How to build useful product dashboards from the CSV templates in this toolkit. This guide is tool-agnostic — it focuses on which charts to build and why, not which buttons to click in a specific BI tool.
Before building anything, internalize these principles:
| Principle | Explanation |
|---|---|
| One dashboard, one audience | An executive dashboard is not an engineering dashboard. Build separate views for each audience. |
| Answer questions, not display data | Every chart should answer a specific question. "How are we growing?" is a question. "DAU time series" is just data. |
| Top-left = most important | People read dashboards like they read pages — top-left first. Put your North Star metric there. |
| Context over numbers | A number without comparison is meaningless. Always show: current value vs. previous period vs. target. |
| Fewer charts, bigger charts | 4-6 well-designed charts beat 15 tiny ones. If you need 15 charts, you need multiple dashboards. |
Build these 4 dashboards, in this priority order:
Audience: CEO, VP Product, board
Update frequency: Weekly
Data sources: revenue-mrr.csv, engagement-metrics.csv, nps-tracking.csv
| Position | Chart | Source Column(s) | Chart Type | Question It Answers |
|---|---|---|---|---|
| Top-left (hero) | North Star metric | Depends on your North Star | Big number + sparkline | "Are we winning?" |
| Top-center | MRR trend | total_mrr over time | Line chart | "How is revenue growing?" |
| Top-right | NPS trend | nps_score over time | Line chart with zones (red/yellow/green) | "Are customers happy?" |
| Middle-left | Customer growth | total_customers, new_customers, churned_customers | Stacked bar | "Are we growing net customers?" |
| Middle-right | Key conversion rates | Calculated from conversion-funnel.csv | Funnel visualization or horizontal bar | "Where is the funnel leaking?" |
| Bottom | DAU/WAU/MAU trend | From engagement-metrics.csv | Multi-line chart | "Is engagement growing?" |
Audience: Growth team, product marketing
Update frequency: Weekly
Data sources: conversion-funnel.csv, engagement-metrics.csv
| Position | Chart | Source Column(s) | Chart Type |
|---|---|---|---|
| Top-left | Visitor → Signup rate | visitor_to_signup_pct | Line chart with target line |
| Top-right | Signup → Activation rate | onboard_to_activated_pct | Line chart with target line |
| Middle-left | Full funnel | All funnel stages | Funnel chart (horizontal bars showing each stage) |
| Middle-right | Stage-by-stage drop-off | Calculated stage drop-offs | Bar chart (one bar per stage showing % lost) |
| Bottom-left | Overall conversion rate | overall_conversion_pct | Line chart with trend line |
| Bottom-right | Weekly signup volume | signups | Bar chart |
Audience: Product team, customer success
Update frequency: Monthly (retention), daily (engagement)
Data sources: retention-cohort.csv, engagement-metrics.csv
| Position | Chart | Source Column(s) | Chart Type |
|---|---|---|---|
| Top-left | Cohort retention matrix | All month_N_pct columns | Heatmap (darker = higher retention) |
| Top-right | Retention curves | Same data, pivoted | Multi-line chart (one line per cohort) |
| Middle-left | Stickiness ratio | dau / mau | Line chart |
| Middle-right | Feature adoption | feature_a/b/c_adoption_pct | Grouped bar chart |
| Bottom-left | Session metrics | avg_session_duration_min, sessions_per_user | Dual-axis line chart |
| Bottom-right | Platform split | mobile_pct, desktop_pct | Stacked area chart |
Audience: Finance, executive team
Update frequency: Monthly
Data sources: revenue-mrr.csv
| Position | Chart | Source Column(s) | Chart Type |
|---|---|---|---|
| Top-left | MRR waterfall | new_mrr, expansion_mrr, contraction_mrr, churned_mrr | Waterfall chart (shows contributions to MRR change) |
| Top-right | ARR trend | arr | Line chart with year targets |
| Middle-left | Revenue churn | gross_churn_rate_pct, net_churn_rate_pct | Dual-line chart |
| Middle-right | Quick Ratio | quick_ratio | Line chart with threshold line at 4.0 |
| Bottom-left | ARPU trend | arpu | Line chart |
| Bottom-right | LTV trend | ltv_estimate | Line chart |
1. Open Google Sheets → File → Import → Upload
2. Select the CSV file
3. Choose "Replace current sheet" or "Insert new sheet"
4. Separator: Comma (auto-detected)
1. Open Excel → Data → From Text/CSV
2. Select the CSV file
3. Encoding: UTF-8, Delimiter: Comma
4. Click "Load"
1. Most BI tools can import CSV as a data source
2. Alternatively, load CSVs into a database (PostgreSQL, SQLite) and connect the BI tool to the database
3. For ongoing tracking, set up automated data pipelines instead of manual CSV updates
| You want to show... | Use this chart type | Avoid |
|---|---|---|
| A trend over time | Line chart | Pie chart |
| Comparison across categories | Horizontal bar chart | 3D bar chart |
| Part-to-whole relationship | Stacked bar chart | Pie chart (hard to compare small segments) |
| Distribution of values | Histogram | Table (hard to see patterns) |
| Correlation between two metrics | Scatter plot | Dual-axis line (misleading) |
| A funnel or sequential process | Funnel chart or horizontal bars | Vertical bar chart |
| Cohort data | Heatmap or multi-line chart | Single line chart |
| A single important number | Big number card with comparison | A chart (overkill for one number) |
| Mistake | Why It's a Problem | Fix |
|---|---|---|
| Too many charts on one screen | Cognitive overload; nobody reads it | Max 6 charts per dashboard. Use tabs/pages for more |
| No time comparison | "MRR is $200K" means nothing without context | Always show vs. last period and vs. target |
| Pie charts for everything | Hard to compare slices, especially with many categories | Use bar charts. Pie charts only work for 2-3 segments |
| Dual Y-axes | Creates false visual correlations between unrelated metrics | Use separate charts side-by-side |
| Dashboard never gets updated | Stale data destroys trust. People stop looking. | Automate data refreshes or set a calendar reminder |
| No clear takeaway | People look at the dashboard and say "so what?" | Add a text block at the top with this week's key insight |
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