited at 2× the rate of articles without them. This is why we produce original research rather than recycling industry data.
  • Content features compound: an article with original statistics, expert quotes, and answer-first structure was cited at 3.7× the rate of the plain-prose control — substantially more than any single feature in isolation.
  • AI citation rates showed almost no correlation with word count above 800 words — longer is not better for AI citation. Density of quotable, factual content matters more than length.

News24: South Africa's Most AI-Cited Publisher

What full public-data AI visibility actually looks like — and what it costs to not be cited alongside it.

To illustrate the depth of our AI visibility analysis, we've profiled News24 — South Africa's highest-traffic news publisher and, from our citation dataset, the most-cited South African source across all major AI engines. This audit uses publicly available data combined with our proprietary citation tracking. We publish it not as a client profile, but as a benchmark: this is what AI-visible authority looks like at scale. Your brand is competing in a space where News24's authority is the reference point AI systems use when evaluating South African content.

14.8M
Monthly visits (SimilarWeb est.)
27.8%
Organic search traffic share
~4.1M
Est. monthly organic visits
DR 82
Domain Rating (Ahrefs)
224K
Referring domains (Ahrefs)
~1.2M
Est. visits lost monthly to AI Overviews
Calculated Figure

The ~1.2M monthly organic visits lost to AI Overviews is our estimate, derived from: 4.1M organic visits × 48% AI Overview trigger rate on informational queries × 60% average CTR reduction = approximately 1.18M visits absorbed by AI Overviews monthly. News24 itself has publicly noted declining traffic despite stable rankings — this is consistent with our model.

News24: Estimated Traffic Source Breakdown
Public data composite (SimilarWeb + Ahrefs, May 2026). Traffic sources estimated from available public data.
Direct 38% Organic 27.8% Social 18% Ref 9% Direct Organic Social Referral Other AI Overviews are eroding the Organic slice — estimated ~1.2M visits/month absorbed by AI responses on informational news queries.
News24 AI Visibility Score vs. SA Media Peers (Proprietary GEO Score)
Our composite AI visibility score aggregates citation frequency across ChatGPT, Gemini, Perplexity and Google AI Overviews for SA-relevant queries. Score out of 100. Based on 8,400 tracked queries, Jan–May 2026.
News24
91 / 100
TimesLive
83 / 100
BusinessTech
74 / 100
Moneyweb
68 / 100
Daily Maverick
62 / 100
IOL
58 / 100
Avg. SA brand website
8 / 100

What News24's Authority Structure Reveals

News24 earns AI visibility because of a specific authority structure that most SA brands cannot replicate directly — but can draw on strategically. With a Domain Rating of 82 and 224,000 referring domains, News24 is part of the first-tier citation pool that all major AI engines have learned to trust. When an AI system is uncertain about a South African fact, News24 is a default reference point.

For most SA brands, the insight is this: getting cited or mentioned in News24, TimesLive, or BusinessTech is not just a PR win. It is a direct GEO intervention. It places your brand in the citation networks that AI systems already trust. Every media placement in a first-tier SA publisher is a GEO asset. We track which placements translate to AI citations and which don't — and we build outreach and content strategies around the ones that do.

The gap between News24's AI visibility score (91) and the average SA brand website (8) is the problem we solve. We can't replicate 20 years of editorial publishing overnight. But we can systematically build your brand into the citation networks that bridge that gap — and for most clients, we see meaningful AI visibility improvements within 90 days.

What Competitor Analysis Actually Looks Like

We run competitor gap analysis for every client before strategy is finalised. The goal isn't to copy what competitors are doing — it's to identify exactly where their authority is strong, where it's thin, and where we can build a meaningful advantage in AI search. Below are three anonymised competitor analyses from real engagements to illustrate the methodology.

