--- name: content-cannibalization description: Detect content cannibalization on a site — multiple URLs ranking (or impressing) for the same query, splitting click-through, diluting authority, and confusing Google about which URL is canonical for the intent. Pulls GSC query × page data, identifies cannibalized clusters (≥ 2 pages with ≥ 50 impressions for the same query within position 1-50), classifies the underlying issue (true duplicate / intent overlap / template confusion / accidental same H1 / variant page leakage), and recommends one of five resolutions: consolidate-and-301, canonicalize, differentiate-intent, noindex-the-weaker, or update-internal-links-to-disambiguate. Generates the actual redirect rules, canonical tags, content briefs for differentiation, and a recovery model showing expected click consolidation. TRIGGER on "cannibalization", "content cannibalization", "keyword cannibalization", "ranking conflicts", "multiple pages for same query", "consolidate content", "GSC cannibalization". version: "1.0.0" category: analysis platforms: - CLAUDE_CODE --- # Content Cannibalization Detector & Resolver You find cannibalization and recommend the specific fix. Cannibalization is the single most common cause of "we have lots of content but rankings are stuck" — and it's invisible without joining GSC query-level data with the site's page intents. ============================================================ === PRE-FLIGHT === ============================================================ - [ ] **GSC data**: from `/gsc-pull` skill (or direct connection). - [ ] **Page-to-intent map**: for each URL, which target query is it written for? If unknown, derive from H1 + meta description. - [ ] **Crawl data**: title, H1, canonical, noindex, content embedding (from `/internal-link-graph` if available). - [ ] **Authority signal**: backlinks per page (from Ahrefs/Majestic if accessible; otherwise GSC referring domain proxy). - [ ] **Action capacity**: how many redirects / consolidations / canonical edits can the team execute monthly? (Drives prioritization.) Recovery: - No backlink data: use internal PageRank from `/internal-link-graph` as authority proxy. - No intent map: auto-derive via top GSC query per page (with a "MUST_VERIFY" flag on results). ============================================================ === PHASE 1: CANNIBALIZATION DETECTION === ============================================================ For each unique query in GSC (filter to impressions ≥ 50 in window): ```python def detect_cannibalization(gsc_rows, min_impressions=50, position_max=50): """ Returns clusters where a single query has 2+ URLs both within position 1-50 with non-trivial impressions. """ by_query = defaultdict(list) for row in gsc_rows: if row.impressions >= min_impressions and row.position <= position_max: by_query[row.query].append(row) clusters = {} for query, rows in by_query.items(): if len(rows) >= 2: clusters[query] = sorted(rows, key=lambda r: -r.clicks) return clusters ``` Output `cannibalization_clusters.csv`: | Query | URL | Impressions | Clicks | Avg Position | CTR | Cluster Size | |---|---|---|---|---|---|---| | best CRM | /blog/best-crm | 8400 | 240 | 8.2 | 2.9% | 3 | | best CRM | /pricing | 1100 | 12 | 22.4 | 1.1% | 3 | | best CRM | /reviews | 600 | 5 | 31.8 | 0.8% | 3 | VALIDATION: Detection produces non-zero clusters on any site with > 500 pages and > 100 ranking queries. ============================================================ === PHASE 2: ROOT-CAUSE CLASSIFICATION === ============================================================ For each cluster, classify the cannibalization type: | Class | Signal | Typical fix | |---|---|---| | **True duplicate** | Embedding similarity > 0.95 between competing pages | Consolidate, 301 weaker → stronger, remove | | **Intent overlap** | Same query, different intents (e.g., transactional + informational) | Differentiate H1 / content; canonical NOT same | | **Template confusion** | Multiple variant/filter pages indexable, same query | Canonicalize to parent; or `noindex` variants | | **Accidental same H1** | Different topics but same H1 / title | Rewrite the H1 / title of one | | **Variant page leakage** | UTM / session ID / filter query strings indexed | Set `` to clean URL; robots Disallow query strings | | **Author overlap** | Same author bio repeated, body content overlaps in intro paragraphs | Update author template to be lighter | Detection per class: - **True duplicate**: embedding cosine ≥ 0.95 across competing URLs. - **Intent overlap**: SERP intent signal (Google AI Overview vs ten blue links vs shopping ads) suggests one canonical intent; multiple pages target different but Google merges. - **Template confusion**: URL pattern suggests filter/variant (`?color=`, `?sort=`, `/category/page/2/`). - **Variant leakage**: URL has query string or session ID. VALIDATION: Each cluster has a class label + confidence (0-1). ============================================================ === PHASE 3: RESOLUTION RECOMMENDATIONS === ============================================================ Per cluster, produce one of five resolutions: **A. Consolidate-and-301** (best for true duplicates): - Identify "winner" (highest authority + best historical clicks + best target intent fit). - All losers 301-redirect → winner. - Merge unique content from losers into winner (don't lose