Service · Marketing & CRM
AI Brand Visibility (GEO, AI ads, etc.)
Evolving brand visibility and discoverability in the AI-driven search landscape. From AI visibility assessments and competitive benchmarking to GEO strategies, content optimisation and AI advertising opportunities, we help brands understand, monitor and improve how they are represented, cited and recommended across generative AI platforms.
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What is AEO, Answer Engine Optimization?
AEO is the optimisation of content so that answer engines can extract and reuse it directly in responses. It focuses on clear, self contained, verifiable statements rather than on ranking a page, because the answer is consumed without a visit.
What is Share of Model?
Share of Model is the percentage of brand mentions compared with competitors in category prompts across the main language models. It is the AI era equivalent of share of voice, and the primary metric for monitoring brand presence in generated answers.
What is algorithmic misrepresentation of a brand?
It is when models spontaneously describe a brand inaccurately or unfavourably, because they are drawing on outdated, partial or third party sources. Since the answer reaches the buyer without the brand's involvement, the correction has to happen upstream, in the sources and structured data the models consume.
What is an AI advertising strategy?
AI advertising strategy redefines the media mix away from a model centred on CPM and CPC in paid search and social, towards presence in the conversational ecosystems of AI assistants. The aim is earlier, cheaper coverage in the channels where discovery is moving.
Why is customer acquisition cost rising on traditional channels?
Because paid search and social inventory is saturated and competition has pushed bidding costs up faster than conversion. arad's response is to rebalance the mix towards AI native and conversational touchpoints, where coverage is still obtainable at lower cost, while tracking CAC and ROAS across both.
What is the GenAI hangover?
The GenAI hangover is the saturation of the market with generic AI generated content and the drop in its effectiveness. Leading brands are responding by re investing in human crafted content and in people able to produce original insight, because volume no longer buys attention and relevance does.
What is Generative Search Visibility?
Generative Search Visibility measures how often and how prominently a brand appears in answers generated by AI search engines and assistants. It is tracked alongside Share of Model and brand sentiment accuracy to give a complete picture of presence in AI answers.
What is Brand Sentiment Accuracy in AI answers?
Brand Sentiment Accuracy measures whether the tone and substance returned by the main language models match the brand's actual positioning. It distinguishes a visibility problem from a representation problem, which need different interventions.
What is the AI Brand Visibility service?
AI Brand Visibility covers the monitoring and optimisation of how a brand appears in AI driven search and recommendations, including GEO and AEO work and AI advertising. It is delivered within the Marketing & CRM area and pairs naturally with agentic readiness work.
What is GEO, Generative Engine Optimization?
GEO is the practice of influencing how generative AI engines describe, position and recommend a brand in their answers. It replaces the click oriented logic of classic SEO with one aimed at being cited correctly inside a generated answer.
How is GEO different from SEO?
SEO optimises for a ranked list of links and measures clicks. GEO optimises for inclusion and accuracy inside a generated answer, where there may be no click at all, and measures share of mentions, sentiment and referral traffic from AI assistants. The two coexist but need different content and metrics.
How does arad monitor how ChatGPT, Perplexity, Gemini and Claude describe a brand?
Through systematic monitoring of brand mentions across the main language models: which prompts surface the brand, how it is positioned against competitors, and whether the description is accurate. The output feeds both content corrections and the structured data work behind them.