Analytics Reporting

Analytics & Reporting Skill

When This Skill Activates

This skill loads automatically when you mention:

• analytics, reporting, traffic metrics, performance reports
• weekly reports, monthly reports, dashboards, data analysis
• traffic drops, traffic spikes, content performance, page performance
• user behavior, conversion analysis, cross-source data correlation
• why did traffic drop, what content is performing, performance anomaly detection
• trend analysis, root cause analysis, traffic investigation
• combined reporting, GSC + GA4 analysis, search traffic, organic traffic trends
• bounce rate analysis, engagement metrics, landing page analysis
• session analysis, revenue correlation, goal conversion
• heat maps, user journeys, content audit performance, traffic forecasting
• any multi-source data analysis and reporting task

Data Sources

Real-time APIs:

• Google Search Console API (impressions, clicks, CTR, position, queries)
• Google Analytics 4 API (property 528383456) — sessions, users, conversions, events
• PostgreSQL OpenSEO DB (100.87.191.9:5432) — internal metrics, backlinks, keywords
• Redis cache (100.87.191.9:6379) — geolab-links queue state, job timing

WordPress & VPS:

• WordPress REST API (thegeolab.net) — post metadata, publish dates, author
• VPS Service APIs (100.87.191.9):
  • seo-intelligence (:3001) — rank tracking data
  • geolab-links (:3002) — link profile, authority scores
  • geolab-backlinks (:4000) — backlink snapshots, competitor data
  • geolab-keywords (:4001) — keyword clustering, SERP features
  • geolab-writer (:4002) — published content, performance tags

Core Responsibilities

1. Multi-Source Correlation — Join data from GSC, GA4, PostgreSQL, WordPress, Redis using lag-aware joins and confidence scoring
2. Anomaly Detection — Z-score, moving averages, seasonality adjustment, algorithm change detection, composite anomaly scoring
3. Report Generation — Weekly summaries, monthly deep-dives, investigation reports, audit snapshots, page-level breakdowns
4. Actionable Insights — Root cause analysis, content recommendations, traffic recovery strategies, opportunity detection
5. Data Validation — Check data completeness, lag detection, source freshness, accuracy within confidence bounds

Key Patterns

Data Joining Strategy

• GSC → GA4: Join on page URL, account for 1-3 day GSC reporting lag
• GA4 → PostgreSQL: Join on post_id via WordPress URL parsing
• WordPress → VPS Services: Query via REST API for metadata enrichment
• Confidence Scoring: Apply weights based on data freshness and source reliability

Anomaly Detection Method

1. Calculate baseline (30-90 day rolling average)
2. Adjust for seasonality (day-of-week, holidays, known events)
3. Compute z-score and isolation forest scores
4. Combine into composite anomaly score
5. Flag if score > threshold + explanation

Report Template Structure

• Executive summary (1 paragraph)
• Key metrics table (YoY/MoM % change)
• Anomaly findings (if any)
• Content performance ranking
• Traffic sources breakdown
• Conversion funnel analysis
• Root cause diagnosis (for drops)
• Actionable recommendations (3-5 items)
• Data quality notes + sources cited

Output Standards

Always include:

• Data date range ("Jan 1-31, 2026")
• All sources used (GSC API, GA4, PostgreSQL, etc.)
• Confidence levels (95%, 85%, unvalidated)
• Actionable recommendations (not just observations)
• Any caveats or data gaps

Never:

• Fabricate data or fill gaps with estimates
• Claim confidence >95% without 3+ sources
• Recommend without understanding intent
• Ignore seasonal patterns without mentioning them
• Skip data freshness checks

See Also

• anomaly-detection.md — Z-score formulas, moving averages, seasonality math
• correlation.md — Multi-source joining strategy, lag-aware logic, confidence scoring
• data-sources.md — API endpoints, query patterns, connection strings
• report-templates.md — Weekly, monthly, investigation, audit, page-level templates