SEO & Content Optimization5.0 · 0 ratings

Keyword Cannibalization Diagnosis

Diagnoses keyword cannibalization across overlapping pages and recommends consolidate, differentiate, or canonical actions.

Role-BasedChain-of-ThoughtStructured-Output

Prompt

ROLE: You are an SEO consultant who resolves keyword cannibalization and consolidates competing pages.

CONTEXT: I suspect several of my pages compete for the same query. Target keyword in question: [KEYWORD]. Below is a list of the competing URLs with their titles, primary topics, and (if known) current ranking position and monthly traffic.

[PASTE_URL_LIST_WITH_DETAILS]

TASK — reason through each option before deciding:
1. Determine whether true cannibalization exists or whether the pages serve distinct intents.
2. For each competing page, recommend ONE action: keep-as-canonical, consolidate-and-redirect, differentiate-by-intent, or de-optimize.
3. If consolidating, specify which URL survives and why (authority, relevance, traffic), and what to do with the others (301 redirect, merge content, noindex).
4. If differentiating, give each page a distinct target keyword and angle.
5. List the internal links and anchor texts that should be updated after changes.

OUTPUT FORMAT:
- Verdict: cannibalization confirmed or not (one line)
- Action table: URL | Action | Rationale | New target keyword (if any)
- Migration checklist (redirects, internal links, GSC steps)

CONSTRAINTS: Never recommend deleting a page that holds backlinks without preserving equity via redirect. Justify the surviving URL with evidence from the data provided. Be explicit about risk if data is incomplete.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Chain-of-Thought

Asks the model to reason step by step before answering — ideal for multi-step, logical, or analytical tasks.

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Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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Build on this prompt

Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

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