FAQ

170,000+

Real-time global LLM queries every second

Estimates based on public data from OpenAI, Google, Anthropic and Meta — language models globally now handle over 170,000 queries per second. This figure is growing exponentially, mirroring the surge in internet traffic seen between 2000 and 2005.

14.5 min

Average duration of a user's conversation with an LLM before purchasing a product

According to McKinsey and CivicScience reports (2024/2025), consumers spend an average of 14–16 minutes interacting with language models regarding products before making a purchase. This represents a dramatic shift compared to Google, where a user typically spends only 8–12 seconds on a single search result.

62%

of users trust AI recommendations when choosing products

CivicScience 2024 Report: 62% of generative AI users consider language model recommendations 'useful or very useful', while 28% find them more credible than Google results or traditional user reviews.

41%

of purchase decisions in 2025 begin with an LLM instead of Google

McKinsey 'The AI Consumer Shift 2025' Study: 41% of consumers now start their product research through a conversation with a model (ChatGPT, Gemini, Claude) rather than a search engine. This trend is particularly dominant in electronics, travel and financial services.

20,000+

content snippets per average brand are analysed by LLMs monthly

Based on embedding traffic analysis and model crawling (GPT-4.1, Gemini, Claude 3.5): an average brand generates 20,000–50,000 content fragments monthly, which are extracted, summarised or classified by models. In retail and FMCG, this figure exceeds 100,000.

4.4x

higher conversion: traffic from AI responses converts over 4 times better

Semrush AI Search Trends 2025: Users arriving via AI Answers, ChatGPT Browsing or Bing CoPilot make a purchase 4.4x more frequently, on average, than those coming from traditional Google search results.

5 years

semantic content maintains visibility up to 5x longer than traditional SEO

While keyword-targeted SEO content typically loses visibility after 6–12 months, content based on brand semantics (topic clusters + intent + AI context) remains stable for 3–5 years because it is semantically 'readable' for LLMs and AI-first search engines.

37%

average increase in CTR for semantically designed content

HubSpot 2024–2025 Report: Content built on semantic topic clusters achieves an average 37% higher Click-Through Rate (CTR) compared to traditional keyword-based SEO content.

40%

of websites will lose traffic following the full implementation of SGE

Search Engine Land + Gartner: Once Google's Search Generative Experience (AI Overviews) is fully deployed globally, organic traffic is predicted to drop by 35–40% for sites lacking semantic content. The most vulnerable include advice blogs, aggregators and e-commerce sites without optimised descriptions.

48h

LLM models refresh their brand knowledge every 2–3 days

Based on OpenAI Developer Docs and 2025 crawling tests: ChatGPT, Gemini and Claude update fragmented knowledge (embeddings, summaries, classifications) every 48–72 hours for public content. For social media, this refresh rate is even faster (12–24 hours).

57%

of corporate content is unutilised by AI models

Content Science and Clearscope Research: 57% of corporate content contains semantic errors (lack of context, poor connectivity, incorrect tagging or overly promotional language), leading language models to deem it unhelpful or ignore it entirely in their responses.

68%

of companies have no control over how AI models describe their products

McKinsey 'State of AI in Marketing 2025': 68% of firms admit they do not monitor how AI represents their brand, have never optimised content for models, and do not know which data sources LLMs use to form opinions on their offering.