Semrush's explanation of topic clusters describes a structure most trade businesses are not using. It fits their situation well: one strong pillar page on a subject, supported by several linked subpages. Each subpage covers one genuine angle of the topic in depth.
What a cluster looks like for a trade business
Take boiler installation as an example. Instead of one page trying to cover cost, timeline, signs of failure, and certification requirements all at once, a cluster splits the topic up. It uses a main pillar page plus focused subpages.
- A pillar page: "Boiler Installation: What to Expect", linking out to each subpage
- A subpage on typical cost ranges and what affects them
- A subpage on realistic installation timelines
- A subpage on the warning signs that a boiler needs replacing rather than repairing
- A subpage on the certifications an installer should hold, and how to check them
Each subpage links back to the pillar, and the pillar links out to every subpage. That internal linking signals something to Google: this is a genuinely comprehensive resource on the topic. It is not a single thin page competing against dozens of similar pages elsewhere.
This is also how AI tools answer questions
This structure maps closely onto the fan-out query behaviour covered in our guide on what Google and ChatGPT's recent warnings mean for trade businesses. When an AI tool fans out a single question into several related searches, a business with a genuine content cluster has an advantage. It usually has something relevant to surface for most of those related searches. A business with one thin page on the topic usually does not.
Building a cluster takes longer than writing one page and moving on. It is a more realistic way to build the kind of content depth that Google and AI tools are increasingly rewarding.