Example A: Financial Services Category (Client vs. Market Leader)

Client: mid-size SA financial advisory firm. Competitor: a JSE-listed financial services group with 40+ years of history. The client ranked comparably on traditional Google but had dramatically lower AI visibility. Here's what the gap analysis revealed:

Gap Dimension Client Score Competitor Score Gap Priority
Entity Authority — Wikipedia presence, Wikidata completeness, Knowledge Panel 18/100 84/100 -66 Critical
Citation Network Position — how many AI-trusted sources cite this entity 22/100 71/100 -49 Critical
Content Authority — original research, cited data, expert bylines 41/100 67/100 -26 High
Trust Signal Coverage — FSCA registration visibility, accreditation mentions, reviews 38/100 79/100 -41 Critical
Domain Authority — DR / traditional link profile 51/100 74/100 -23 Medium
AI Citation Frequency — appearances in AI search results for category queries 9/100 68/100 -59 Critical

What the gap analysis revealed was that the competitor's AI visibility wasn't driven by better content or better SEO — it was driven by a 40-year legacy of mentions in authoritative South African financial media, regulatory databases, and JSE records. These "reality signals" — offline authority that has been digitised — are things a younger brand cannot replicate quickly.

Our strategy: rather than trying to close the entity authority gap directly (too slow), we focused on the content authority gap first — producing original financial research that Perplexity and ChatGPT could cite — while simultaneously building the entity foundation in parallel. Within 6 months, the client's AI citation frequency score moved from 9 to 31. The entity gap won't close fully for 18–24 months, but citation frequency is already improving because content authority can be built faster.

Example B: E-Commerce Category (Three-Way Comparison)

A retail client wanted to understand how they stacked up against two competitors in AI search for their product category. All three brands have similar DR scores (47–53) and comparable traditional Google rankings. Their AI visibility looks like this:

Three-Way E-Commerce AI Visibility Comparison (Anonymised)
Composite AI visibility score across ChatGPT, Gemini, Perplexity. Product category queries. n=1,200 queries.
0 25 50 75 100 Entity Citations Content Trust AI Cite Rate Our Client Competitor A Competitor B

The analysis revealed the client's single exploitable advantage: their content quality score (44) outperforms Competitor A (38), even though their overall AI visibility lags significantly. Competitor B has strong content (71) but weaker entity and citation authority than Competitor A. Our strategy: invest in entity and citation authority first (closing the gap on Competitor A's main advantages), while leveraging the existing content strength. In the medium term, building content authority to match Competitor B creates a brand that outperforms both competitors on combined GEO score.

What We're Currently Testing

Research doesn't stop. Below are the active experiments running in our synthetic authority labs right now — questions we don't yet have definitive answers to, but will.

Citation Decay Rates by Engine
We're measuring how quickly AI citation rates fall when active signal-building stops. Early data suggests ChatGPT citations decay more slowly than Perplexity citations (which are retrieval-based), but we want 12+ months of data before publishing.
Podcast and Audio GEO
As AI systems (particularly Gemini and Grok) increasingly index audio and video content, we're testing whether podcast appearances in authoritative SA shows translate to measurable AI citation increases. Initial results are promising.
POPIA Compliance as Trust Signal
We're investigating whether visible POPIA compliance documentation on South African brand sites correlates with higher AI trust signals in the local query context. The hypothesis: AI systems may weight regulatory compliance visibility as an E-E-A-T signal.
Multi-language Entity Recognition
South Africa has 11 official languages. We're testing whether entity mentions in isiZulu, Afrikaans, and other local languages affect AI citation rates in English-language queries about SA-specific topics — and which engines show this effect.
X/Twitter Authority Velocity
Grok's integration with X means Twitter/X mention velocity may directly affect citation rates on that engine. We're running a controlled test comparing two matched entities with different X mention cadences.
AI Citation vs. Conversion Rate
We're beginning to measure whether higher AI citation rates actually convert to business outcomes — brand search increases, direct traffic lifts, lead enquiries. The GEO industry is young enough that this causal chain hasn't been rigorously established yet. We're building the data to establish it.

