Topical map from a seed topic
Use when planning content coverage for a topic and you need a structure rather than a flat keyword list.
Fill in before running
Replace each placeholder with your own detail. The more specific you are, the less the model invents.
- {{SEED_TOPIC}}
- {{BUSINESS_MODEL}}
- {{AUDIENCE_LEVEL}}
- {{EXISTING_PAGES}}
Getting a better result
- Give it your existing URL list, otherwise it will happily recommend pages you published last year.
- The overlaps section usually finds cannibalisation faster than a rank tracker does.
- Take the table into your keyword tool afterwards to attach real volumes to titles it produced.
Questions about this prompt
When should I use this rather than a keyword list from a tool?
When the decision is how many pages to build and how they link, not which phrases have volume. A flat list gives no hierarchy and no view of what already competes. This returns a pillar definition, 15 to 25 clusters with intent and buyer stage, and the links up and across between them.
What do I need to hand before mapping the topic?
Your existing pages as a real URL list, the business model, and the audience expertise level. Without the URL list it will happily recommend pages you published last year. The business model matters because every cluster has to justify why it exists for you, not just why somebody might search for it.
What comes back, and where is the surprise usually?
The core entity and its required attributes, a pillar definition including what it must not cover, the cluster table, gaps, overlaps and a build order for the first six pages. The overlaps section is usually the surprise, since it spots cannibalisation from intent and titles before a rank tracker shows it.
What is the mistake people make with the cluster table?
Expecting volume or difficulty numbers in the table. The prompt refuses to output them because it cannot verify them, and anything it produced would be invented. Take the working titles into your keyword tool afterwards, attach real numbers there, and drop the clusters that turn out to have no demand.