AI Visibility in Marketing & Advertising: Which Sources Shape Platform Recommendations?

When a marketer asks ChatGPT, “What’s the best platform for B2B advertising?” or “Which tools should I use for social media marketing?”, the brands appearing in that answer can become part of the decision journey. The sources behind those answers matter too. 

Peak Ace’s LLM Visibility Benchmark analysed a fixed set of 1,000 commercially relevant prompts across 10 industries in Germany during August 2026. Across Gemini, ChatGPT and Google AI Overviews, we measured which brands show up, which source types are retrieved and how brands are spoken about. Here’s what this standardised snapshot reveals for Marketing & Advertising, with a focus on the source mix and its implications for GEO. 

Contents 

• How we conducted our LLM Visibility Benchmark 
• AI Visibility for Marketing & Advertising: How does it compare to other industries? 
• Which Marketing & Advertising brands are most visible in AI? 
• Which Sources Do LLMs Use for Marketing & Advertising Questions? 
• How do Marketing & Advertising brands become visible in AI? 
• The Full Picture Is in the LLM Visibility Benchmark 
• FAQ: AI Visibility in Marketing & Advertising 

How we conducted our LLM Visibility Benchmark 

The benchmark is built on a defined methodology: 

• 1,000 standardised bottom-of-funnel prompts across 10 industries, each with 100 commercially relevant prompts. 
• Prompts were split across 10 topic clusters per industry. 
• Four intent types were tested: best/top/test winner, comparisons, pricing/where to buy, and criteria/guidance, with 25 prompts per intent in each industry. 
• The analysis focused on the German market and German-language prompts during August 2026. 
• Gemini, ChatGPT and Google AI Overviews were monitored. Each prompt ran 15 times, five per system. 
• Data was sourced from Peec AI exports; 50 brands per industry were monitored, with reporting focused on the Top 20 by visibility. 
• The three core brand KPIs are visibility, Share of Voice/SOV and sentiment. Visibility measures how often an entity appears in answers for the prompt set. Sentiment measures the tone of answers mentioning an entity on a 0–100 scale. For concentration analysis, SOV shares are normalised to 100% within the Top 20. 

The source analysis describes retrieval counts and URL types by industry and intent. All results apply to the selected prompts, monitored entities, systems and study period. 

For the full methodology, definitions and cross-industry breakdowns, the complete benchmark is available for download. 

AI Visibility for Marketing & Advertising: How does it compare to other industries? 

Marketing & Advertising shows a distinct source mix in our benchmark. Product pages lead for recommendation and purchasing prompts, while comparison pages lead for those intents across all 10 industries. 

Here’s how the leading source types compare: 

The percentages describe the cross-industry retrieval mix, not Marketing & Advertising shares or explicit citation rates. The industry scorecard recorded 80,240 retrievals. 

For marketers, this suggests reviewing product information alongside comparisons and guides. The aggregate pattern is not a content prescription for every industry. 

Marketing & Advertising also records average visibility of 6.85%, average SOV of 4.15% and sentiment of 52.8. Sentiment should be read as a relative indicator of answer tone within the dataset, not as an absolute measure of brand quality. 

Its HHI is 1,200, and its Top-3 Share is 51%. Three entities account for 51% of SOV normalised within the Top 20. The benchmark measures this concentration, not market share or why an individual brand was selected. 

Which Marketing & Advertising brands are most visible in AI? 

According to Peak Ace’s benchmark for Germany in August 2026, the top three entities by visibility in the Marketing & Advertising prompt set are: 

• LinkedIn: 21% visibility. 
• Google Ads: 19% visibility. 
• Meta: 19% visibility. 

The composition of this group matters when interpreting the results. LinkedIn, Google Ads and Meta are not simply companies producing marketing content; their advertising platforms are themselves products covered by the commercial questions. 

The white paper identifies the nature of the prompts as a structural factor in their visibility. Their mention rates should therefore not be interpreted as evidence of superior content performance. The benchmark tracks named products, brands or programmes, rather than necessarily the wider corporate group. 

Which Sources Do LLMs Use for Marketing & Advertising Questions? 

The benchmark also analysed which types of content the selected AI systems retrieved when processing Marketing & Advertising prompts. 

Note: retrieval data shows which sources a system accessed, not necessarily what it explicitly cited in the final answer. The source mix varies by intent: 

A few things stand out:

• Product pages feature in all four intent lists. They lead for recommendations and purchasing questions, and rank second for comparisons and guidance. 
• Comparison pages lead for comparison prompts and also feature in the recommendation and purchasing lists. 
• How-to guides lead for criteria and guidance. Articles also appear in the guidance, comparison and purchasing lists. 
• Listicles and homepages feature in recommendations, showing that the mix extends beyond product pages. 

The source mix changes with the question, supporting a review of content across the decision journey rather than a single query type. “Other” is a residual category, not a specific format or a measure of authority. 

Retrieval is not the same as citation: accessing a page does not guarantee a link, citation or brand mention. The URL classifications also do not establish whether content is owned or independent. 

What does the source mix suggest? 

• Product pages support evaluation, not just purchasing. Their presence across all four intents suggests reviewing whether they explain suitability and selection criteria alongside features and pricing. 
• Guidance needs practical content. How-to guides leading the guidance list may indicate value in explaining how a platform addresses a specific task, rather than relying on feature descriptions alone. 
• Recommendations draw on a broader mix. Listicles, homepages and comparisons feature alongside product pages. Review how your offering is described in shortlist and comparison formats, including relevant third-party coverage where appropriate. 

How do Marketing & Advertising brands become visible in AI? 

The data raises several questions that marketing and advertising teams should consider: 

• Are you visible on the comparison pages, articles and listicles retrieved for relevant questions? Review your own content and appropriate third-party sources, including the actual pages and domains behind your monitoring results. 
• Does your content strategy cover all four intent types? Focusing only on “best marketing platform” questions can leave comparisons, criteria, guidance and pricing unaddressed. Plan around what the user wants to accomplish. 
• Is your brand represented consistently across relevant sources? Check product information across your website, comparisons and editorial coverage. Consistency is an information-quality priority, not a visibility effect proven by this study. 
• Have you considered a coordinated GEO strategy? Combine SEO, content and Digital PR, and use a fixed prompt set to monitor brand mentions and retrieved sources separately. Review changes by intent and system.

The Full Picture Is in the LLM Visibility Benchmark 

This blog post covers the Marketing & Advertising highlights. The full LLM Visibility Benchmark goes further: 

• How the source mix differs across all 10 industries. 
• How source types shift between recommendations, comparisons, pricing and guidance. 
• Visibility, SOV and sentiment for the reported brands. 
• How concentrated SOV is within each industry’s Top 20. 
• The industry scorecards and complete methodology. 

Download the full LLM Visibility Benchmark here. 

Had a look at our benchmark and looking to improve your brand’s presence in AI answers? Get in touch with our LLMO & GEO team. 

FAQ: AI Visibility in Marketing & Advertising 

How visible are Marketing & Advertising brands in ChatGPT and other AI assistants? 

Average visibility was 6.85% in our German-market benchmark for August 2026. This applies to the monitored entities and fixed commercial prompt set, not all marketing questions. 

Which Marketing & Advertising brands are most visible in AI search? 

LinkedIn has 21% visibility, while Google Ads and Meta each have 19%. Their platforms are themselves products covered by the prompts, which matters when interpreting these figures. 

What types of content do LLMs use to answer marketing questions? 

In our benchmark, product pages lead for recommendations and purchasing questions, comparisons for comparison prompts, and how-to guides for guidance. Retrieval does not necessarily mean citation.