Our 20 Biggest GEO Research Findings

These are not hypotheses. These are observations from our proprietary dataset — things we believe to be true based on measured evidence, flagged as our findings rather than established industry consensus.

01
Entity recognition by AI systems consistently precedes citation growth — you typically see recognition improve 4–8 weeks before citation rates follow.
02
AI systems appear to trust cited research significantly more than uncited opinion content, even when the uncited content is factually accurate and more detailed.
03
Only 11% of citations overlap between ChatGPT and Perplexity for equivalent queries — the two systems draw on fundamentally different source sets.
04
In South Africa, Wikipedia mentions in an entity's article contribute to AI citation rates across all major engines — more than any other single on-page signal we've tested.
05
Traditional SEO ranking correlates with AI citation at r=0.43 — moderate correlation, meaning significant GEO opportunity exists for brands with moderate traditional rankings.
06
Content with three or more original statistics is cited at approximately 2× the rate of equivalent content without original data. This is the single strongest content-level predictor of AI citation we've found.
07
AI systems appear to have a "trust threshold" for entities: below ~25 high-authority mentions, citation rates remain low and inconsistent regardless of content quality.
08
Google AI Overviews select from a different source set than the standard top-10 results on the same SERP approximately 35% of the time — confirming that AIO optimisation requires separate strategy.
09
Perplexity's 90-day freshness preference is real and measurable: content older than 90 days is cited at roughly 60% the rate of equivalent fresh content for most query categories.
10
Gemini shows stronger correlation with Google Business Profile completeness than any other AI engine — a 100% complete GBP correlates with a 34% higher Gemini AI citation rate in our test data.
11
Multi-engine consensus citations — where a brand is cited by three or more AI engines for the same query — are significantly harder to achieve than single-engine citations, and appear to require entity establishment (not just content) as a prerequisite.
12
The "answer-first" paragraph structure increases Google AI Overview inclusion probability by approximately 71% compared to intro-then-answer structures, in our A/B tests.
13
South African AI search adoption grew from ~10.5% in H1 2024 to 23.1% in Q1 2026 — a +120% increase in 24 months — making SA one of the fastest-growing AI search markets in emerging economies.
14
Authority of the mentioning source matters more than volume of mentions: 50 mentions in DR70+ publications outperform 200 mentions in DR20–40 publications for AI citation purposes.
15
Informational queries show AI-related organic CTR declines of -42% when an AI Overview appears — nearly three times the decline seen on transactional queries (-18%). Brands whose traffic is heavily informational face the most urgent GEO need.
16
For FSCA-regulated financial brands, regulatory registration visibility (name appearing in FSCA databases, compliance mentions in authoritative press) correlates with higher AI trust scores across all engines.
17
Brands with AI visibility scores above 50 in their category see directional brand search volume increases — our data shows an average 18% increase in branded search volume coinciding with significant AI visibility improvements.
18
Grok citations skew heavily towards brands and people with active X/Twitter presence — entities with more than 5,000 X followers show significantly higher Grok citation rates than comparable entities without X presence.
19
Content compound effects are real: articles with original data + expert quotes + answer-first structure are cited at 3.7× the rate of plain-prose content on the same topic — substantially higher than any single feature in isolation.
20
The GEO landscape is moving faster than anyone anticipated. What worked for AI visibility in early 2024 is partially obsolete by mid-2026. Continuous tracking — not one-time audits — is the only way to maintain and grow AI visibility over time.

Our Predictions for AI Search in 2027

Predictions in a fast-moving field are always partially wrong. We make them anyway because a reasoned view of where things are heading is better than paralysis. These are informed by our two-year dataset, our understanding of the technical direction of the major AI systems, and observable trends in user behaviour.

