Consumer Behaviour
Brand demand
Search volume for branded terms. In an AI-search world, brand demand is the single strongest moat, generic queries are absorbed by AI Overviews and ChatGPT, while branded queries route users directly to brand properties.
What it is
Brand demand is search and prompt volume for terms that name a specific company, product, or person. It reflects deliberate intent to reach a known entity rather than to explore a generic topic.
Why it matters
As generic queries are absorbed by AI Overviews and chat assistants, branded queries remain the strongest moat because they route users directly to brand properties instead of being answered away by a synthesised summary.
How it works
Brand demand is observed through branded query volume, the rate at which people add a brand name to generic searches, and how often a brand is asked for by name inside generative assistants.
When it applies
It applies whenever measuring discovery durability and the resilience of traffic against zero-click answers.
Examples
- A user types the brand name plus reviews rather than the generic product category.
- Someone asks an assistant for that specific tool by name instead of asking for the best option.
- Branded navigational queries climb after a campaign while generic category clicks decline.
How it is measured
- Branded search and prompt volume over time
- Ratio of branded to non branded query volume
- Share of branded navigational queries reaching owned properties
- Frequency of the brand being named directly inside assistant conversations
Related terms in Consumer Behaviour
- Agentic browserA browser (or browsing layer) that uses an LLM agent to interpret pages, summarise content, and take actions on behalf of the user. Arc Search, Perplexity Comet, Browser Company's Dia, Dia browser, and similar.
- Agentic commerceAgentic commerce is buying and selling in which an AI agent completes part or all of the purchase on a person's behalf, from finding products to placing the order. Instead of browsing a site, the shopper states an intent and the agent searches, compares, fills the cart and sometimes pays. It shifts the point of decision away from the merchant's own interface and towards the assistant.
- App discoveryApp discovery is the set of ways people find and decide to install mobile apps, including store search and browse, editorial placements, web search, social feeds, advertising, AI assistants and word of mouth. It covers the whole path from first awareness to tapping install. Growth teams study it to work out which surfaces create demand and which only capture it.
- Brand discoveryBrand discovery is the process by which someone encounters a brand for the first time, or becomes newly aware it can solve their problem. It happens across search results, AI assistants, social feeds, communities, creators, reviews, marketplaces and word of mouth. Marketers study it to work out which surfaces introduce them to future customers.
- Consumer behaviour signalObservable patterns in how users phrase queries, refine searches, and choose answers, used by both ranking systems and generative models to infer intent and quality.
- Conversational searchConversational search is the pattern of finding information through a back and forth dialogue rather than a single keyword query, with each follow-up interpreted in the context of what came before. Users ask broad questions, then narrow with refinements such as cheaper, nearby or without the subscription. It shifts discovery from ranked link lists towards answers that must survive several rounds of questioning.
Primary research · August 2026
How ChatGPT Shortlists Software Brands
An audit across 10 categories and 60 buying questions. I recorded what ChatGPT reads, throws away and links to when a buyer asks it which software to buy, and what that decides.
- 60
- Questions asked
- 10
- Software markets
- 2,680
- Results read
- 367
- Links shown
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