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⚡ Promptolis Original · Marketing & Content

📝 WordPress Content Cluster Strategist

Designs your topic cluster + pillar page + supporting articles for a chosen keyword theme — with the URL structure, internal linking pattern, and the 12-30 article roadmap that wins SEO in 2026 (not 2018 SEO advice).

⏱️ 5 min to set up 🤖 ~120 seconds in Claude 🗓️ Updated 2026-04-28

Why this is epic

Most WordPress content strategy is still '2018 SEO': stuff a keyword in a post, link to your homepage, hope. This Original designs the actual cluster: pillar page + 12-30 supporting articles + internal linking + entity-based structure that 2026 search engines reward.

Outputs the COMPLETE cluster: pillar topic, supporting article titles with brief outlines, target keywords with search-intent labels, internal link map, URL structure, and the publish sequence. Calibrated to YOUR niche + competition level + content capacity.

Calibrated to 2026 SEO realities: AI Overviews quote E-E-A-T-strong sources, Google's helpful-content updates penalize thin clusters, programmatic AI content gets penalized while genuine expert content surfaces. The strategy emphasizes depth over breadth.

Includes the AEO + GEO layer: which articles get FAQPage schema, which get DefinedTerm schema, which signals Anthropic Claude / OpenAI's web crawler will pick up. AI-citation traffic is real and growing.

The prompt

Promptolis Original · Copy-ready
<role> You are a content cluster strategist with 7+ years building topical authority for B2B SaaS, agencies, affiliate sites, and solo blogs. You have shipped 80+ cluster strategies; ~30 reached page 1 for the pillar keyword within 9 months. You know what works in 2026 — not what worked in 2018. You are direct. You will tell a builder their niche is too saturated to win, that their pillar topic is too broad, that 30 thin articles will get penalized while 12 deep articles will rank. You refuse to recommend keyword density, generic 'write more content,' or AI-generated 1500-word fluff posts. </role> <principles> 1. Pillar pages are 3000+ words, comprehensive, the deepest source on the topic. 2. Supporting articles target long-tail; each ranks for specific intent. 3. Internal linking is the cluster glue. Pillar↔supporting + sibling↔sibling where relevant. 4. Search intent > keyword volume. Match content type to intent. 5. Topical authority beats individual SEO tactics. Coverage depth signals competence. 6. FAQPage + HowTo schema for AEO/AI Overview visibility. 7. Refresh pillars quarterly. Stale content gets outranked by refreshed competitors. </principles> <input> <niche>{your industry/topic area — be specific. 'marketing' is too broad; 'B2B SaaS demand-gen for engineering teams' is winnable}</niche> <pillar-keyword>{the broad keyword you want to rank for}</pillar-keyword> <current-domain-authority>{rough DA — '20', 'new domain', '50+', etc.}</current-domain-authority> <existing-content>{posts already on the topic — paste 5-10 titles + URLs}</existing-content> <content-capacity>{articles per month + word count tolerance}</content-capacity> <competitor-landscape>{top 3-5 competing sites for the pillar keyword + their content depth}</competitor-landscape> <expertise-source>{who at your company will provide the actual expert content — internal SME, customer interviews, etc.}</expertise-source> <conversion-goal>{what content should drive — newsletter subs, demo requests, affiliate clicks, etc.}</conversion-goal> <timeline>{how long you have — 3 months / 6 months / 12 months}</timeline> <seo-tools>{Ahrefs / Semrush / GSC / nothing}</seo-tools> </input> <output-format> # Content Cluster: [pillar topic] ## Niche Suitability Check Is the niche winnable? If saturated, pivot recommendation. If too broad, narrow. ## The Pillar Page Pillar topic, target keyword, search intent, recommended URL, target word count, key entities to cover, the 8-12 H2 sections, the conversion CTA. ## Supporting Articles (12-30 articles) For each: title, URL, target keyword, search intent (informational / commercial / navigational / transactional), word count, brief outline (4-6 H2s), schema markup type, internal links to pillar + 1-2 siblings. ## Internal Linking Map Visual or text-based: pillar at center, supporting articles pointing to it. Sibling-to-sibling links where relevant. ## URL Structure Pattern for the cluster: /[topic-area]/[slug]/. URL stability rules. ## Publishing Sequence Week-by-week or month-by-month publish order. Pillar first or last? ## Schema Markup Strategy Per article type: which schema (Article, FAQPage, HowTo, DefinedTerm, ItemList, etc.). ## AEO + GEO Considerations AI Overview optimization. Anthropic / OpenAI / Perplexity citation strategy. ## E-E-A-T Strategy Author bios, credentials, expert review, source citations. How to signal expertise. ## Refresh Cadence When to update pillar + each supporting article. Annual refresh vs quarterly. ## Competitive Strategy Where your cluster will out-do existing top-ranking competitors. The specific gaps. ## What This Strategy Won't Do Honest limits. Saturated pillar keywords; lack of expertise input; pure AI-generated content. ## Implementation Cadence Weekly + monthly checklist for the cluster's 6-12 month build. ## Key Takeaways 4-6 bullets — for the team's content playbook. </output-format> <auto-intake> If input incomplete: ask for niche, pillar keyword, domain authority, existing content, capacity, competitors, expertise source, conversion goal, timeline, SEO tools. </auto-intake> Now, design the content cluster:
🚀 Open in ChatGPT ✨ Open in Claude 💎 Open in Gemini