2027
Backlinks become less important for AI citation than citation graph position. Traditional link building will still have value for Google rankings, but the metric that matters for AI search is where you sit in the citation graph — who cites you, not just how many. Agencies that only build links will struggle to build AI authority.
2027
Citations in AI responses become more important than page-one rankings for brand discovery. By 2027, we predict the majority of brand-discovery queries will be answered by AI before the user ever sees organic results. Being cited in those answers will be the new "ranking #1".
2027
Established brands outperform pure content sites in AI search. AI systems are getting better at distinguishing real brands from content farms. Entities with offline reality signals — physical presence, regulatory registrations, news coverage, employee profiles — will increasingly dominate AI responses at the expense of SEO-only content plays.
2027
Original research becomes the dominant driver of AI citation authority. As AI systems become more sophisticated, generic content becomes less valuable. Brands that conduct and publish original research — even modestly scoped studies — will be disproportionately cited. The research barrier to entry for AI visibility will rise.
2027
AI systems increasingly trust real-world signals over purely digital ones. Wikidata, company registry entries, award databases, accreditation bodies, regulatory filings, and government databases all feed AI knowledge graphs. Brands with comprehensive real-world footprints will enjoy structural AI visibility advantages over digital-only brands.
2027
South African AI search adoption crosses 35%, becoming a mainstream search channel. Extrapolating from our 24-month growth trajectory (+120%), AI search adoption in SA will likely cross 35% by late 2027 — moving from early-adopter behaviour to mainstream usage. Brands not optimising for AI search now will face catch-up costs later.
2027
GEO measurement becomes standardised — AI visibility will be a boardroom metric. Currently, AI visibility tracking is largely proprietary. By 2027, we expect platforms comparable to SEMrush or Ahrefs for AI citation tracking to exist. When that happens, AI visibility scores will become reportable board-level metrics. The companies that built GEO authority early will show structurally superior numbers.

What We Stand For — and What We Won't Do

GEO is a young discipline with no established ethical standards. That creates opportunity for bad actors. We're deliberately transparent about where we draw lines — both because it's the right thing to do, and because we believe the AI systems we're optimising for are getting better at detecting and discounting manipulation.

We Will Never

Recommend content that exists solely to manipulate AI rankings
If a piece of content would be worthless to a human reader, it will be worthless to an AI system in the medium term. We don't produce AI bait. Everything we publish must be genuinely useful.
Build fake citation networks
Unlike some link-building practices, AI citation networks are built on editorial trust. We earn citations by placing real, accurate information in genuine editorial sources. We don't fabricate press or manufacture citations.
Claim GEO benefits we can't substantiate
This is a young industry and some claims being made are optimistic at best. We report what our data shows. When we're uncertain, we say so.
Optimise for citations that misrepresent a client
AI citations that inaccurately describe a brand are a long-term liability. We optimise for accurate representation — which is also more durable than manufactured narratives.

We Always

Optimise for being the best answer
The most defensible GEO strategy is to make your brand genuinely the best, most authoritative, most accurate answer to relevant queries. That's what we build toward.
Optimise for trust
Trust signals in AI search are real-world signals — editorial mentions, regulatory records, verifiable facts. We build trust by helping clients establish real authority, not manufactured appearances of it.
Report our findings openly
We publish research that contradicts conventional GEO wisdom when the evidence supports it. Our database is proprietary, but our findings are shared — because the industry needs better data, and sharing findings establishes us as the authority we claim to be.
Measure actual outcomes
We track AI citation rates, entity recognition scores, and AI visibility metrics against baselines. We report these honestly — including when campaigns underperform and we need to adjust strategy.
"We optimise for being cited because you're genuinely the best answer — not because you've gamed the system. Gaming AI systems is a short-term play; the systems are getting smarter faster than the manipulators."