value). - Update internal links to point to winner. **B. Canonicalize** (best for variant leakage): - Set `` on variants. - Don't 301 (preserve UX for filtered nav). **C. Differentiate-intent** (best for intent overlap): - Keep both pages. Rewrite each to target distinct intent. - Page A → transactional ("buy X"); Page B → informational ("what is X"). - Update internal links to disambiguate. **D. Noindex-the-weaker** (best for template / pagination): - `` on weaker pages. - Or use `rel="next/prev"` pagination semantics where applicable. **E. Update-internal-links-only** (lightest touch, valid when both pages should stay live): - Reroute internal links so the intended page gets all the link equity. - Don't change URL structure. Per cluster, output `resolution_{cluster_id}.md` with: - Recommended resolution (A-E) - Reasoning (which signals drove it) - Exact code/redirects/canonical tags to add - Internal link updates needed - Expected click recovery (sum of cluster clicks × consolidation multiplier 1.2-1.8) VALIDATION: Recommendation per cluster is concrete and tied to evidence. ============================================================ === PHASE 4: REDIRECT RULES & CANONICAL PATCHES === ============================================================ Generate platform-specific implementation: **Nginx**: ``` location = /blog/old-url { return 301 /blog/winner-url; } ``` **Apache (.htaccess)**: ``` RewriteRule ^blog/old-url$ /blog/winner-url [R=301,L] ``` **Next.js (`next.config.js`)**: ```js async redirects() { return [ { source: '/blog/old-url', destination: '/blog/winner-url', permanent: true }, ... ] } ``` **Cloudflare Workers** / **Vercel `vercel.json`** / **Netlify `_redirects`**: ``` /blog/old-url /blog/winner-url 301 ``` **WordPress** (Redirection plugin export): ```csv source,target,type /blog/old-url,/blog/winner-url,301 ``` **Canonical tag patches** for "B. Canonicalize": ```html ``` VALIDATION: Generated redirects parse correctly in their target stack. ============================================================ === PHASE 5: RECOVERY MODEL === ============================================================ Estimate post-fix click recovery: ``` Expected clicks per cluster after fix = (sum of impressions in cluster) × (CTR at winner's new expected position) Position lift from consolidation: if total cluster clicks > 100 and lift ~ -1 to -3 positions (closer to top) use CTR-by-position curve (Google avg: pos 1=27%, pos 2=15%, pos 3=11%, pos 4=8%, pos 5=7%, etc.) ``` For each cluster: - Current cluster total clicks/week - Expected clicks/week after fix - Net gain - Confidence (high if true duplicate, medium for intent split, low for soft variants) Aggregate: total expected click gain across all cannibalization fixes. Prioritize highest-gain × lowest-effort first. VALIDATION: Recovery model uses real CTR-by-position curves, not made-up multipliers. ============================================================ === PHASE 6: ACTION QUEUE === ============================================================ Generate `action_queue.md` ordered by impact × inverse effort: ```markdown # Cannibalization Action Queue — {site} ## P0 — High impact, low effort 1. [Consolidate] "best CRM" cluster: 301 /blog/reviews + /pricing → /blog/best-crm. Expected: +180 clicks/week. Effort: 30 min. Risk: low. ## P1 — High impact, medium effort 2. [Differentiate] "API rate limits" cluster: rewrite /docs/api-limits to focus on technical reference vs /blog/api-rate-limits which keeps tutorial focus. Expected: +90 clicks/week. Effort: 4 hours. ## P2 — Polish 3. [Canonicalize] "/?utm_source=*" variants: add canonical pointing to clean URL. Expected: +5 clicks/week (de-duped indexing). Effort: 1 hour. ``` VALIDATION: Action queue has per-item expected gain + effort. ============================================================ === SELF-REVIEW === ============================================================ - **Complete**: Detection + classification + 5 resolution types + redirect patches + recovery model? - **Robust**: Handles variant leakage with query strings? Avoids over-consolidating (some pairs SHOULD stay separate)? - **Clean**: Recommendations are platform-specific (Nginx / Next.js / WordPress)? - **SEO-credible**: Would an Ahrefs power-user accept the analysis as production-ready? Common gap: recommending 301 on a page that's still gaining traffic. Always check trend before consolidating — growing-but-second-best may overtake. ============================================================ === LEARNINGS CAPTURE === ============================================================ `~/.claude/skills/content-cannibalization/LEARNINGS.md`. ============================================================ === STRICT RULES === ============================================================ - Never recommend a 301 without first checking that both pages have the same primary intent. Intent splits don't consolidate, they differentiate. - Never propose a redirect that creates a chain (A→B→C). Always squash to A→C directly. - Never assume cluster sizes > 2 = always bad. Sometimes Google legitimately surfaces multiple URLs (e.g., subdirectory + a sub-page). - Always update internal links AFTER 301-ing. Otherwise the redirects hop forever and crawl budget burns. - Always re-pull GSC after 4-8 weeks to verify recovery model was correct. Refine assumptions over time.