Glossary

Topic cluster

A topic cluster is an SEO content architecture organized around a broad "pillar" page covering a central topic, surrounded by more specialized "cluster" pages that all link back to the pillar — a topical authority signal for Google.

Also known as

  • topic cluster
  • content cluster
  • content silo
  • pillar content

The topic cluster model was formalized by HubSpot in 2017 but traces back to the **SEO siloing** concept of the 2000s. The principle: Google rewards sites that demonstrate **deep expertise on a subject** rather than those that scatter content across heterogeneous themes. Architecture: 1 pillar page (~3,000-5,000 words, covering the topic broadly) + 10-30 cluster pages (~1,500-2,500 words each on a specific sub-topic) + dense internal linking between cluster ↔ pillar.

Measured benefits (HubSpot, Animalz, Backlinko): a site organized in topic clusters sees on average **+150% indexed pages in 6 months** and **+40% top 10 positions** compared to a flat architecture. The effect is especially pronounced for young sites (<2 years) that need to build topical authority against established competitors. pSEO and topic clusters are complementary: pSEO scales horizontally (long tail), clusters scale in depth (authority).

In the getchatsocial.com product

getchatsocial.com's SEO module explicitly includes `seo_build_topic_clusters`, which takes a subject and proposes a pillar + cluster architecture, and `seo_build_content_plan`, which breaks that architecture down into article briefs.

FAQ

  • What is the right length for a pillar page vs a cluster page?

    Pillar: 3,000-5,000 words, covering the topic broadly with sections per sub-topic (and an outbound link to each cluster page). Cluster: 1,500-2,500 words on a specific sub-topic, with a link back to the pillar in the first few paragraphs.

  • How many cluster pages should surround a pillar?

    10-30 cluster pages around a pillar is the effective range. Fewer than 10 = topical authority not dense enough. More than 30 = dilution and risk of keyword cannibalization between clusters.