Example: input → output

Here's how this prompt actually performs. Real input below, real output from Claude Opus 4.

📝 Input
<niche>B2B SaaS DevTools for engineering teams (specifically: incident response + on-call tooling for mid-size companies, 50-200 engineers).</niche>
<pillar-keyword>incident response best practices</pillar-keyword>
<current-domain-authority>22 (we're a 2-year-old startup, ~$1M ARR)</current-domain-authority>
<existing-content>5 posts: 'Why on-call sucks' (2K words), 'Our PagerDuty alternative' (1.5K), 'How we cut alert noise 60%' (3K, our best post), 'Setting up Slack for on-call' (1K), 'When to wake an engineer' (2K).</existing-content>
<content-capacity>1 article per week (4/month). Can produce up to 3000-word in-depth pieces. We have a content marketer + access to our 2 founders for SME interviews.</content-capacity>
<competitor-landscape>Top 3 for 'incident response best practices': PagerDuty (DA ~80, deep content but corporate-feeling), Atlassian (DA ~85, ITIL-focused, dated), incident.io (DA ~50, modern, very competitive). Below them: lots of older blog posts from individual engineers.</competitor-landscape>
<expertise-source>2 founders: ex-Stripe SRE + ex-PagerDuty PM. Strong domain credibility. Can do 1-hour SME interviews per article.</expertise-source>
<conversion-goal>Demo requests + newsletter signups. Newsletter is more important early-stage; demos pick up at month 6+.</conversion-goal>
<timeline>9 months. We want to be on page 1 for some part of this cluster by month 9.</timeline>
<seo-tools>Ahrefs subscription. GSC connected. Limited use so far.</seo-tools>
🤖 Output

Content Cluster: Incident Response Best Practices

Niche Suitability Check

The pillar keyword 'incident response best practices' is heavily contested at the head. PagerDuty + Atlassian rank top 3 with DA 80+. At DA 22, you won't displace them in 9 months for the head term.

Recommendation: shift to a winnable narrower angle. Specifically: 'incident response best practices for mid-size engineering teams' or 'modern incident response best practices' (the 'modern' framing positions you against the dated Atlassian content).

Why this works:

  • Mid-size teams (50-200 engineers) is your actual customer profile — content authority maps to product authority
  • 'Modern' positions you against ITIL-flavored content that's increasingly outdated
  • incident.io (DA 50) is your real competitor here, not PagerDuty
  • Your founders' credibility (Stripe + PagerDuty) is uniquely strong for THIS framing

Pillar keyword pivot: 'modern incident response best practices' (combined with 'incident response for engineering teams' as a secondary cluster).

The Pillar Page

Title: 'Modern Incident Response: A 2026 Playbook for Engineering Teams (50-200 People)'

URL: /incident-response/

Target keyword: modern incident response best practices (sub-targets: incident response for engineering teams, incident response playbook, 2026 incident response)

Search intent: Informational + comparative. Reader is researching how to set up or improve incident response.

Word count target: 4,500-6,000 words. (Your existing 'How we cut alert noise 60%' at 3K is the proof you can produce depth.)

Key entities: SLO, incident commander, runbook, blameless postmortem, alert fatigue, MTTR, MTTD, on-call rotation, escalation policy, paging, Slack, PagerDuty, incident.io, your-product-name.

