sickn33/antigravity-awesome-skills/kpi-dashboard-design

Name: kpi-dashboard-design
Author: sickn33

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Comprehensive patterns for designing effective Key Performance Indicator (KPI) dashboards that drive business decisions.

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SKILL.md

KPI Dashboard Design

Comprehensive patterns for designing effective Key Performance Indicator (KPI) dashboards that drive business decisions.

Do not use this skill when

The task is unrelated to kpi dashboard design
You need a different domain or tool outside this scope

Instructions

Clarify goals, constraints, and required inputs.
Apply relevant best practices and validate outcomes.
Provide actionable steps and verification.
If detailed examples are required, open resources/implementation-playbook.md.

Use this skill when

Designing executive dashboards
Selecting meaningful KPIs
Building real-time monitoring displays
Creating department-specific metrics views
Improving existing dashboard layouts
Establishing metric governance

Core Concepts

1. KPI Framework

Level	Focus	Update Frequency	Audience
Strategic	Long-term goals	Monthly/Quarterly	Executives
Tactical	Department goals	Weekly/Monthly	Managers
Operational	Day-to-day	Real-time/Daily	Teams

2. SMART KPIs

Specific: Clear definition
Measurable: Quantifiable
Achievable: Realistic targets
Relevant: Aligned to goals
Time-bound: Defined period

3. Dashboard Hierarchy

├── Executive Summary (1 page)
│   ├── 4-6 headline KPIs
│   ├── Trend indicators
│   └── Key alerts
├── Department Views
│   ├── Sales Dashboard
│   ├── Marketing Dashboard
│   ├── Operations Dashboard
│   └── Finance Dashboard
└── Detailed Drilldowns
    ├── Individual metrics
    └── Root cause analysis

Common KPIs by Department

Sales KPIs

yaml

Revenue Metrics:
  - Monthly Recurring Revenue (MRR)
  - Annual Recurring Revenue (ARR)
  - Average Revenue Per User (ARPU)
  - Revenue Growth Rate
 
Pipeline Metrics:
  - Sales Pipeline Value
  - Win Rate
  - Average Deal Size
  - Sales Cycle Length
 
Activity Metrics:
  - Calls/Emails per Rep
  - Demos Scheduled
  - Proposals Sent
  - Close Rate

Marketing KPIs

yaml

Acquisition:
  - Cost Per Acquisition (CPA)
  - Customer Acquisition Cost (CAC)
  - Lead Volume
  - Marketing Qualified Leads (MQL)
 
Engagement:
  - Website Traffic
  - Conversion Rate
  - Email Open/Click Rate
  - Social Engagement
 
ROI:
  - Marketing ROI
  - Campaign Performance
  - Channel Attribution
  - CAC Payback Period

Product KPIs

yaml

Usage:
  - Daily/Monthly Active Users (DAU/MAU)
  - Session Duration
  - Feature Adoption Rate
  - Stickiness (DAU/MAU)
 
Quality:
  - Net Promoter Score (NPS)
  - Customer Satisfaction (CSAT)
  - Bug/Issue Count
  - Time to Resolution
 
Growth:
  - User Growth Rate
  - Activation Rate
  - Retention Rate
  - Churn Rate

Finance KPIs

yaml

Profitability:
  - Gross Margin
  - Net Profit Margin
  - EBITDA
  - Operating Margin
 
Liquidity:
  - Current Ratio
  - Quick Ratio
  - Cash Flow
  - Working Capital
 
Efficiency:
  - Revenue per Employee
  - Operating Expense Ratio
  - Days Sales Outstanding
  - Inventory Turnover