What We Offer That Others Don't

Original GEO Research
We conduct original research — not research summaries of other people's work. When we tell a client what affects their AI visibility, we're drawing on our own data, our own experiments, and our own findings. No other agency in South Africa can say this.
Proprietary Authority Dataset
Our 100,000+ query database and citation tracking infrastructure is ours. It's not based on publicly available tools. It gives us visibility into AI citation patterns that simply doesn't exist in off-the-shelf platforms.
Competitor Trust Signal Reversal
We don't just build your authority — we reverse-engineer how competitors earned theirs. We identify the specific sources, publications, and citation chains that underpin competitor AI visibility, and we build strategies to access the same networks.
Multi-Platform AI Visibility Tracking
We track your visibility across ChatGPT, Perplexity, Gemini, Grok, Claude, Copilot, and Google AI Overviews simultaneously — not just one engine. You see exactly where you're visible, where you're absent, and how you compare to competitors on each platform.
Controlled Environment Testing
When something is worth testing, we test it in isolation — in our controlled lab environment — rather than running experiments on client accounts. You get the benefit of our findings without the risk of being the experiment.
Published Research & Intellectual Leadership
We publish findings. That means our clients benefit from the authority of being associated with the agency that produces GEO research — their citations and the agency's citations are linked in the networks AI systems map.
The Bottom Line

If you want someone to write blog posts and call it GEO, there are dozens of agencies that will do that. If you want a research-backed, measurement-driven programme that actually tracks whether AI systems are citing your brand — and systematically improves that — we're the only agency in South Africa running that programme.

Jaco Smit

JS
Jaco Smit
Founder & Lead GEO Researcher
20+ years software development
10+ years SEO strategy
CIO Consultant to major SA organisations
AI Researcher — published findings
Biochemist by academic background
GEO Specialist since 2023

generativeoptimization.co.za ?

Jaco Smit is not a marketer who pivoted to AI. He's a software developer with over two decades of experience building systems, a biochemist who understands how complex datasets work, and an AI researcher who began studying generative systems before the current wave of tools existed.

His background matters because GEO sits at the intersection of software, data science, and search strategy. Most people coming to this space arrive from one direction — usually content marketing or SEO. Jaco's technical depth means he understands not just what AI systems respond to, but why: how language models construct world models, how retrieval-augmented systems source content, and how entity graphs are built and queried.

CIO Experience

Jaco has served as a CIO consultant to major South African organisations, an experience that shapes how he approaches GEO for clients. He understands how decisions get made at the executive level, what risk looks like from a board perspective, and why a sustainable, measurable strategy outperforms a flashy short-term play. Clients who work directly with Jaco often comment that the thinking goes deeper than they expected — because it does.

The Research Commitment

The proprietary database, the synthetic authority labs, the controlled experiments — these weren't features added to make the agency look impressive. They were built because Jaco found the available GEO research inadequate and decided to generate better data. The 100,000-query dataset didn't exist when he started building it. He built it because the questions he needed to answer for clients couldn't be answered any other way.

AI Research Background

Jaco's AI research work predates his GEO specialisation. He has studied the architecture of large language models, how they encode entity knowledge during training, and how retrieval-augmented generation systems integrate live data with trained knowledge. This theoretical foundation is what makes his practical GEO strategies different — they're built on an accurate model of how the systems actually work, not on inference from surface-level observations.

The South African Context

Working in South Africa adds layers that international GEO frameworks don't account for. POPIA compliance, FSCA regulatory authority, JSE-listed entity signals, the role of South African media in AI training data, the particular weight given to News24 and TimesLive in AI citation networks for local queries — these are things Jaco has mapped specifically for the SA market. The strategy we build for a Johannesburg financial services client is not a copy of a US GEO playbook adapted superficially. It's built from the ground up with SA authority structures as the foundation.

"Most GEO strategies I see are content strategies in new clothes. Real GEO requires understanding how AI systems actually construct and update their world models — and that's a technical question, not a content question."

Find Out Where Your Brand Stands in AI Search

We start every engagement with a baseline AI visibility audit — tracking your citation frequency across ChatGPT, Perplexity, Gemini, Grok, and Google AI Overviews, and benchmarking it against your top three competitors. You'll know exactly where you are before we discuss where you need to be.

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South Africa's dedicated GEO research agency. Based in Johannesburg. Working with clients nationally and across Africa.