Get your brand into the answers buyers trust.
Your customers are no longer only searching Google. They are asking ChatGPT, Gemini, Perplexity and Google's AI which company to choose. I help brands understand how those systems see them, build the signals that make them easier to trust and cite, and measure what happens when AI visibility turns into traffic, leads and revenue.
Being on Google is no longer the same as being in the consideration set.
For years, search visibility mostly meant earning a ranking and winning the click. That journey is changing. A buyer can now ask an AI to recommend three providers, compare them and explain which one best suits their needs without visiting ten websites first. That creates a different problem for marketing teams. You may rank well and still be absent from the answer. You may appear in the answer, but with old information. A competitor may be recommended because third-party sources explain their proposition more clearly than yours.
And even when AI starts sending visitors and leads, most reporting stacks still bury that demand under referral traffic, organic or 'other'. AEO and GEO work is about fixing that entire chain. Not finding another place to stuff keywords.
What are AEO and GEO consulting?
Answer Engine Optimisation (AEO) and Generative Engine Optimisation (GEO) are the disciplines of improving how clearly AI-powered search and answer systems understand, source, cite and recommend a brand.
AEO tends to describe optimisation for direct answers. GEO is commonly used for visibility within generative AI responses. In practice, the work increasingly overlaps. Good AEO/GEO consulting looks beyond content alone. It examines the entity behind the brand, the information published about it, structured data, third-party sources, technical accessibility, content architecture, citations and the measurement layer underneath all of it. QFD works across that full system.
This is not SEO with 'AI' added to the proposal.
SEO still matters. A lot. AI systems need reliable information to work with, and search visibility, authoritative websites and strong content remain important signals. But getting a page to rank and getting a brand confidently recommended are not exactly the same problem. An AI engine may draw on your website, media coverage, review sites, structured data, industry publications, comparison articles, knowledge sources and other material when forming an answer. So the work starts with a broader question: What does the information ecosystem say about your business, and does it give an AI enough confidence to recommend you? That changes the job.
If you want the full diagnostic version of this, the AEO/GEO Visibility Audit is where most engagements begin.
From 'what is AI saying about us?' to a system you can actually operate.
Establish the baseline
Before changing anything, I test the questions real buyers are likely to ask. We look at where the brand appears, where it does not, which competitors repeatedly surface, what claims are being made, which sources are influencing the answers and where the information is simply wrong. That creates the baseline everything else is measured against. Includes: prompt testing, competitor visibility, citation analysis, entity review and answer accuracy.
Fix the information layer
AI engines cannot confidently recommend information they cannot resolve. I review how the brand, products, services, people, locations and key commercial facts are represented across the site and the wider web. The goal is consistency and clarity, not adding schema for the sake of saying schema was added. Includes: entity architecture, structured data, knowledge signals, source consistency and technical accessibility.
Build content worth citing
Most AI-generated content is remarkably easy to ignore. The objective is not to produce more words. It is to create information that is useful enough to be retrieved, quoted, compared or cited. That can include definitive answers, original research, comparisons, methodology pages, benchmarks, commercial guides and genuinely useful subject-matter content. Every content recommendation must have a reason to exist beyond filling a keyword gap.
Strengthen the citation footprint
Your website is only one source. If the wider information environment barely mentions the brand, describes it inconsistently or lacks credible evidence of what it does, there is a limit to what on-site optimisation can accomplish. I map the sources AI systems are relying on in your category and identify where legitimate authority can be strengthened. This is not a link-buying exercise. It is source strategy.
Test the answers again
AI visibility is not something I mark as 'implemented' and walk away from. We return to the original prompt set and test whether the information being surfaced has changed, whether visibility has moved and whether new citation patterns are emerging. What changes gets retained. What does not gets challenged.
Connect visibility to revenue
This is where QFD differs from most AEO providers. Being mentioned by ChatGPT is interesting. Generating qualified demand is commercially useful. I build the measurement layer that separates AI referral traffic, tracks what those visitors do, carries acquisition source into lead and CRM data where possible, and gives the business a way to evaluate AI visibility against pipeline and revenue. Because eventually somebody in finance is going to ask whether any of this made money. They should get a better answer than a screenshot of a ChatGPT response.
The work ends in implementation, not a 70-page deck.
The exact scope depends on what the baseline uncovers, but an AEO/GEO consulting engagement can include:
AI visibility baseline
A repeatable prompt set across the AI/search surfaces relevant to your market, with competitor visibility, recommendation position, answer accuracy and citation sources documented.
Entity and technical architecture
Clear recommendations and implementation guidance covering structured data, entity relationships, crawlability, knowledge signals and information consistency.
