Cannibalization Audit

Find pages that are cannibalizing each other

Combine vector similarity with Search Console query overlap to detect pages competing against each other - then give your team the data to decide what to consolidate, redirect, or differentiate.

Cannibalization Audit· running
Find pages that are cannibalizing each other on commercial queries.
read_corpus-Loaded 1,247 indexed pages
embed_pages-Generated 3,072-dim embeddings · pairwise cosine on top quartile
read_search_console-Joined 90-day shared-query overlap per pair
score_cannibalization-47 pairs · 12 actively splitting clicks
For the /seo pair, which one should win?
Ask about your website content…
SerpAPISearch ConsoleAI Overview & Snippet Capt…
Claude Sonnet
AI-generated answers can be wrong or incomplete. Verify anything important before you rely on it.

Illustrative preview - actual platform experience may differ.

How it works

How it works

Two signals that reveal cannibalization: semantic similarity and query overlap.

01

Index & connect

Crawl your site into the vector database and connect Search Console. Morrison has both content similarity and query performance data.

02

Detect overlaps

Build workflows that use vector similarity to find near-duplicate pages and cross-reference Search Console queries to check for impression splitting.

03

Analyze & report

The AI assesses each overlap and provides analysis with the competing pages, shared queries, and context your team needs to decide next steps.

Capabilities

What you can do

Vector similarity matching

The vector index identifies pages that are semantically near-identical. Surface content that covers the same ground from different URLs.

Query overlap detection

Cross-reference Search Console data to find pages competing for the same queries. See where Google is splitting impressions between your own pages.

Cannibalization impact assessment

Ask the AI to assess the impact of each overlap based on Search Console data - helping your team prioritize the cases that matter most.

Cluster-level analysis

Go beyond page pairs. Identify entire topic areas where you have multiple overlapping pages and need to consolidate or differentiate.

Intent overlap detection

Ask the AI to analyze whether competing pages target the same search intent or genuinely serve different purposes. Not all overlap is cannibalization.

Consolidation recommendations

Get structured reports showing which pages overlap, their respective performance, and whether to merge, redirect, or differentiate - for your team to decide.

FAQ

Frequently asked questions

What is keyword cannibalization?

Keyword cannibalization occurs when multiple pages on your site compete for the same search queries. This splits ranking signals, confuses search engines, and often results in neither page ranking as well as a single consolidated page would.

How does Morrison detect keyword cannibalization?

Morrison combines vector similarity analysis (finding semantically similar pages) with Search Console query overlap data (pages ranking for the same terms). This dual approach catches cannibalization even when pages use different wording.

What should I do when I find cannibalized pages?

Common fixes include consolidating pages into one stronger piece, adding canonical tags, differentiating content to target distinct intents, or redirecting the weaker page to the stronger one. Morrison helps you identify the issue – your team decides the best fix.

Closed Beta

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Morrison helps your team manage and optimize content at scale. Join the waitlist to get early access.

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