Build a topical authority cluster from a seed keyword or topic. Use when the user asks about topic clusters, content silos, pillar pages, topical authority, content architecture, or how to structure content around a theme. For finding the right keywords, see find-keywords. For writing individual pie

Build Clusters Build a topical authority cluster from a seed keyword using pillar spoke structure, coverage scoring, and interlinking plans. What is a Topic Cluster? A topic cluster is a group of interlinked pages that collectively cover a subject area. Google evaluates topical authority at the cluster level — ranking a single page is harder if the site has no supporting content around the topic. Structure: Pillar page — comprehensive overview of the broad topic (targets head term) Spoke pages — focused articles covering subtopics (target body/long tail terms) Internal links — every spoke links to the pillar, pillar links to all spokes, spokes cross link to siblings Before You Start Gather this context (ask if not provided): 1. Seed topic. The broad subject area to build authority around. 2. Existing content. Does the site already have pages on this topic? List them. 3. Business relevance. How does this topic connect to the product or service? 4. Content capacity. How many pieces can the team produce per month? Step 1: Subtopic Discovery From the seed topic, generate subtopics using these methods: Search derived: People Also Ask questions for the seed keyword Related searches at the bottom of SERPs Autocomplete suggestions (seed + a, b, c...) Competitor content analysis — what subtopics do top ranking sites cover? Intent derived: Awareness: "what is [topic]", "why [topic] matters" Consideration: "best [topic] tools", "[topic] vs [alternative]" Implementation: "how to [topic]", "[topic] tutorial" Troubleshooting: "[topic] not working", "common [topic] mistakes" Audience derived: Beginner questions about the topic Advanced practitioner concerns Decision maker evaluation criteria Aim for 8 20 subtopics per cluster. Step 2: Cluster Map Organize subtopics into a structured cluster: Step 3: Coverage Scoring Score how well the existing site covers the cluster: Subtopic Existing Page? Quality (1 5) Traffic Gap? [subtopic 1] /blog/topic 1 4 500/mo No [subtopic 2] — — — Yes [subtopic 3] /blog/old post 2 50/mo Partial (needs refresh) Full gap — no existing page, needs creation Partial gap — page exists but is thin, outdated, or off intent Covered — strong existing page, may just need internal linking Step 4: Pillar Page Design The pillar page should: Cover the topic comprehensively at an overview level (2,000 4,000 words) Link to every spoke page for deeper dives Be structured as a table of contents for the entire cluster Target the highest volume keyword in the cluster Include a summary of each subtopic (2 3 paragraphs) with a link to the full spoke Pillar page is NOT a mega article that tries to cover everything in depth. It is a hub that distributes authority and directs readers to the right spoke. Step 5: Interlinking Plan Map the internal links: From Page To Page Anchor Text Context Pillar Spoke 1 "[subtopic 1] guide" In the subtopic 1 overview section Spoke 1 Pillar "[broad topic]" In the introduction or conclusion Spoke 1 Spoke 2 "[subtopic 2]" Where subtopic 2 is mentioned contextually Spoke 3 Spoke 1 "[subtopic 1]" Where comparison is relevant Rules: Every spoke links to the pillar (mandatory) Pillar links to every spoke (mandatory) Spokes cross link to 2 4 siblings (where contextually natural) Use varied anchor text (not always the exact keyword) Step 6: Cluster Health Metrics Score the cluster's readiness to compete: Metric Score Threshold Coverage [x]% 70% to start ranking for pillar keyword Link Health [x]% 100% is the target — every spoke must link to pillar and back Content Quality [x]% 80% — clusters with thin spokes dilute authority Expected Outcomes by Health Level Cluster State Coverage Link Health Content Quality Expected Result Incomplete <50% <70% Any Pillar unlikely to rank page 1; spokes rank individually at best Developing 50 70% 70 90% 50 80% Pillar may appear page 2 3; some spokes rank for long tail Competitive 70 90% 100% 80 90% Pillar competes for page 1; most spokes rank for their targets Dominant 90% 100% 90% Pillar strong on page 1; cluster captures most queries in the topic Internal Link Standards per Cluster Link Type Minimum Count Direction Pillar → each spoke 1 per spoke Downward — link from the relevant section of the pillar Each spoke → pillar 1 per spoke Upward — "our complete [topic] guide" Spoke ↔ sibling spokes 2 4 per spoke Lateral — where contextually natural Cross cluster bridges 0 2 per cluster Between hubs — only with genuine topical relevance Cluster ready to compete: Coverage 70%, Link Health = 100%, Content Quality 80%. Below these thresholds, prioritize filling gaps before expecting the pillar to rank. Step 7: Production Sequence Order the content production for maximum impact: 1. Pillar page first — even as a draft, it establishes the hub 2. Highest opportunity spokes next — pages targeting gaps with the best opportunity scores 3. Refresh existing spokes — update and relink any partial gap pages 4. Remaining spokes — fill out the cluster over time 5. Update pillar — add links to each new spoke as it's published Output Format Topic Cluster: [seed topic] Cluster Summary Pillar keyword: [keyword] (volume: [x], difficulty: [y]) Total spokes: [count] Existing coverage: [x]% ([n] pages exist, [n] need creation) Total cluster volume: [sum of all keyword volumes] Cluster Map [Visual structure from Step 2] Coverage Scorecard [Table from Step 3] Pillar Page Spec Target keyword: [keyword] Recommended title: [title] Structure: [heading outline with spoke links] Interlinking Plan [Table from Step 5] Production Roadmap [Ordered list from Step 6 with estimated timelines] Pro Tip: Use the free [Blog Keyword Generator](https://seojuice.com/tools/blog keyword generator/) to discover subtopics for your cluster. SEOJuice MCP users get automatic cluster mapping — run /seojuice:content strategy to see existing clusters with coverage metrics, or use list clusters and get cluster detail to check cluster health and identify gaps.

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