/digital-marketing-pro:executive-dashboard skill
Design an executive dashboard spec: north-star metrics, charts, alert thresholds.
by indranilbanerjee·MIT license·★ 866 Stars on the repo·GitHub ↗
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SKILL.md · the author's own words# /digital-marketing-pro:executive-dashboard ## Purpose Design a C-suite marketing dashboard that translates marketing metrics into business outcomes for executive decision-making. Bridges the ga… ## Input Required The user must provide (or will be prompted for): - **Executive role**: Primary audience — CEO, CMO, CFO, VP Marketing, or board — each requires different metric emphasis and abstraction le… - **Business model and revenue drivers**: How the company makes money — SaaS, e-commerce, lead gen, marketplace, subscription — and the key… - **Strategic priorities this quarter**: The 2-4 business priorities the executive team is focused on that marketing should ladder up to - **Reporting frequency**: How often the dashboard will be reviewed — weekly executive standup, monthly leadership meeting, quarterly board… - **Current data sources and tools**: Analytics platforms, CRM, ad platforms, attribution tools, and BI systems currently in use with data… - **Existing reports being replaced**: Current reporting artifacts the dashboard will consolidate or replace — helps identify gaps and redu…
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SKILL.md
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/digital-marketing-pro:executive-dashboard
Purpose
Design a C-suite marketing dashboard that translates marketing metrics into business outcomes for executive decision-making. Bridges the gap between marketing activity data and business impact, giving senior leaders the clarity to make faster, better-informed strategic decisions without drowning in operational detail.
Input Required
The user must provide (or will be prompted for):
- Executive role: Primary audience — CEO, CMO, CFO, VP Marketing, or board — each requires different metric emphasis and abstraction level
- Business model and revenue drivers: How the company makes money — SaaS, e-commerce, lead gen, marketplace, subscription — and the key revenue levers marketing influences
- Strategic priorities this quarter: The 2-4 business priorities the executive team is focused on that marketing should ladder up to
- Reporting frequency: How often the dashboard will be reviewed — weekly executive standup, monthly leadership meeting, quarterly board review
- Current data sources and tools: Analytics platforms, CRM, ad platforms, attribution tools, and BI systems currently in use with data freshness and reliability notes
- Existing reports being replaced: Current reporting artifacts the dashboard will consolidate or replace — helps identify gaps and redundancies
- Key decisions the dashboard should inform: Specific decisions executives make that this dashboard should support — budget allocation, channel mix, hiring, campaign scaling, market expansion
- Stakeholder data literacy level: How comfortable the audience is with marketing metrics — determines labeling, context, and narrative density needed
Process
- Load brand context: Read
~/.claude-marketing/brands/_active-brand.jsonfor the active slug, then load~/.claude-marketing/brands/{slug}/profile.json. Apply brand voice, compliance rules for target markets (skills/context-engine/compliance-rules.md), and industry context. Also check for guidelines at~/.claude-marketing/brands/{slug}/guidelines/_manifest.json— if present, load restrictions and relevant category files. Check for custom templates at~/.claude-marketing/brands/{slug}/templates/. Check for agency SOPs at~/.claude-marketing/sops/. If no brand exists, ask: "Set up a brand first (/digital-marketing-pro:brand-setup)?" — or proceed with defaults. - Identify north-star metrics: Select 5-7 metrics that directly tie marketing activity to business outcomes — revenue influenced, pipeline generated, customer acquisition cost, lifetime value, market share, brand equity indicators
- Design metric hierarchy: Organize metrics into three tiers — leading indicators (predict future performance), lagging indicators (confirm past results), and health metrics (signal system stability and sustainability)
- Select visualization type per metric: Choose the optimal chart type for each metric based on data shape and decision context — trend lines for trajectory, gauges for targets, bar charts for comparisons, sparklines for density
- Define alert thresholds and anomaly triggers: Set green/yellow/red thresholds for each metric with specific trigger values, and configure anomaly detection rules for unexpected spikes or drops
- Map data sources to each metric: Document which system provides each metric, how it is calculated, data freshness (real-time, daily, weekly), and known limitations or lag
- Design layout for scanning speed: Structure the dashboard for F-pattern or Z-pattern scanning — most critical metrics top-left, summary before detail, consistent visual hierarchy, minimal cognitive load
- Add narrative guidance: Write "how to read this" instructions for each section — what good looks like, what bad looks like, and what action to take in each scenario