The 10 H2 sections:

1. What's changed since 2020 (set the 'modern' frame)

2. The 4 phases of modern incident response (preparation, detection, response, learning)

3. Setting up a real on-call rotation (not the bad version most companies have)

4. Alert design: separating signal from noise (link to your existing 'cut alert noise 60%' post)

5. Runbooks: when they help vs hurt

6. The incident commander role at mid-size teams

7. Blameless postmortems that actually drive change (not theater)

8. Tooling stack for 2026: what to use + what to skip

9. Common anti-patterns (the on-call rotations that destroy retention)

10. The 90-day implementation plan (your CTA bridge — readers need this)

Conversion CTA: Newsletter signup ('Get our weekly incident-response playbook') + secondary 'Book demo' for products page.

Supporting Articles (16 articles total — your 9-month capacity is ~36; quality over quantity)

Phase 1 — Foundational pillar support (months 1-3, 12 articles)

Article 1: 'How to Run a Blameless Postmortem (with Template)'

  • URL: /incident-response/blameless-postmortem-template/
  • Keyword: blameless postmortem template
  • Intent: informational + transactional (template downloads)
  • Word count: 2500
  • H2s: What blameless means; common failures; the 6-section template; facilitation tips; example excerpts; downloadable template
  • Schema: HowTo + downloadable lead-magnet
  • Links: → Pillar, → Article 4, → Article 7

Article 2: 'On-Call Rotation Schedules: Patterns That Don't Burn Out Engineers'

  • URL: /incident-response/on-call-rotation/
  • Keyword: on-call rotation schedule
  • Intent: informational
  • Word count: 2500
  • H2s: Why rotations break; 5 rotation patterns (with pros/cons); calibrating frequency to team size; integrating with PTO; tools; what to measure
  • Schema: Article + ItemList for the 5 patterns
  • Links: → Pillar, → Article 3, → Article 12

Article 3: 'Reducing Alert Fatigue: A Practical Guide for SREs'

  • URL: /incident-response/alert-fatigue/
  • Keyword: alert fatigue
  • Intent: informational
  • Word count: 2800
  • H2s: What alert fatigue is; the cost (specifically retention); 7 techniques to reduce; case study (your 60% cut); when to use AI triage; how to measure
  • Schema: Article + your existing 'cut alert noise 60%' as case study source
  • Links: → Pillar, → existing 'How we cut alert noise 60%' (refresh + integrate), → Article 8

Article 4: 'The Incident Commander Role: A Guide for Engineering Managers'

  • URL: /incident-response/incident-commander/
  • Keyword: incident commander
  • Intent: informational
  • Word count: 2200
  • H2s: What an IC does; choosing ICs; training; rotation; common IC mistakes; templates for IC handoff
  • Schema: Article
  • Links: → Pillar, → Article 1, → Article 9

Article 5: 'Modern Runbook Best Practices (Beyond Wikis That Nobody Reads)'

  • URL: /incident-response/runbooks/
  • Keyword: incident response runbook
  • Intent: informational
  • Word count: 2400
  • H2s: Why most runbooks fail; 4 runbook formats; auto-generated vs human-written; embedded in alerts; refreshing
  • Schema: Article
  • Links: → Pillar, → Article 4, → Article 10

Article 6: 'MTTR vs MTTD: Which Metric Matters More? (And Why That's the Wrong Question)'

  • URL: /incident-response/mttr-vs-mttd/
  • Keyword: MTTR vs MTTD
  • Intent: informational + comparison
  • Word count: 2000
  • H2s: Definitions; what each measures (and doesn't); why MTTR-only optimization fails; the metrics that actually matter; how to instrument
  • Schema: Article + FAQPage
  • Links: → Pillar, → Article 7

Article 7: 'SLOs for Engineering Teams: A Practical Guide (No Math PhD Required)'

  • URL: /incident-response/slo-guide/
  • Keyword: service level objectives engineering
  • Intent: informational
  • Word count: 3000
  • H2s: SLO vs SLI vs SLA; choosing the right SLOs; error budgets; example SLOs by service type; iterating; tooling
  • Schema: Article + DefinedTerm for SLO/SLI/SLA
  • Links: → Pillar, → Article 6, → Article 11

Article 8: 'When to Wake an Engineer: A Severity Decision Framework'

  • URL: /incident-response/severity-framework/
  • Keyword: incident severity levels
  • Intent: informational
  • Word count: 2200
  • H2s: Severity model basics; SEV1-SEV5 explained; mapping to paging behavior; common mistakes; templates
  • Schema: Article + ItemList
  • Links: → Pillar, → existing 'When to wake an engineer' (consolidate or update + redirect)

Article 9: 'PagerDuty vs incident.io vs Modern Alternatives: 2026 Buyer's Guide'

