Intent classification

Intent classification sorts every tracked prompt into one of five categories so you can see which part of the buying journey your citations are winning.

Not all AI queries are equal. Someone asking "what is a compounding pharmacy?" is in a very different mindset from someone asking "best compounding pharmacy near me." Intent classification is how Outercite sorts every prompt it tracks into one of five categories, so you can see exactly where in the buying journey your brand appears. The five category names below reflect how they appear in the product currently and may evolve over time.

Diagram placing the five intent types along the buyer journey from early research to ready-to-buy.

What you'll learn

The five intent types and what each one signals
Why intent mix matters more than raw citation count
How to use your intent breakdown to cover the full funnel

The five intent types

1. Local

The user is looking for something nearby or in a specific place. Queries include location phrases like "near me," a suburb name, or a city.

Examples: "pharmacy in Fitzroy," "best coffee roasters Melbourne CBD," "accountant near me."

Local intent signals high commercial readiness. The user knows roughly what they want. They are choosing between options based on proximity, hours, or reviews. If your business appears in local-intent answers, you are in the final shortlist for a nearby customer.

2. Buying intent

The user is actively considering a purchase or booking. They are past the awareness stage and evaluating options or asking for recommendations.

Examples: "best CRM software for small business," "which conveyancer should I use," "recommend a good SEO agency."

Buying-intent citations are the most commercially valuable. A user who asks an AI for a direct recommendation and gets your name is very likely to follow through. The aggregate citation rate across all six tracked engines is 48%, meaning nearly half of checked queries already surface a citation for the monitored business. Buying-intent queries often exceed that average.

If you see a low citation rate on buying-intent prompts, that is the highest-priority gap to close. Start by reviewing your product and service pages for completeness, clarity, and structured data.

3. Informational

The user is learning. They are not buying yet. They want to understand a topic, process, or concept.

Examples: "how does compounding medication work," "what is a share registry," "explain invoice factoring."

Informational citations build authority. When an AI names your business in an explanatory answer, it positions you as an expert source in that category. Users in this phase may not convert immediately, but they are forming brand associations. Winning informational intent today creates a warmer audience for buying-intent queries later.

4. Comparison

The user is comparing two or more options, often side by side. They may name specific brands or product categories.

Examples: "HubSpot vs Salesforce," "Xero or MYOB for small business," "difference between Medicare and private health cover."

Comparison queries are competitive by definition. Your brand might appear as one of the named options, as a recommended alternative, or not at all. Tracking comparison intent tells you how AI engines position you relative to direct competitors. It feeds directly into your share of voice picture.

5. Branded

The user is searching for your brand specifically by name. They already know you exist.

Examples: "Outercite pricing," "Acme Accounting Melbourne hours," "is Brand X still operating."

Branded intent is about protecting your existing reputation. If a user asks an AI specifically about your business and the answer is vague, inaccurate, or omits you, that is a problem. Monitoring branded intent tells you whether AI engines have accurate, current information about your organisation.

A low confidence score on branded queries often means the AI has incomplete or outdated information about your business. This is worth investigating and fixing at the source, by improving your website's factual clarity and ensuring accurate business listings.

Why intent mix matters

Looking at total citation count can be misleading. A business might have a strong overall citation rate but win almost entirely on informational queries. That means AI engines know them as an educational resource, not as a place to buy.

The intent breakdown shows you where in the funnel you are visible and where you have gaps. A healthy funnel usually looks like this:

Intent type	What it means for your brand
Informational	Awareness and authority building
Comparison	Competitive positioning
Local	Capturing nearby, ready-to-act users
Buying intent	Direct commercial conversion
Branded	Protecting and informing existing customers

A brand with strong informational citations but weak buying-intent citations needs to improve its recommendation signals. A brand with strong buying intent but almost no informational citations may be winning short-term but failing to build authority that sustains long-term visibility.

How to use intent classification in Outercite

Your prompts dashboard lets you filter citations by intent type. Use that filter to:

Identify funnel gaps. If comparison-intent citations are low, look at which competitors are winning those answers and what content they have that you do not.
Prioritise content. If informational intent is strong but buying intent is weak, you may need clearer product or service pages that signal commercial context.
Set up targeted alerts. You can configure alerts to notify you when citation rates shift for a specific intent type. See set up alerts for the steps.

Try this in Outercite

Go to your prompts dashboard and group your keywords by intent type. Look at the citation rate for each group. Find the intent type with the biggest gap between your current rate and 100%, and start there. That is your highest-leverage area for content investment.