SEO Drift

/digital-marketing-pro:seo-drift

Script location. If your host does not set ${CLAUDE_PLUGIN_ROOT}, the scripts are in this plugin's scripts/ folder, next to skills/.

Purpose

Take two snapshots of SEO performance data — separated by weeks, a Core Update, a content refresh, or an algorithm change — and produce a structured drift report: top gainers, top losers, classifications (growth / decline / reshuffle / stable / new / lost), and diagnostic patterns. Works with classic GSC, the new GSC AI Performance Report, rank-tracker exports, and aeo-audit probe results.

Context efficiency

Heavy skill. Grep before Read any referenced file, then Read only matched ranges with offset + limit. List ${CLAUDE_PLUGIN_DATA}/<brand>/ before opening files. On re-invocation mid-session, skip files already in context.

When to Use

• Monthly performance review — last month vs the month before
• Core Update triage — pre-update vs post-update + settling window (use 14+ days after rollout-complete)
• AI Mode citation tracking — quarter-over-quarter aeo-audit outputs to see which queries gained / lost AI Mode citations (Google AI Mode citation diff is a leading indicator for organic decline)
• Content refresh attribution — before vs after a planned content update to attribute lift to the refresh vs other factors
• GSC AI Performance Report — month-over-month deltas on the new (3 Jun 2026) combined AI Overviews + AI Mode report
• Site migration audit — pre-migration baseline vs post-migration settling

Don't use for single-point-in-time analysis (use the source skill — seo-audit, aeo-audit, gsc-ai-performance).

Brand context (auto-applied)

1. Read ~/.claude-marketing/brands/_active-brand.json for the active slug, then load ~/.claude-marketing/brands/{slug}/profile.json
2. If no brand exists: ask "Set up a brand first (/digital-marketing-pro:brand-setup)?" — or proceed with defaults
3. Apply skills/context-engine/industry-profiles.md for industry-specific noise thresholds (YMYL industries should use higher --noise to filter out routine Quality Rater Guidelines volatility)

Inputs

Both snapshots must come from the same source. Mixing a GSC export with an Ahrefs export will produce nonsense — different sources count different things.

Process (10 steps, numbered-file output)

All outputs go to ${CLAUDE_PLUGIN_DATA}/{brand}/seo/seo-drift/{YYYY-MM-DD}/.

1. 00-input.md — capture baseline date range, current date range, source (GSC / GSC AI / rank-tracker / aeo-audit), brand context
2. 01-baseline.csv — copy baseline export here (so the drift run is reproducible months later)
3. 02-current.csv — copy current export here
4. 03-drift-run.json — run the script:

   python "${CLAUDE_PLUGIN_ROOT}/scripts/seo_drift.py" \
       --baseline "${CLAUDE_PLUGIN_DATA}/{brand}/seo/seo-drift/{date}/01-baseline.csv" \
       --current  "${CLAUDE_PLUGIN_DATA}/{brand}/seo/seo-drift/{date}/02-current.csv" \
       --top 30 --noise 5 \
       --out "${CLAUDE_PLUGIN_DATA}/{brand}/seo/seo-drift/{date}/03-drift-run.json"

5. 04-quality-scorecard.md — read quality_scorecard from 03-drift-run.json. If status: needs_review, diagnose:
   • date_range_distinct: warn → script couldn't auto-validate. Manually confirm in 00-input.md that baseline and current cover non-overlapping windows.
   • sample_size: fail → either input has < 50 rows. Re-export without row limits.
   • metric_compatibility: fail → no numeric metrics in BOTH inputs. Column-name mismatch — re-export from the same source.
   • no_lookup_collisions: fail → duplicate keys in one input (e.g., same query × page row twice). Re-export with deduplication or use --join-on to add a distinguishing column.
6. 05-biggest-gainers.md — narrative on the top 10 gainers across impressions / clicks / position. For each: hypothesis on cause (new content? backlinks gained? Core Update favoured E-E-A-T? Featured Snippet rotation?). Hand off candidates to /digital-marketing-pro:content-engine for amplification.
7. 05-biggest-losers.md — narrative on the top 10 losers. For each: triage matrix — is_yMYL × had_recent_change × Core_Update_window → action (refresh content / restore reverted change / wait for next algo cycle / accept and reallocate).
8. 06-ai-mode-shift.md (only if input source is GSC AI Performance Report) — queries that LOST AI Mode impressions are a leading indicator. Cross-reference with /digital-marketing-pro:aeo-audit to verify citation loss in synthetic probes.
9. 07-classification-distribution.md — counts table:
   • growth / decline / reshuffle / stable / new / lost
   • If >40% in decline: likely Core Update or competitor catch-up. Run /digital-marketing-pro:seo-audit for diagnosis.
   • If >20% reshuffle: likely intent shift (AI Mode reweighting). Run /digital-marketing-pro:aeo-geo to align with new intent patterns.
   • If >30% growth: find amplification opportunities. Run /digital-marketing-pro:content-engine to brief follow-ups.
   • If >15% new: new SERP coverage — track and validate intent fit.
10. PLAN.md — single-page summary: stats + scorecard + top 5 actions ranked by impact × effort, with owner suggestions (SEO lead / content lead / dev team).

Output format

${CLAUDE_PLUGIN_DATA}/{brand}/seo/seo-drift/2026-06-04/
├── 00-input.md
├── 01-baseline.csv
├── 02-current.csv
├── 03-drift-run.json
├── 04-quality-scorecard.md
├── 05-biggest-gainers.md
├── 05-biggest-losers.md
├── 06-ai-mode-shift.md       (only when input is GSC AI Performance Report)
├── 07-classification-distribution.md
└── PLAN.md