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@bdb4922

Use when writing a complete SEO article. Includes the full anti-AI-slop ruleset (banned vocabulary, banned phrases, banned structural patterns) and voice rules. The agent researches the SERP itself if needed — no keyword data exports required.

Use this Skill: https://skilld.dev/gh/inhouseseo/superseo-skills/write-content

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referencescontent-typescomparison.md

≈1.4k tokens on demand. Your agent reads this file only when SKILL.md points to it.

Technique 26: X vs Y Comparison Articles

What It Is

Commercial investigation content comparing two specific options side-by-side. Captures "[Product A] vs [Product B]" and "[A] of [B]" searches. One of the highest-converting content types in SEO.

When to Use

Commercial investigation intent -- user is deciding between two specific options they already know about. These users are close to a purchase decision.

Structure Template (10-Section Framework)

H1: "[Product A] vs [Product B]: [Outcome promise]"
    (e.g., "Vattenfall vs Eneco: welke is goedkoper in 2026?")

H2: Quick verdict (above the fold)
    "Choose A if..." / "Choose B if..."
    Maximum 4 bullet points per option

H2: At-a-glance comparison table
    4-6 key criteria in a clean table format
    Bold the winner per row

H2: How we compared (methodology transparency)
    1-2 paragraphs explaining evaluation criteria and process
    E-E-A-T signal: shows expertise and transparency

H2: Head-to-head by criteria
    H3: Criterion 1: [Category name]
        Verdict first: "[A] wins on [criterion] because..."
        Detailed analysis with specific data
    H3: Criterion 2: [Category name]
        Same pattern: verdict first, then evidence
    H3: Criterion 3-6: ...

H2: Use cases
    3-5 real-world scenarios with recommendation per scenario
    "If you [situation], choose [option] because [reason]"

H2: Pros and cons
    Specific, honest pros and cons for each option
    Not generic -- tied to real features and real limitations

H2: Pricing comparison
    12-month total costs with gotchas/hidden fees
    Table format: plan names, monthly cost, annual cost, what's included

H2: FAQ
    Pre-purchase questions, 2-4 sentences each
    Common: "Is [A] worth the extra cost?" "Can I switch from [A] to [B]?"

H2: Final recommendation
    Clear recommendation with nuance per use case
    CTA to relevant conversion page

Word Count

1,200-2,500 words

Schema Markup

  • Primary: FAQ (for FAQ section)
  • Secondary: Product (for both items compared)

Featured Snippet Strategy

  • Format: Table snippet (comparison queries strongly trigger tables)
  • Target: The at-a-glance comparison table
  • Alternative: Paragraph snippet for the quick verdict

CTA Placement

  • After quick verdict (above fold -- highest conversion point)
  • After final recommendation (bottom -- for readers who read through)
  • Inline within pricing section

Internal Linking Strategy

  • Link to individual review articles for each product
  • Link to "best of" roundup for the category
  • Link to "alternatives to" pages for each product
  • Link to buying guide for the category
  • Receive links from pillar page and individual reviews

Key Success Factors

  1. Lead with the verdict: Never make readers scroll to find which is better
  2. Verdict-first per criterion: Each H3 section starts with who wins and why
  3. Consistent criteria: Apply the exact same evaluation framework to both options
  4. Real pricing with gotchas: Include hidden fees, price increases, contract terms
  5. Use case matching: Specific scenarios ("If you're a family of 4 in an apartment...")
  6. Honest limitations: Acknowledge what each option does poorly (builds trust)
  7. Methodology section: How and why you compared these criteria (E-E-A-T signal)

Common Mistakes

  • Not leading with the verdict (the #1 mistake)
  • Inconsistent evaluation criteria between products
  • No pricing transparency or missing total cost of ownership
  • Obviously biased toward one product without declaring it
  • Generic feature lists without real-world context
  • Missing the methodology section (undermines trust)
  • No use-case scenarios (readers can't self-select)

Anti-AI Focus

Evidence of actual usage is the strongest signal. Screenshots of dashboards, specific feature interactions, support experience anecdotes. AI can't fabricate these convincingly.

To make comparison articles unmistakably experience-based:

  • Include screenshots of both products. Show the actual interface, dashboard, or configuration screen you encountered. Annotate screenshots to highlight differences. AI cannot generate authentic product screenshots.
  • Describe specific interactions with support. "When we contacted Eneco's support about a billing discrepancy, the response came within 2 hours via their app chat" is verifiable and specific in a way AI cannot replicate.
  • Reference your testing methodology with dates. "We signed up for both services in January 2026 and tracked costs over 3 months" establishes a timeline of actual usage.
  • Note UI quirks, bugs, or friction points. "The Vattenfall app crashes when switching between monthly and annual views on iOS 18" -- these micro-observations come only from real usage.
  • Compare what the marketing says vs. what you experienced. "Eneco advertises 'fixed pricing,' but the contract allows for a 5% annual adjustment" -- this kind of fine-print analysis signals thorough, hands-on evaluation.
  • Include customer service response times and quality. Document actual wait times, resolution quality, and communication style from real interactions.

Example Topics by Niche

  • Energy: "Vattenfall vs Eneco vergelijken: prijs, service en duurzaamheid"
  • Telecom: "KPN vs Ziggo 2026: welke is beter voor glasvezel?"
  • SaaS: "HubSpot vs Salesforce: which CRM fits your business?"
  • E-commerce: "Shopify vs WooCommerce: wat is beter voor een webshop?"
  • Finance: "ABN AMRO vs ING hypotheek vergelijken"

Source: SKILL.md on GitHub

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    The skill provides a detailed multi-phase framework for researching and generating SEO-optimized articles while minimizing common AI writing patterns. It ingests and processes external data from search engine results and competitor web pages, creating a standard indirect prompt injection surface area. No malicious behaviors, obfuscation, or unauthorized access patterns were detected.

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