Dashboard Layout Patterns

Pattern 1: Executive Summary

┌─────────────────────────────────────────────────────────────┐
│  EXECUTIVE DASHBOARD                        [Date Range ▼]  │
├─────────────┬─────────────┬─────────────┬─────────────────┤
│   REVENUE   │   PROFIT    │  CUSTOMERS  │    NPS SCORE    │
│   $2.4M     │    $450K    │    12,450   │       72        │
│   ▲ 12%     │    ▲ 8%     │    ▲ 15%    │     ▲ 5pts     │
├─────────────┴─────────────┴─────────────┴─────────────────┤
│                                                             │
│  Revenue Trend                    │  Revenue by Product     │
│  ┌───────────────────────┐       │  ┌──────────────────┐   │
│  │    /\    /\          │       │  │ ████████ 45%     │   │
│  │   /  \  /  \    /\   │       │  │ ██████   32%     │   │
│  │  /    \/    \  /  \  │       │  │ ████     18%     │   │
│  │ /            \/    \ │       │  │ ██        5%     │   │
│  └───────────────────────┘       │  └──────────────────┘   │
│                                                             │
├─────────────────────────────────────────────────────────────┤
│  🔴 Alert: Churn rate exceeded threshold (>5%)              │
│  🟡 Warning: Support ticket volume 20% above average        │
└─────────────────────────────────────────────────────────────┘

Pattern 2: SaaS Metrics Dashboard

┌─────────────────────────────────────────────────────────────┐
│  SAAS METRICS                     Jan 2024  [Monthly ▼]     │
├──────────────────────┬──────────────────────────────────────┤
│  ┌────────────────┐  │  MRR GROWTH                          │
│  │      MRR       │  │  ┌────────────────────────────────┐  │
│  │    $125,000    │  │  │                          /──   │  │
│  │     ▲ 8%       │  │  │                    /────/      │  │
│  └────────────────┘  │  │              /────/            │  │
│  ┌────────────────┐  │  │        /────/                  │  │
│  │      ARR       │  │  │   /────/                       │  │
│  │   $1,500,000   │  │  └────────────────────────────────┘  │
│  │     ▲ 15%      │  │  J  F  M  A  M  J  J  A  S  O  N  D  │
│  └────────────────┘  │                                      │
├──────────────────────┼──────────────────────────────────────┤
│  UNIT ECONOMICS      │  COHORT RETENTION                    │
│                      │                                      │
│  CAC:     $450       │  Month 1: ████████████████████ 100%  │
│  LTV:     $2,700     │  Month 3: █████████████████    85%   │
│  LTV/CAC: 6.0x       │  Month 6: ████████████████     80%   │
│                      │  Month 12: ██████████████      72%   │
│  Payback: 4 months   │                                      │
├──────────────────────┴──────────────────────────────────────┤
│  CHURN ANALYSIS                                             │
│  ┌──────────┬──────────┬──────────┬──────────────────────┐ │
│  │ Gross    │ Net      │ Logo     │ Expansion            │ │
│  │ 4.2%     │ 1.8%     │ 3.1%     │ 2.4%                 │ │
│  └──────────┴──────────┴──────────┴──────────────────────┘ │
└─────────────────────────────────────────────────────────────┘

Pattern 3: Real-time Operations

┌─────────────────────────────────────────────────────────────┐
│  OPERATIONS CENTER                    Live ● Last: 10:42:15 │
├────────────────────────────┬────────────────────────────────┤
│  SYSTEM HEALTH             │  SERVICE STATUS                │
│  ┌──────────────────────┐  │                                │
│  │   CPU    MEM    DISK │  │  ● API Gateway      Healthy    │
│  │   45%    72%    58%  │  │  ● User Service     Healthy    │
│  │   ███    ████   ███  │  │  ● Payment Service  Degraded   │
│  │   ███    ████   ███  │  │  ● Database         Healthy    │
│  │   ███    ████   ███  │  │  ● Cache            Healthy    │
│  └──────────────────────┘  │                                │
├────────────────────────────┼────────────────────────────────┤
│  REQUEST THROUGHPUT        │  ERROR RATE                    │
│  ┌──────────────────────┐  │  ┌──────────────────────────┐  │
│  │ ▁▂▃▄▅▆▇█▇▆▅▄▃▂▁▂▃▄▅ │  │  │ ▁▁▁▁▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁  │  │
│  └──────────────────────┘  │  └──────────────────────────┘  │
│  Current: 12,450 req/s     │  Current: 0.02%                │
│  Peak: 18,200 req/s        │  Threshold: 1.0%               │
├────────────────────────────┴────────────────────────────────┤
│  RECENT ALERTS                                              │
│  10:40  🟡 High latency on payment-service (p99 > 500ms)    │
│  10:35  🟢 Resolved: Database connection pool recovered     │
│  10:22  🔴 Payment service circuit breaker tripped          │
└─────────────────────────────────────────────────────────────┘

Implementation Patterns

Define reporting timezone, currency/conversion date, numerator/denominator and comparison period for each card. Do not mix percent changes with percentage points or NPS points. ARR = 12 × MRR implies equal growth rates when using the same period and definition. These synthetic layout figures are not reconciled accounts. Require access controls, aggregation/minimum cohort sizes and freshness/coverage labels before showing customer/employee or financial data; avoid exporting raw PII. Email opens/clicks can include privacy proxies/bots and are not direct engagement proof.

