Keyword Cannibalisation
Discover which pages on your site compete against each other for the same keywords—then resolve the conflicts with AI-powered recommendations.
Quick start
1. Review the table for keywords with multiple competing URLs
2. Click a keyword row to expand and see all competing pages
3. Select up to 3 pages if more than 3 are competing
4. Click Analyse with AI to get specific recommendations
5. Add recommendations to Kanban for implementation
What is keyword cannibalization?
Keyword cannibalization occurs when multiple pages on the same website compete for the same search terms. Instead of consolidating ranking signals on one strong page, authority is split across several pages—often causing all of them to rank lower than they should.
Common symptoms include:
• Rankings that fluctuate between different URLs for the same keyword
• Pages stuck in positions 4–20 instead of breaking into the top 3
• Search engines indexing a less relevant page for important keywords
Understanding the display
Expanded view
Click any keyword row to expand and see the competing URLs. The expanded view shows position metrics for each page:
| Metric | Description |
| URL | The page competing for this keyword |
| Best | Best ranking position achieved in the analysis period |
| Worst | Worst ranking position in the analysis period |
| Average | Average position across all checks |
What should I do next?
| Situation | Action |
| 2–3 competing pages | Click Analyse with AI to get recommendations |
| 4+ competing pages | Select the 3 most important pages, then analyse |
| Pages have similar content | Consider consolidating into one comprehensive page |
| Pages serve different intents | Differentiate content and target distinct keywords |
| One page clearly stronger | Set it as primary; redirect or de-optimise others |
| Canonical issues detected | Fix canonical tags to signal preferred page |
Using the domain filter
The domain dropdown at the top filters results to a specific domain. Select "All Domains" to see cannibalization across all tracked domains, or choose a specific domain to focus the analysis.
Running AI Analysis
1. Click a keyword row to expand it
2. If 4+ URLs appear, select up to 3 using the checkboxes
3. Click Analyse with AI
4. Wait for the analysis to complete (typically 30–60 seconds)
5. Review canonical check results and AI recommendations
The analysis runs asynchronously. Page content is fetched and analysed in the background—the interface remains responsive while processing completes.
Understanding AI recommendations
AI Analysis examines page content from competing URLs and generates specific, actionable recommendations. Results are organised by page, with each recommendation including exact wording suggestions.
Recommendation types
| Type | What it covers |
| Title change | Current and recommended page title with explanation |
| Meta description change | Recommended meta description text |
| Heading changes | H1/H2 modifications to differentiate content |
| Content modifications | Specific sections to rewrite with exact replacement text |
| Sections to add | New content sections with suggested headings and text |
| Sections to remove | Content to delete to reduce overlap |
Priority levels
| Priority | Meaning |
| Immediate | High-impact changes affecting rankings now—implement within 1–2 weeks |
| Near-term | Important improvements—implement within 1–2 months |
| Can-wait | Lower priority optimisations for when time permits |
Understanding canonical check
The canonical check runs alongside AI Analysis and examines the canonical tag configuration of competing pages. It identifies conflicts that may be confusing search engines.
Common issues detected:
• Multiple pages pointing to the same canonical URL
• Conflicting canonical references between pages
• Missing or incorrect canonical tags
Adding recommendations to Kanban
1. Find a recommendation worth implementing
2. Click the + button next to the recommendation
3. Select the target project from the dropdown
4. Click Confirm Selection
The button changes to a tick when added successfully. All recommendation details are preserved in the Kanban task.
Troubleshooting
No cannibalization data found
No competing pages were detected within the analysis thresholds.
• Ensure ranking data exists for the past 14 days
• Verify keywords are actively tracked
• Check the correct workspace is selected
AI Analysis is slow or times out
Analysis fetches full page content for each URL before processing. Large pages or slow servers increase processing time.
• Select fewer pages (maximum 3) for analysis
• If timeout occurs, try again—the system automatically retries
Cannot add recommendation to Kanban
No projects exist in the current workspace.
• Create a project in Kanban first
• Verify the correct workspace is selected
FAQ
How does SERP360 detect cannibalization?
SERP360 analyses ranking data over the past 14 days, looking for keywords where multiple URLs from the same domain rank within similar positions (top 30) with position fluctuations. This pattern indicates search engines are uncertain which page to rank.
Why can I only select 3 pages for analysis?
AI Analysis fetches and processes full page content. Limiting to 3 pages ensures analysis completes within reasonable time and provides focused, actionable recommendations. The most impactful cannibalization issues typically involve 2–3 competing pages.
Does fixing cannibalization guarantee better rankings?
Resolving cannibalization consolidates ranking signals and typically improves positions. However, rankings depend on many factors including content quality, backlinks, and competitor activity. Cannibalization fixes remove a barrier to ranking—they don't guarantee top positions.
How often should I check for cannibalization?
Monthly reviews are sufficient for most sites. Check after publishing new content that targets existing keywords, or when rankings for important keywords become unstable.
Getting help
Contact support for persistent issues or questions about recommendations