/analytics-insights

name: analytics-insights
description: "Marketing measurement module — builds KPI trees per business model, reporting templates (weekly, monthly, QBR, campaign), anomaly root-cause diagnosis, MMM and incrementality guidance, dark-social tracking, and privacy-first cookieless measurement architecture, including the GA4 AI Assistant channel group for attributing AI-referred traffic. Triggers on \"/digital-marketing-pro:analytics-insights\", \"why did traffic drop\", \"define our KPIs\", \"design an executive dashboard\", \"can we do marketing mix modeling\". Reads the brand profile, industry benchmarks, and campaign history; pairs with /digital-marketing-pro:gsc-ai-performance and /digital-marketing-pro:aeo-audit to triangulate AI-surface impressions against actual traffic."

Analytics & Insights

GA4 "AI Assistant" channel group (added 13 May 2026)

Google Analytics 4 added a new **default channel group called "AI Assistant"** on 13 May 2026 ([GA4 channel groups doc](https://support.google.com/analytics/answer/9164320?hl=en)). When a referrer matches a recognized AI Assistant (ChatGPT, Gemini, Claude, etc.), GA4 automatically:

• Categorizes the session under the **AI Assistant channel group**
• Sets the **Medium dimension to `ai-assistant`**

This is the **attribution-side counterpart** to the new GSC AI Performance Report (rolled out 3 June 2026 — see `/digital-marketing-pro:gsc-ai-performance`). Because the GSC AI report intentionally excludes click data, the GA4 AI Assistant channel is currently the cleanest path to attribute *actual traffic* coming from generative AI surfaces.

**Recommended GA4 setup checks** when onboarding a brand:

1. **Confirm the channel group is live in the property.** Newer GA4 properties get it automatically; older ones may need it to appear after Google's backfill completes. If the brand reports their channel reports look unchanged after 13 May, check explore reports filtered by `sessionDefaultChannelGroup = "AI Assistant"`. 2. **Add the AI Assistant channel to custom reports + dashboards** — for any brand running an AEO program (`/digital-marketing-pro:aeo-geo`, `/digital-marketing-pro:aeo-audit`), the AI Assistant channel trend is now a primary KPI alongside organic search clicks. 3. **Don't merge AI Assistant into "Organic Search" or "Direct".** Some legacy reporting templates roll AI traffic into Direct (because referrers weren't always present) or Organic Search (because answer engines feel "search-like"). Both are misattributions now — the AI Assistant channel is the authoritative bucket. 4. **Reconcile with `aeo-audit` outputs and the GSC AI report.** Three data sources, three different views:

• `aeo-audit` (synthetic probing) — what AI engines *could* say about the brand
• GSC AI Performance Report — actual impressions in Google AI Overviews / AI Mode (no clicks)
• GA4 AI Assistant channel — actual *traffic* from AI assistants (clicks materialized)

A healthy AEO program shows growth across all three; divergence between them is a diagnostic signal.

When to Use This Skill

Activate this module when the user's request involves any of the following:

• **KPI Frameworks**: Defining the right metrics and success measures for a business model, campaign, or channel
• **Performance Reporting**: Building weekly, monthly, quarterly, or campaign-specific reporting templates
• **Anomaly Investigation**: Diagnosing sudden drops or spikes in traffic, conversions, or other metrics
• **Competitive Intelligence**: Analyzing competitor strategies, share of voice, positioning, and performance
• **Attribution Modeling**: Determining how credit for conversions is assigned across marketing touchpoints
• **Marketing Mix Modeling (MMM)**: Estimating the impact of each marketing channel on overall business outcomes
• **Incrementality Testing**: Designing experiments to measure the true causal impact of marketing activities
• **Dark Social Measurement**: Tracking and attributing traffic from private sharing channels (DMs, Slack, email forwards)
• **Privacy-First Measurement**: Adapting measurement strategies for a cookieless, privacy-regulated environment
• **Dashboard Design**: Structuring dashboards for different stakeholder audiences

**Trigger phrases**: "KPIs," "metrics," "reporting," "dashboard," "why did traffic drop," "anomaly," "competitor analysis," "competitive intelligence," "attribution," "marketing mix model," "MMM," "incrementality," "lift test," "dark social," "cookieless," "privacy-first," "ROAS," "ROI," "performance," "what happened to our numbers"

Brand Context (Auto-Applied)

Before producing any marketing output from this module:

1. **Check session context** — The active brand summary was output at session start. Use the brand name, industry, voice settings, channels, goals, compliance, and competitors shown there. 2. **If you need the full profile**, read: `~/.claude-marketing/brands/{slug}/profile.json` 3. **Apply brand voice** — Formality, energy, humor, authority levels must shape all content tone and word choices 4. **Check compliance** — Auto-apply rules for brand's target_markets and industry using `skills/context-engine/compliance-rules.md` 5. **Reference industry benchmarks** — Consult `skills/context-engine/industry-profiles.md` for the brand's industry 6. **Use platform specs** — Reference `skills/context-engine/platform-specs.md` for character limits and format requirements 7. **Check campaign history** — Run `python campaign-tracker.py --brand {slug} --action list-campaigns` before planning new work 8. **If no brand exists**, say: "No brand profile found. Use /digital-marketing-pro:brand-setup to create one, or I can proceed with general best practices." 9. **Check brand guidelines** — If `~/.claude-marketing/brands/{slug}/guidelines/_manifest.json` exists, load and enforce: `restrictions.md` for banned words, restricted claims, and mandatory disclaimers; `channel-styles.md` for channel-specific tone override