- Build drill-down structure: Design three levels of depth — summary view (the dashboard itself), detail view (campaign or channel breakdowns), and root cause view (diagnostic data for investigating anomalies)
- Create mobile-friendly variant: Adapt the dashboard layout for mobile or tablet viewing — prioritize top 3-5 metrics, stack vertically, enlarge touch targets, and simplify visualizations
- Add comparison baselines: Define what each metric is compared against — plan/target, prior period (MoM, QoQ, YoY), industry benchmark, and competitive estimate — with comparison display format
Output
A structured executive dashboard design containing:
- North-star metrics (5-7): Selected metrics with business rationale explaining why each matters to the executive audience and how it connects to strategic priorities
- Metric hierarchy diagram: Visual framework showing leading, lagging, and health metrics with causal relationships and directional influence between them
- Visualization recommendations: Chart type, scale, color coding, and annotation style for each metric with rationale for the design choice
- Alert threshold definitions: Green/yellow/red boundaries for each metric with specific trigger values, anomaly detection rules, and notification routing
- Data source mapping: Metric-by-metric documentation of source system, calculation method, refresh frequency, data latency, and known quality issues
- Dashboard wireframe layout: Spatial layout showing metric placement, section grouping, visual hierarchy, and scanning flow optimized for the target audience
- Narrative guide: Section-by-section presentation guide explaining how to read each area, what questions it answers, and what actions to consider based on the data shown
- Drill-down structure: Three-level depth design — summary (dashboard), detail (channel/campaign breakdown), and root cause (diagnostic investigation) with navigation flow
- Mobile layout variant: Adapted design for mobile viewing with prioritized metrics, vertical stacking, simplified charts, and touch-optimized interactions
- Comparison baseline definitions: For each metric, the comparison standard (target, prior period, benchmark, competitive) with display format and context notes
- Refresh cadence and data latency notes: Documentation of how often each metric updates, expected data lag, and implications for decision timing
- Executive summary template: A 3-sentence written narrative template that synthesizes dashboard findings into a verbal briefing — what happened, why it matters, what to do next
- Glossary of terms: Plain-language definitions of all metrics and marketing terminology for non-marketing stakeholders with examples and context
Agents Used
- analytics-analyst — Metric selection, hierarchy design, visualization recommendations, data source mapping, alert thresholds, drill-down architecture, refresh cadence, and dashboard layout optimization
| 1 | |
| 2 | name executive-dashboard |
| 3 | description "Design an executive dashboard spec: north-star metrics, charts, alert thresholds. \"design a CMO dashboard\"" |
| 4 | |
| 5 | |
| 6 | # /digital-marketing-pro:executive-dashboard |
| 7 | |
| 8 | ## Purpose |
| 9 | |
| 10 | Design a C-suite marketing dashboard that translates marketing metrics into business outcomes for executive decision-making. Bridges the gap between marketing activity data and business impact, giving senior leaders the clarity to make faster, better-informed strategic decisions without drowning in operational detail. |
| 11 | |
| 12 | ## Input Required |
| 13 | |
| 14 | The user must provide (or will be prompted for): |
| 15 | |
| 16 | **Executive role**: Primary audience — CEO, CMO, CFO, VP Marketing, or board — each requires different metric emphasis and abstraction level |
| 17 | **Business model and revenue drivers**: How the company makes money — SaaS, e-commerce, lead gen, marketplace, subscription — and the key revenue levers marketing influences |
| 18 | **Strategic priorities this quarter**: The 2-4 business priorities the executive team is focused on that marketing should ladder up to |
| 19 | **Reporting frequency**: How often the dashboard will be reviewed — weekly executive standup, monthly leadership meeting, quarterly board review |
| 20 | **Current data sources and tools**: Analytics platforms, CRM, ad platforms, attribution tools, and BI systems currently in use with data freshness and reliability notes |
| 21 | **Existing reports being replaced**: Current reporting artifacts the dashboard will consolidate or replace — helps identify gaps and redundancies |
| 22 | **Key decisions the dashboard should inform**: Specific decisions executives make that this dashboard should support — budget allocation, channel mix, hiring, campaign scaling, market expansion |
| 23 | **Stakeholder data literacy level**: How comfortable the audience is with marketing metrics — determines labeling, context, and narrative density needed |
| 24 | |
| 25 | ## Process |
| 26 | |