  • URL: /incident-response/pagerduty-alternatives/
  • Keyword: pagerduty alternatives
  • Intent: commercial (high conversion potential)
  • Word count: 3500
  • H2s: How to evaluate; PagerDuty (current state); incident.io (mid-market focus); other tools; your-product-name; selection framework
  • Schema: Article + Product (your tool) + comparison table
  • Links: → Pillar, → Product page, → Article 14

Article 10: 'Incident Response Templates: Postmortems, Runbooks, and War Room Notes'

  • URL: /incident-response/templates/
  • Keyword: incident response template
  • Intent: transactional (template downloads)
  • Word count: 2000
  • H2s: 5 templates with explanations + downloads; how to customize; when each is used
  • Schema: Article + ItemList + lead-magnet
  • Links: → Pillar, → Article 1, → Article 5

Article 11: 'How to Measure Your Incident Response Maturity (with Self-Assessment Quiz)'

  • URL: /incident-response/maturity-assessment/
  • Keyword: incident response maturity
  • Intent: informational + interactive (high engagement)
  • Word count: 2200 + interactive quiz
  • H2s: 5 maturity stages; signals at each stage; assessment quiz; what to fix at each level
  • Schema: Article + Quiz schema
  • Links: → Pillar, → Article 7

Article 12: 'On-Call Compensation: How Companies Pay for Pager Duty in 2026'

  • URL: /incident-response/on-call-compensation/
  • Keyword: on-call compensation
  • Intent: informational (HR + eng leaders search this)
  • Word count: 2400
  • H2s: Why this matters now; common models (flat-rate, hourly, time-off); benchmarks by company size; legal considerations; case studies
  • Schema: Article
  • Links: → Pillar, → Article 2
Phase 2 — Comparison + commercial intent (months 4-6, 4 articles)

Article 13: 'Slack-Based Incident Response: Setup Guide'

  • URL: /incident-response/slack-setup/
  • Keyword: slack incident management
  • Intent: informational + commercial
  • Word count: 2500
  • Links: → Pillar, → Product, → Article 9

Article 14: 'Incident.io Review: Honest Take from a Mid-Size Engineering Team'

  • URL: /incident-response/incident-io-review/
  • Keyword: incident.io review
  • Intent: commercial
  • Word count: 2800
  • Links: → Pillar, → Article 9

Article 15: 'Buying On-Call Tooling: A Procurement Guide for Engineering Leaders'

  • URL: /incident-response/buying-guide/
  • Keyword: on-call tool buying guide
  • Intent: commercial
  • Word count: 3000
  • Links: → Pillar, → Article 9, → Product

Article 16: 'PagerDuty AIOps vs Modern AI-Native Incident Tools'

  • URL: /incident-response/pagerduty-aiops-vs-ai-native/
  • Keyword: pagerduty aiops alternatives
  • Intent: commercial
  • Word count: 2500
  • Links: → Pillar, → Article 9, → Product

Internal Linking Map

                  [PILLAR: Modern Incident Response]
                          ↑ (every article)
            ┌─────────────┼──────────────┐
            │             │              │
     [Foundational]  [Tactical]    [Commercial]
     1, 2, 3, 4, 5     6, 7, 8     9, 13, 14, 15, 16
     11, 12              10

Each supporting article has 2-3 internal links: 1 to pillar (mandatory) + 1-2 to relevant siblings.

URL Structure

Pattern: /incident-response/[slug]/

All cluster URLs under /incident-response/. Stable. The pillar at /incident-response/ itself.

If migrating existing posts: use 301 redirects from old URLs to new cluster-aware URLs.

Publishing Sequence

Month 1: Pillar (week 4 publish, week 1-3 write). Plus Articles 1, 2 (weeks 1-2 publish — Phase-1 priority).

Month 2: Articles 3, 4, 5, 6.

Month 3: Articles 7, 8, 9 (commercial — high conversion), 10.

Month 4: Articles 11, 12, 13, 14.

Month 5: Articles 15, 16. + first quarterly refresh of pillar based on Search Console data.

Month 6-9: monitor + iterate. Add articles addressing emerging questions from comments / user feedback / Search Console queries.

Why pillar publishes month 1 (not last): counter to some advice. Reasons: (a) builds the core URL + earns foundational backlinks early, (b) gives you real SC data to refine supporting articles, (c) you can already link FROM existing posts TO pillar on day 1.

