analytics-insights
starsforks
How to install analytics-insights?
indranilbanerjee/digital-marketing-pro/analytics-insights
$npx -y skills add indranilbanerjee/digital-marketing-pro --skill analytics-insightsAnalyze marketing performance. Use when: KPI frameworks, attribution modeling, anomaly investigation, measurement strategy.
SKILL.md
| 1 | # Analytics & Insights |
| 2 | |
| 3 | ## GA4 "AI Assistant" channel group (added 13 May 2026) |
| 4 | |
| 5 | 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: |
| 6 | |
| 7 | - Categorizes the session under the **AI Assistant channel group** |
| 8 | - Sets the **Medium dimension to `ai-assistant`** |
| 9 | |
| 10 | 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. |
| 11 | |
| 12 | **Recommended GA4 setup checks** when onboarding a brand: |
| 13 | |
| 14 | 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"`. |
| 15 | 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. |
| 16 | 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. |
| 17 | 4. **Reconcile with `aeo-audit` outputs and the GSC AI report.** Three data sources, three different views: |
| 18 | - `aeo-audit` (synthetic probing) — what AI engines *could* say about the brand |
| 19 | - GSC AI Performance Report — actual impressions in Google AI Overviews / AI Mode (no clicks) |
| 20 | - GA4 AI Assistant channel — actual *traffic* from AI assistants (clicks materialized) |
| 21 | |
| 22 | A healthy AEO program shows growth across all three; divergence between them is a diagnostic signal. |
| 23 | |
| 24 | ## When to Use This Skill |
| 25 | |
| 26 | Activate this module when the user's request involves any of the following: |
| 27 | |
| 28 | - **KPI Frameworks**: Defining the right metrics and success measures for a business model, campaign, or channel |
| 29 | - **Performance Reporting**: Building weekly, monthly, quarterly, or campaign-specific reporting templates |
| 30 | - **Anomaly Investigation**: Diagnosing sudden drops or spikes in traffic, conversions, or other metrics |
| 31 | - **Competitive Intelligence**: Analyzing competitor strategies, share of voice, positioning, and performance |
| 32 | - **Attribution Modeling**: Determining how credit for conversions is assigned across marketing touchpoints |
| 33 | - **Marketing Mix Modeling (MMM)**: Estimating the impact of each marketing channel on overall business outcomes |
| 34 | - **Incrementality Testing**: Designing experiments to measure the true causal impact of marketing activities |
| 35 | - **Dark Social Measurement**: Tracking and attributing traffic from private sharing channels (DMs, Slack, email forwards) |
| 36 | - **Privacy-First Measurement**: Adapting measurement strategies for a cookieless, privacy-regulated environment |
| 37 | - **Dashboard Design**: Structuring dashboards for different stakeholder audiences |
| 38 | |
| 39 | **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" |
| 40 | |
| 41 | ## Brand Context (Auto-Applied) |
| 42 | |
| 43 | Before producing any marketing output from this module: |
| 44 | |
| 45 | 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. |
| 46 | 2. **If you need the full profile**, read: `~/.claude-marketing/brands/{slug}/profile.json` |
| 47 | 3. **Apply brand voice** — Formality, energy, humor, authority levels must shape all content tone and word choices |
| 48 | 4. **Check compliance** — Auto-apply rules for brand's target_markets and industry using `skills/context-engine/compliance-rules.md` |
| 49 | 5. **Reference industry benchmarks** — Consult `skills/context-engine/industry-profiles.md` for the brand's industry |
| 50 | 6. **Use platform specs** — Reference `skills/context-engine/platform-specs.md` for character limits and format requirements |
| 51 | 7. **Check campaign history** — Run `python campaign-tracker.py --brand {slug} --action list-campaigns` before planning new work |
| 52 | 8. **If no brand exists**, say: "No |
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