SQL for KPI Calculations

Use resources/metric-queries.sql for executable normalized-input examples. users contains one row per customer, events contains user/month observations, spend contains source spend rows, and monthly_revenue contains one reconciled amount per month. Represent months as an integer year × 12 + month − 1 so offsets do not wrap after December.

The queries keep the original cohort denominator, deduplicate activity before counting, aggregate spend before joining customers, and return NULL for undefined growth or acquisition cost. Missing cohort/month combinations need an explicit reporting calendar if zero-activity rows must be displayed. The growth query compares consecutive available rows; require a complete monthly calendar or label gaps as unavailable rather than calling a multi-month change monthly growth. Match spend and acquired-customer channel/time cohorts before interpreting CAC. Normalize subscription intervals, currency, refunds and revenue recognition before producing monthly revenue; these examples do not define accounting policy.

Python Dashboard Code (Streamlit)

python

import streamlit as st
import pandas as pd
import plotly.express as px
import plotly.graph_objects as go
st.set_page_config(page_title="KPI Dashboard", layout="wide")
# Synthetic layout illustration; this is not a connected or filterable dashboard.
# Header with illustrative date selector
col1, col2 = st.columns([3, 1])
with col1:
    st.title("Executive Dashboard")
with col2:
    date_range = st.selectbox(
        "Period",
        ["Last 7 Days", "Last 30 Days", "Last Quarter", "YTD"]
    )
# KPI Cards
def metric_card(label, value, delta, prefix="", suffix="", delta_unit="%", lower_is_better=False):
    st.metric(
        label=label,
        value=f"{prefix}{value:,.1f}{suffix}",
        delta=f"{delta:+.1f}{delta_unit}",
        delta_color="inverse" if lower_is_better else "normal",
    )
col1, col2, col3, col4 = st.columns(4)
with col1:
    metric_card("Revenue", 2400000, 12.5, prefix="$")
with col2:
    metric_card("Customers", 12450, 15.2)
with col3:
    metric_card("NPS Score", 72, 5.0, delta_unit=" pts")
with col4:
    metric_card("Churn Rate", 4.2, -0.8, suffix="%", delta_unit=" pp", lower_is_better=True)
# Charts
col1, col2 = st.columns(2)
with col1:
    st.subheader("Revenue Trend")
    revenue_data = pd.DataFrame({
        'Month': pd.date_range('2024-01-01', periods=12, freq='ME'),
        'Revenue': [180000, 195000, 210000, 225000, 240000, 255000,
                    270000, 285000, 300000, 315000, 330000, 345000]
    })
    fig = px.line(revenue_data, x='Month', y='Revenue',
                  line_shape='spline', markers=True)
    fig.update_layout(height=300)
    st.plotly_chart(fig, use_container_width=True)
with col2:
    st.subheader("Revenue by Product")
    product_data = pd.DataFrame({
        'Product': ['Enterprise', 'Professional', 'Starter', 'Other'],
        'Revenue': [45, 32, 18, 5]
    })
    fig = px.pie(product_data, values='Revenue', names='Product',
                 hole=0.4)
    fig.update_layout(height=300)
    st.plotly_chart(fig, use_container_width=True)

This is the start of the file. Read the full SKILL.md on GitHub.

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Source

SKILL.md in the repositoryCheckingskills/kpi-dashboard-design/SKILL.md

Popularity

Repository stars: 27,440
Repository forks: 4,624
Repository npm downloads, 7 days: 11,772
7-day trend score: 72

Stars and forks are for the whole GitHub repository, not this skill alone. Downloads are for the repository's npm package. Refreshed 21 Mar 2026, 7 months ago.

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