Algorithm
Topical authority
The perceived depth and breadth of a domain's coverage of a topic. Post-HCU, depth + first-hand expertise are weighted more heavily than breadth.
What it is
The perceived depth and breadth of a domain's coverage of a subject, reflecting how thoroughly and credibly it addresses a topic and its subtopics. Since the helpful content shift, depth combined with first-hand expertise is weighted more heavily than sheer breadth.
Why it matters
Strong topical authority lifts rankings across a whole subject cluster and makes a domain a likelier source for AI-generated answers. It compounds, so authority earned on core subtopics raises the visibility of related pages.
How it works
It is built by covering a topic and its meaningful subtopics with genuine expertise, internal linking, and consistent intent fit, so the response is to map subtopics and fill gaps with substantive, experience-led content. Avoid padding the cluster with thin pages, which now dilutes rather than strengthens authority.
When it applies
It applies whenever a domain competes within a defined subject area or content cluster.
Examples
- A site that ranks for a head term and most of its supporting questions and subtopics.
- A specialist blog outranking a larger generalist site within its niche.
- A cluster gaining strength after deep guides replace a scatter of thin posts.
How it is measured
- Share of subtopic queries within a cluster where the domain ranks
- Internal link density and coherence across the cluster
- Proportion of the cluster's pages showing first-hand expertise
- Citation share within the topic on AI answer surfaces
Insights on Topical authority
Related terms in Algorithm
- Core updateA broad Google algorithm update affecting search rankings sitewide rather than a single feature. Recent core updates (e.g. May 2026) have increasingly favoured intent-aligned content over keyword-optimised content.
- EEATGoogle's quality framework: Experience, Expertise, Authoritativeness, Trustworthiness. EEAT signals are increasingly weighted in both classical ranking and AI Overview source selection.
- Entity salienceEntity salience is a measure of how central an entity is to a piece of content, as opposed to merely being mentioned in it. Natural language processing systems assign a salience score based on signals such as position, frequency, grammatical role and surrounding context. It helps a system decide what a document is actually about.
- Google Search algorithmThe Google Search algorithm is the collection of ranking and retrieval systems Google uses to find, order and present results for a query. It is not a single formula but many interacting systems that assess content, links, query intent, context and user signals. Google updates these systems continuously, with larger changes announced as core updates.
- Google Spam UpdateA Google Spam Update is a rollout of changes to the systems Google uses to detect and demote content that breaks its spam policies. These updates target things like scaled content abuse, cloaking, hacked pages, link schemes and site reputation abuse rather than general content quality. Sites hit by a spam update usually need to remove the offending practices before they can recover.
- Helpful Content UpdateGoogle's quality-focused update class targeting low-value, AI-generated, or thin content. Successive HCUs have favoured first-hand experience and named expertise over comprehensive but shallow coverage.
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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