Product Cannibalization
Find product pages on your site competing for the same queries.
Product list
One per line: URL | feature keywords | sales/clicks
Product cluster 1 (4 variants)
Product cluster 2 (2 variants)
Product cluster 3 (2 variants)
Start here · What is product cannibalization?
Multiple SKUs can satisfy the same shopper query when titles and bullets reuse the same phrases. Internal search and Google may rank the wrong PDP.
Each line is URL | feature keywords | sales-or-clicks. Tokens strip punctuation and stopwords before similarity math.
The tool unions SKUs whose Jaccard similarity clears your threshold, picks the highest metric SKU as primary, and surfaces shared tokens that explain the collision.
When to use this tool
- Variant sprawl cleanup
Wide versus mid versus low cuts of the same boot might share nearly identical descriptive tokens.
- Marketplace seller hygiene
Detect duplicate listings that compete for the same long-tail modifiers.
- Merchandising strategy
Decide which SKU keeps the head term and which needs differentiated positioning or canonical policy.
- Data science handoffs
Export clusters for finance teams comparing revenue concentration across near-duplicate PDPs.
Examples
Walk through these with the form above — they are practice scenarios, not live data.
Adjust sensitivity
Try this
Drag Similarity threshold down to 0.35 to see looser clusters; raise toward 0.8 for strict matches.
What to look for
Conflict cards grow or shrink depending on how aggressively you define duplication.
Primary selection
Try this
Ensure sales numbers reflect your analytics—not future forecasts—before trusting the primary badge.
What to look for
Highest sales URL becomes primary; others get consolidate guidance that still needs merchandiser judgement.
Short tutorial
Follow in order the first time you use the tool; later you can skip to the step you need.
- Step 1 — Build the paste file
One PDP per line with human-readable keyword phrases and a numeric performance metric.
- Step 2 — Normalize phrases honestly
If two rows share marketing fluff only, they may cluster unfairly. Edit copy upstream.
- Step 3 — Tune threshold
Start at 0.5 default, then widen or tighten to match merchandising tolerance.
- Step 4 — Review clusters
Read shared token chips to confirm shoppers would conflate the SKUs.
- Step 5 — Pair with site-wide cannibal workflows
Use Keyword cannibalization for query-level conflicts and Ecommerce site auditor for template health.
More detail
New here? Skim Start here first, then run one Examples scenario in the form above.
Product Cannibalization does one job: find product pages on your site competing for the same queries. It lives under Competitor & Strategy on SEOToolkits, where the beginner idea is simple: Competitor SEO compares your site with ranking pages so you can find realistic gaps and advantages.
FAQ
- Does this read GTIN or SKU codes?
- Only the keyword phrase and URL text you enter. Add identifiers externally if needed.
- Can it auto-merge products?
- No. It surfaces clusters. PIM, ERP, and CMS teams still execute merges.
- What metric should I use?
- Sales, revenue, or Search Console clicks all work as long as the column stays numeric and consistent.
- International duplicates?
- Separate locales into different pastes so language tokens do not distort similarity.
Related tools
Same workflow cluster on SEOToolkits — open another module without leaving context.
Keyword Cannibalization
Find pages on your site fighting each other for the same term.
Ecommerce Site Auditor
Storefront audit: faceted nav, schema, OOS handling, more.
Content Consolidator
Find merge candidates among overlapping URLs and recommend a canonical.
Product Schema Generator
Generate Product/Offer JSON-LD with reviews and pricing.