Schema Markup Strategy

  • Pillar: Article + FAQPage (with 8-10 Q&As of common reader questions)
  • Foundational articles (1-8): Article + (FAQPage if Q&A-heavy, HowTo if process-heavy, ItemList if list-heavy)
  • Templates (1, 10): Article + lead-magnet markup (offer-attached) + downloadable file schema
  • Comparison (9, 14, 16): Article + Product + Review (where applicable)
  • Definition-heavy (7): Article + DefinedTerm for key entities (SLO, SLI, SLA)

AEO + GEO Considerations

For AI Overview / Claude / ChatGPT citation:

1. Direct-answer paragraphs at top of each article. First 2 paragraphs answer the search query directly. AI tools quote these.

2. FAQPage schema with crisp Q&A. Ensures structured questions appear in AI training and rich results.

3. Author E-E-A-T: founder bios with credentials (ex-Stripe, ex-PagerDuty) should appear on author pages with Person schema. AI tools weight authorship for citation.

4. Citations to authoritative sources (Google SRE Book, Atlassian/PagerDuty research, your own data). AI tools prefer well-cited sources.

5. llms.txt at root listing your top 5 cluster pillar pages. Increasing AI-crawler discovery.

For maximum AI Overview visibility, the AEO-Optimized Mode variant adds detailed Q&A structure.

E-E-A-T Strategy

Author bios (each article): detailed founder bios with prior roles, years in the space, and 1-2 specific credentials. Person schema on author pages with sameAs links to LinkedIn + Twitter.

Source citations: every claim citing benchmarks, research, or competitive data → cite explicitly with link. Inline citations build credibility.

Customer references: 'one of our customers reduced X by Y%' is more authoritative than 'studies show.' Use real examples (with permission).

Update transparency: every article shows 'Last updated: [date]' prominently. Refreshed dates are E-E-A-T signals.

Refresh Cadence

Pillar: Every 90 days. Update: stats, tools mentioned, examples, any sections that aged. Adds 'Updated: [date]' signal.

Foundational supporting articles: Every 6 months. Lighter updates.

Comparison/commercial articles: Every 90 days (vendors change features fast).

Refresh triggers:

  • Competitor publishes a 'better' version → refresh + add depth they don't have
  • Major industry shift (new tool, new methodology) → update affected articles
  • Search Console shows ranking decay → refresh that specific article

Competitive Strategy

Where you out-do existing competitors:

  • Vs PagerDuty content: they're corporate-tone + ITIL-flavored. You're founder-voice + SRE-influenced. Mid-size readers prefer your voice.
  • Vs Atlassian content: dated. Your 'modern' framing + 2026 references makes their content look stale.
  • Vs incident.io: they're competitive in this space. You differentiate by founder credibility (specific names + roles) + customer-grounded examples vs their more generic content.

Specific gaps in their content:

1. None of them have a deep 'on-call compensation' article (Article 12). You can own this.

2. Atlassian's runbook content is dated. Your modern angle wins.

3. None have an interactive maturity assessment (Article 11). High-engagement uniqueness.

What This Strategy Won't Do

  • Won't outrank PagerDuty for 'incident response' (head term). That's a 5-year fight at DA 22. The pivot to 'modern' + mid-team-size is the realistic win.
  • Won't replace product marketing. Cluster builds top-of-funnel awareness. Your demos still convert via product + sales.
  • Won't work without expert input. If founder interviews skip month 3+, content drifts to AI-generated 'fluff.' Expert-grounded depth is the moat.
  • Won't show ROI in month 1-3. Cluster strategies see real traffic at month 6+. Set expectations.
  • Won't fix poor on-page SEO basics. Verify: every article has proper H1/H2 hierarchy, image alt text, internal links, fast page speed, mobile-responsive.

Implementation Cadence

Weekly:

  • 1 article published (Phase 1 publish schedule)
  • Internal linking sweep: did this week's article get linked from older articles? Did it link out properly?
  • Search Console check: any ranking shifts?

Monthly:

  • Refresh date stamps on articles touched
  • Newsletter to subscribers featuring 2-3 cluster articles
  • Backlink check (Ahrefs): any new domains linking? Any link opportunities to pursue?
  • Internal linking audit: orphaned articles?

Quarterly:

  • Pillar refresh
  • Cluster expansion review: which new articles to add based on Search Console queries?
  • Competitive monitoring: did any competitor publish something we should respond to?
  • E-E-A-T audit: bios, schema, source citations all in place?

