Consumer Behaviour
Local search
Also known as: near me search, local intent search
Local search is the behaviour of looking for products, services or places near a specific location. It includes explicit queries such as "barber near me" or "plumber Bristol" and implicit ones where the search engine infers location from the device. These searches usually sit close to action, with the searcher intending to call, visit or book soon.
What it is
Local search describes a category of consumer behaviour rather than a single tool or channel. It happens on search engines, maps, voice assistants, review sites, marketplaces and increasingly inside AI chat interfaces. The defining feature is a proximity constraint: the searcher only wants options they can reach or that can reach them.
Why it matters
Local searches tend to carry high commercial intent, so they matter disproportionately to revenue for place based businesses. Understanding the behaviour tells marketers which surfaces to prioritise, which details searchers check before choosing, and which objections to answer up front. It also explains why operational facts such as opening hours, parking and stock levels behave as ranking and conversion factors.
How it works
Practitioners map the local journey: discovery query, comparison of the shortlist shown, verification of details like hours and reviews, then contact. They then make sure each step is served, with accurate listings for discovery, photos and reviews for comparison, and a fast call or booking path for the final step. Query data, call recordings and in store questions are used to spot the details searchers actually care about.
When it applies
It applies to any category where distance or travel time affects the buying decision, from emergency trades to restaurants and clinics. It is less relevant for digital products with no delivery or service boundary.
Examples
- A user searches "pharmacy open now" on a phone at 9pm and picks the second result because the hours are confirmed as open.
- A homeowner searches "boiler repair same day" and calls straight from the map listing without visiting any website.
- A commuter searches "coffee" in Maps at a station, compares photos and ratings, and walks to the nearest option above four stars.
How it is measured
- Volume and share of impressions from queries with explicit local modifiers
- Click to call rate from map and local pack listings
- Direction requests and store visit conversions by day part
- Conversion rate of local landing pages against site average
Insights on Local search
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 demandSearch 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.
- 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.
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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