Citation and source map
A view of which third-party sources influence answers in your category, where your competitors have stronger information footprints and where legitimate gaps can be closed.
Content architecture
A prioritised content plan based on buyer questions, citation opportunities, commercial intent and genuine information gaps.
Implementation support
Technical briefs, content briefs, implementation review and direct collaboration with the people building the work.
Measurement
AI referral tracking, visibility measures and, where the stack allows it, attribution through to leads, pipeline and revenue.
I have already done this where getting the answer wrong mattered.
For a national brand, major AI engines were describing products and pricing using information that was years out of date. This was not a traffic problem. People were receiving the wrong answer before they ever reached the website. I traced where the outdated information was coming from, rebuilt the entity and structured-data layer, corrected the source signals and monitored the answers across the major engines. The stale information was replaced by the current facts across four AI/search environments.
Visibility is a metric. Revenue is the outcome.
A lot of AEO reporting currently ends with screenshots, mention counts and 'share of voice'. Those are useful diagnostic measures. They are not the business case. QFD also works on the acquisition architecture underneath the marketing. That means we can track AI referral traffic separately, understand what those users do, connect lead sources to CRM outcomes where the stack supports it, and compare AI-driven demand with the rest of the acquisition mix. The objective is not to make AI visibility look impressive. It is to understand whether it creates commercial value.
This tends to work best when the brand already has something worth finding.
AEO/GEO is not a shortcut around having a credible business, useful website or real market presence. The strongest engagements tend to be with businesses that already have established expertise, customers, products, data or authority, but have not yet translated those assets into a clear AI-search footprint.
A good fit
- Established or scaling brands
- B2B and B2C businesses with meaningful customer consideration
- Businesses where recommendations influence the buying journey
- Marketing teams already investing in SEO, content, PR or performance media
- Brands with subject-matter expertise or proprietary data that is currently underused
- Organisations that care about measurement after the mention
Probably not a good fit
- Businesses looking for guaranteed ChatGPT rankings
- Companies wanting hundreds of cheap AI articles
- Brands without a clear proposition or credible evidence behind their claims
- Anyone looking for a one-week "GEO hack"
Start with the evidence. Then decide how much work is actually required.
If we have not worked together before, the cleanest starting point is usually the AEO/GEO Visibility Audit. That establishes what AI systems currently say about the brand, where competitors are stronger, which sources matter and what is technically or informationally broken. From there, I can either hand the implementation roadmap to your internal team, work alongside them, or stay involved through the implementation and measurement phase. No forced long-term retainer. No proprietary black box you become dependent on. The goal is to leave you with a system your team understands.
AEO & GEO consulting: common questions
AEO usually refers to optimising information so search and AI systems can provide clear answers. GEO focuses more specifically on visibility and citation within generative AI responses. The terminology is still evolving and the disciplines overlap heavily, which is why QFD treats them as one connected optimisation problem.
No. Strong organic search fundamentals remain valuable because AI systems still depend on accessible, authoritative information from the web. AEO/GEO extends the work into entities, citations, answer formats, third-party sources, AI visibility and measurement.
No, and anybody promising that should make you nervous. AI responses change based on model, prompt, context, sources and updates. The job is to improve the quality and strength of the information signals available, measure what changes and systematically increase the brand's ability to surface in relevant answers.
The exact mix depends on the market, but testing can include ChatGPT, Gemini, Perplexity, Google AI Overviews and Google AI Mode. The point is not to optimise for a single interface. It is to build a stronger information footprint that can travel across multiple answer systems.
It depends on the starting point. Incorrect structured information can sometimes be fixed relatively quickly. Building authority, earning stronger citation signals and changing recommendation patterns can take longer. QFD establishes a baseline first so progress can be measured against evidence rather than an arbitrary timeline.
The work can span AI-answer testing, entity analysis, structured data, citation research, technical accessibility, content architecture, source strategy, implementation review and measurement. QFD also connects the visibility work to analytics and revenue attribution.
QFD can develop the strategy, research, content briefs and core specialist content required by the programme. Where a client already has writers or a content team, I can work directly with them rather than replacing the function.
No. QFD is based in Cape Town and works remotely. The methodology can be applied to South African, UK, US and other international markets, with the prompt, source and competitive research adapted to the actual market.
Before trying to 'rank in AI', find out what the machines are already telling your customers.
We will start with the questions buyers ask, the answers they receive and the sources shaping those answers. If there is a meaningful gap, I will tell you where it is and what I would do about it. If there is not, I will tell you that too.
30 minutes. No pitch deck. No obligation. Cape Town based, working globally.