| name | executive-dashboard |
| description | Design an executive marketing dashboard as a build-ready specification — 5-7 north-star metrics with rationale, metric hierarchy, chart choices, alert thresholds, data-source mapping, wireframe layout, drill-down structure, and a mobile variant. It designs the dashboard; it does not build or connect a live one. Triggers on "/digital-marketing-pro:executive-dashboard", "design a CMO dashboard", "what metrics should the board see", "our exec report is too noisy", "create a leadership reporting view". Reads the brand profile and guidelines; pairs with /digital-marketing-pro:exec-summary for the written companion narrative. |
/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.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.
- 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
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
