Duplicate Content Detection

Detect duplicate and near-duplicate content

Use vector similarity to find pages that cover the same ground - even when the wording is completely different. Ask the AI to assess overlap and recommend next steps.

Duplicate Content Detection· running
Find near-duplicate pages on our site - even when wording differs.
read_corpus-Loaded 1,247 indexed pages with body-only content slices
embed_pages-Generated 1,247 × 3,072-dim semantic embeddings
compute_overlap-Cosine similarity matrix · threshold 0.72 for candidates
score_consolidation-17 high-sim pairs · 28 watch · 12 cross-section
For the merge candidates - which URL should we keep based on performance?
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

Vector embeddings make duplicate detection semantic, not just textual.

01

Embed everything

Morrison embeds every crawled page into a vector database, capturing meaning rather than just keywords.

02

Find similarity

Ask the AI to find pages with high semantic overlap. It compares content meaning, not just word matching.

03

Decide & consolidate

The AI suggests whether to merge, redirect, or differentiate - with Search Console performance data to guide the decision.

Capabilities

What you can do

Vector similarity matching

Every page is embedded in the vector database. Ask the AI to find content pairs that are semantically near-identical even when the wording differs.

Near-duplicate flagging

Surface pages that cover the same topic from slightly different angles. The AI explains exactly what overlaps and what's unique to each.

Cross-section detection

Find duplicates that span different site sections - like a blog post and a docs page covering the same content independently.

Similarity analysis

Ask the AI to assess semantic similarity between page pairs. Focus on the highest-overlap content first for consolidation.

SEO impact assessment

Cross-reference duplicates with Search Console data to understand which version performs better and what traffic is at risk from consolidation.

Consolidation recommendations

For each duplicate pair, the AI suggests whether to merge, redirect, or differentiate - based on content uniqueness and performance.

FAQ

Frequently asked questions

How does Morrison detect duplicate content?

Morrison uses vector similarity to find pages that cover the same ground – even when the wording is completely different. This catches semantic duplicates that traditional text-matching tools miss.

What's the difference between duplicate and cannibalized content?

Duplicate content means two pages say essentially the same thing. Cannibalization means two pages target the same keywords but may have different content. Both hurt SEO, but they require different fixes.

What should I do with duplicate pages?

Options include consolidating into a single stronger page, adding canonical tags to point to the preferred version, differentiating the content to serve distinct user intents, or redirecting one page to the other.

Closed Beta

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