| 27 | **Load brand context**: Read `~/.claude-marketing/brands/_active-brand.json` for the active slug, then load `~/.claude-marketing/brands/{slug}/profile.json`. Apply brand voice, compliance rules for target markets (`skills/context-engine/compliance-rules.md`), and industry context. **Also check for guidelines** at `~/.claude-marketing/brands/{slug}/guidelines/_manifest.json` — if present, load restrictions and relevant category files. Check for custom templates at `~/.claude-marketing/brands/{slug}/templates/`. Check for agency SOPs at `~/.claude-marketing/sops/`. If no brand exists, ask: "Set up a brand first (/digital-marketing-pro:brand-setup)?" — or proceed with defaults. |
| 28 | **Identify north-star metrics**: Select 5-7 metrics that directly tie marketing activity to business outcomes — revenue influenced, pipeline generated, customer acquisition cost, lifetime value, market share, brand equity indicators |
| 29 | **Design metric hierarchy**: Organize metrics into three tiers — leading indicators (predict future performance), lagging indicators (confirm past results), and health metrics (signal system stability and sustainability) |
| 30 | **Select visualization type per metric**: Choose the optimal chart type for each metric based on data shape and decision context — trend lines for trajectory, gauges for targets, bar charts for comparisons, sparklines for density |
| 31 | **Define alert thresholds and anomaly triggers**: Set green/yellow/red thresholds for each metric with specific trigger values, and configure anomaly detection rules for unexpected spikes or drops |
| 32 | **Map data sources to each metric**: Document which system provides each metric, how it is calculated, data freshness (real-time, daily, weekly), and known limitations or lag |
| 33 | **Design layout for scanning speed**: Structure the dashboard for F-pattern or Z-pattern scanning — most critical metrics top-left, summary before detail, consistent visual hierarchy, minimal cognitive load |
| 34 | **Add narrative guidance**: Write "how to read this" instructions for each section — what good looks like, what bad looks like, and what action to take in each scenario |
| 35 | **Build drill-down structure**: Design three levels of depth — summary view (the dashboard itself), detail view (campaign or channel breakdowns), and root cause view (diagnostic data for investigating anomalies) |
| 36 | **Create mobile-friendly variant**: Adapt the dashboard layout for mobile or tablet viewing — prioritize top 3-5 metrics, stack vertically, enlarge touch targets, and simplify visualizations |
| 37 | **Add comparison baselines**: Define what each metric is compared against — plan/target, prior period (MoM, QoQ, YoY), industry benchmark, and competitive estimate — with comparison display format |
| 38 | |
| 39 | ## Output |
| 40 | |
| 41 | A structured executive dashboard design containing: |
| 42 | |
| 43 | **North-star metrics (5-7)**: Selected metrics with business rationale explaining why each matters to the executive audience and how it connects to strategic priorities |
| 44 | **Metric hierarchy diagram**: Visual framework showing leading, lagging, and health metrics with causal relationships and directional influence between them |
| 45 | **Visualization recommendations**: Chart type, scale, color coding, and annotation style for each metric with rationale for the design choice |
| 46 | **Alert threshold definitions**: Green/yellow/red boundaries for each metric with specific trigger values, anomaly detection rules, and notification routing |
| 47 | **Data source mapping**: Metric-by-metric documentation of source system, calculation method, refresh frequency, data latency, and known quality issues |
| 48 | **Dashboard wireframe layout**: Spatial layout showing metric placement, section grouping, visual hierarchy, and scanning flow optimized for the target audience |
| 49 | **Narrative guide**: Section-by-section presentation guide explaining how to read each area, what questions it answers, and what actions to consider based on the data shown |
| 50 | **Drill-down structure**: Three-level depth design — summary (dashboard), detail (channel/campaign breakdown), and root cause (diagnostic investigation) with navigation flow |
| 51 | **Mobile layout variant**: Adapted design for mobile viewing with prioritized metrics, vertical stacking, simplified charts, and touch-optimized interactions |
| 52 | **Comparison baseline definitions**: For each metric, the comparison standard (target, prior period, benchmark, competitive) with display format and context notes |
| 53 | **Refresh cadence and data latency notes**: Documentation of how often each metric updates, expected data lag, and implications for decision timing |
| 54 | **Executive summary template**: A 3-sentence written narrative template that synthesizes dashboard findings into a verbal briefing — what happened, why it matters, what to do next |
| 55 | **Glossary of terms**: Plain-language definitions of all metrics and marketing terminology for non-marketing stakeholders with examples and context |
| 56 | |
| 57 | ## Agents Used |
| 58 | |
| 59 | **analytics-analyst** — Metric selection, hierarchy design, visualization recommendations, data source mapping, alert thresholds, drill-down architecture, refresh cadence, and dashboard layout optimization |
| 60 |
Discussion
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