# Data Dashboard Design > Plans data dashboard layouts with metric selection, visualization types, refresh frequency, and user-focused design. Use when building dashboards that drive decisions. - Skill: `reaperinvest/data-dashboard-design` (Agent Skill) - Install (CLI): `npx skillmds@latest add reaperinvest/data-dashboard-design` - Raw SKILL.md: https://api.skillmd.com/api/skills/reaperinvest/data-dashboard-design/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Data & Analytics - Author: reaperinvest (https://skillmd.com/u/reaperinvest) - Updated: 2026-09-22 - Page: https://skillmd.com/skills/reaperinvest/data-dashboard-design --- # Data Dashboard Design ## When to Use This Skill Use this skill when you need to: - Design a business metrics dashboard layout - Select the right visualizations for different metric types - Plan a dashboard hierarchy (executive, operational, team-level) - Specify requirements for a developer or BI tool configuration **DO NOT** use this skill for building dashboards in code, creating actual charts, or configuring specific BI tools. This is for dashboard planning and design. --- ## Core Principle A DASHBOARD THAT REQUIRES EXPLANATION HAS FAILED — EVERY METRIC SHOULD ANSWER A QUESTION THE VIEWER ALREADY HAS IN 5 SECONDS OR LESS. --- ## Phase 1: Brief ### Required Inputs | Input | What to Ask | Default | |-------|------------|---------| | **Audience** | "Who will view this dashboard? (founder, team leads, investors, whole team)" | Founder / CEO | | **Purpose** | "What decisions should this dashboard inform?" | Weekly business health check | | **Key questions** | "What 3-5 questions should someone answer by looking at this?" | Must be provided | | **Data sources** | "Where does your data live? (Stripe, GA4, CRM, spreadsheets)" | Mixed sources | | **Tool** | "What will you build this in? (Google Sheets, Looker, Tableau, Databox, Notion)" | Google Sheets or Looker Studio | | **Refresh frequency** | "How often should data update? (real-time, daily, weekly)" | Daily | **GATE: Confirm brief before proceeding.** --- ## Phase 2: Design ### Dashboard Architecture 1. **Top-line KPIs** — 3-5 big numbers at the top answering "How are we doing overall?" 2. **Trend charts** — time-series showing direction over the last 30/90 days 3. **Breakdowns** — dimensions that explain the top-line numbers (by channel, product, segment) 4. **Comparison context** — vs. last period, vs. target, vs. benchmark 5. **Action triggers** — thresholds that signal when something needs attention ### Visualization Selection Rules | Data Type | Best Visualization | Avoid | |-----------|-------------------|-------| | Single KPI | Big number with trend arrow | Pie chart | | Trend over time | Line chart | Bar chart for 30+ data points | | Part of whole | Stacked bar or donut | 3D pie charts (always) | | Comparison across categories | Horizontal bar chart | Vertical bars with 10+ categories | | Correlation | Scatter plot | Line chart | | Geographic | Map / heatmap | Table with location names | **GATE: Present the dashboard wireframe and wait for approval.** --- ## Phase 3: Build ### Deliverables **1. Dashboard Specification Document** - Complete layout with sections, metrics, and visualization types - Data source mapping for each metric - Filter and drill-down requirements - Refresh schedule and data latency notes **2. Metric Definitions** - How each metric is calculated (formula) - Data source and table/field references - Expected range and alert thresholds **3. Wireframe Layout** - Text-based or sketch layout showing placement of each element - Reading order: top-left to bottom-right, most important first - Mobile considerations if viewed on phones **4. Implementation Checklist** - [ ] Data sources connected and verified - [ ] Metric calculations validated against source - [ ] Date filters working correctly - [ ] Comparison periods accurate - [ ] Loading time under 5 seconds - [ ] Mobile layout reviewed --- ## Phase 4: Polish ### Review Cadence - Week 1: Verify all numbers match source data - Week 4: Survey users — is anything missing or confusing? - Month 3: Remove metrics nobody looks at, add any new questions ### Dashboard Hygiene Rules - No more than 10 metrics on a single view — if you need more, create sub-dashboards - Every metric has a definition tooltip or footnote - Color coding is consistent (green = good, red = attention needed) --- ## Example 1: SaaS Founder Dashboard **Top-line:** MRR, Active Users, Churn Rate, NPS **Trends:** MRR growth (12 months), signup trend (30 days) **Breakdowns:** Revenue by plan tier, signups by acquisition channel ## Example 2: E-commerce Weekly Dashboard **Top-line:** Revenue, Orders, AOV, Conversion Rate **Trends:** Daily revenue (30 days), traffic (30 days) **Breakdowns:** Revenue by product category, traffic by source, conversion by device --- ## Anti-Patterns - **Dashboard overload** — 30 metrics on one screen means nobody reads any of them. Ruthlessly prioritize. - **Vanity metrics** — total pageviews without context is meaningless. Always show metrics that connect to revenue or retention. - **No comparison context** — a number without a benchmark is just a number. Show vs. last period, vs. target, or vs. industry. - **Rainbow color coding** — 8 colors for 8 categories creates visual noise. Use 2-3 colors max with gray for secondary elements. - **Stale data** — a dashboard that updates monthly when decisions happen weekly is useless. --- ## Recovery - **User cannot define key questions:** Ask "What do you check first thing Monday morning? What number keeps you up at night?" Extract dashboard requirements from the answers. - **Too many data sources:** Start with 1-2 sources for the MVP dashboard. Add sources incrementally. - **No BI tool:** Google Sheets with charts and a refresh button is a valid V1 dashboard for small businesses. - **Data quality issues:** Flag metrics with known quality problems. A metric with an asterisk is better than a missing metric.