Key Takeaways

  • Pivot pillar from 'incident response best practices' to 'modern incident response for engineering teams.' At DA 22, the broader head term is unwinnable in 9 months.
  • 16 deep articles beats 30 thin ones. Quality over breadth in 2026 SEO.
  • Pillar publishes Month 1, not last. Builds foundational link target + gives Search Console data to refine supporting articles.
  • FAQPage + HowTo schema on every article. Direct-answer paragraphs at top. Optimizes for AI Overview citation.
  • Founder credibility (ex-Stripe + ex-PagerDuty) is a unique E-E-A-T moat. Lean on it heavily — author bios, customer-grounded examples, specific data.
  • Refresh pillar quarterly. Stale content gets outranked by refreshed competitors. Expect real traffic ROI at month 6+.

Common use cases

  • B2B SaaS marketing team building thought leadership in a specific niche
  • Solo blog operator picking a niche + building topical authority efficiently
  • Agency planning a 6-month content sprint for a client
  • Founder evaluating whether their niche is winnable or already saturated
  • Content marketer migrating from 'random posts' strategy to a structured cluster strategy
  • Marketing team competing against larger sites in a specific topic area

Best AI model for this

Claude Opus 4. Cluster strategy needs reasoning about search intent, competitive landscape, and topical authority — exactly Claude's strengths. ChatGPT GPT-5 second-best.

Pro tips

  • Pillar pages need to be the deepest, most comprehensive piece. 3000+ words minimum. They earn the rankings + supporting articles funnel toward them.
  • Supporting articles target long-tail variations of the pillar topic. Each ranks for 1-3 specific queries; the pillar ranks for the broad query.
  • Internal linking is the unsung hero. Every supporting article links to the pillar. The pillar links to all supporting. Sibling articles link to each other when relevant.
  • Search intent matters more than keyword volume. 'best [tool]' is different intent from '[tool] vs [other tool]' from 'how to [task]'. Match your content type to intent.
  • Don't chase 1.0% keyword density. That's 2018 advice. Modern search reads context + entities + topical authority — keyword stuffing actively hurts.
  • FAQPage + HowTo schema markup shows up in AI Overviews and rich results. Add to every supporting article where applicable.
  • Update old pillar pages quarterly. Refreshed content with current dates outranks stale content. Don't let your best pillar age.

Customization tips

  • Be honest about your domain authority and existing content depth. The strategy calibrates against realistic ranking timelines — DA 22 needs different tactics than DA 60.
  • List your top 3-5 actual competitors and their content strength. The cluster strategy positions specifically against them, not against generic 'big sites.'
  • Specify your expertise source. Without expert input (SME interviews, real customer data), the cluster becomes generic AI-content, which gets penalized.
  • Be precise about content capacity (articles/month). 16-article clusters take 4-6 months at 1/week; 30-article clusters take 12+ months. Match scope to capacity.
  • Specify your conversion goal. Newsletter-focused clusters and demo-focused clusters have different content-to-CTA mappings.
  • Use the AEO-Optimized Mode variant if AI Overview citation is important — it adds the FAQ structure, schema markup, and authoritative citation patterns AI tools prefer.

Variants

B2B SaaS Mode

For SaaS marketing — emphasizes pain-point clusters that map to your product, solution-aware vs problem-aware content.

Solo Blog Mode

For 1-person content operations — minimum-viable cluster (8-12 articles) that's achievable in 4-6 months.

Affiliate / Comparison Mode

For affiliate sites — emphasizes 'best of' + comparison + 'vs' content with disclosure-aware structure.

AEO-Optimized Mode

Specifically optimized for AI Overview citations and Claude/ChatGPT visibility — emphasizes structured Q&A, schema, and authoritative tone.

Frequently asked questions

How do I use the WordPress Content Cluster Strategist prompt?

Open the prompt page, click 'Copy prompt', paste it into ChatGPT, Claude, or Gemini, and replace the placeholders in curly braces with your real input. The prompt is also launchable directly in each model with one click.

Which AI model works best with WordPress Content Cluster Strategist?

Claude Opus 4. Cluster strategy needs reasoning about search intent, competitive landscape, and topical authority — exactly Claude's strengths. ChatGPT GPT-5 second-best.

Can I customize the WordPress Content Cluster Strategist prompt for my use case?

Yes — every Promptolis Original is designed to be customized. Key levers: Pillar pages need to be the deepest, most comprehensive piece. 3000+ words minimum. They earn the rankings + supporting articles funnel toward them.; Supporting articles target long-tail variations of the pillar topic. Each ranks for 1-3 specific queries; the pillar ranks for the broad query.

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