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 |
A structured approach to reviewing product metrics at weekly, monthly, and quarterly intervals. Each review has a different purpose, audience, and depth.
Purpose: Catch problems early, keep the team aligned on short-term trends.
Duration: 30 minutes
Audience: Product team, engineering leads
Data sources: Engagement metrics, conversion funnel
## Weekly Metrics Review — Week of [date]
### 1. North Star Check (5 min)
- Current value: [X]
- vs. last week: [+/-X%]
- vs. target: [on track / behind / ahead]
- Trend (4-week): [improving / declining / flat]
### 2. Engagement Snapshot (5 min)
- DAU: [X] (vs. [last week])
- WAU: [X]
- Stickiness (DAU/MAU): [X%]
- Noteworthy pattern: [e.g., "Tuesday DAU spike from email campaign"]
### 3. Conversion Funnel (10 min)
- Visitor → Signup: [X%] (vs. [target])
- Signup → Activated: [X%]
- Trial → Paid: [X%]
- Biggest drop-off this week: [stage] — why? [hypothesis]
### 4. Alerts & Anomalies (5 min)
- [Any metric that hit an alert threshold this week]
- [Any unexplained change]
### 5. Actions for Next Week (5 min)
- [What will we do to improve the metric that needs attention?]
- [Who owns each action?]Purpose: Assess progress against monthly targets, identify systemic trends, plan next month's focus.
Duration: 60 minutes
Audience: Product team, engineering, design, leadership
Data sources: All dashboards — engagement, retention, conversion, revenue, NPS
## Monthly Metrics Review — [Month Year]
### 1. Executive Summary (5 min)
- MRR: $[X] ([+/-X%] MoM, target: $[X])
- Total customers: [X] (net [+/-X])
- North Star: [X] (vs. target)
- NPS: [X] (vs. last month)
- Overall: [On track / Needs attention / Off track]
### 2. Revenue Deep Dive (15 min)
- MRR waterfall: New $[X] + Expansion $[X] - Contraction $[X] - Churn $[X] = Net $[X]
- ARPU: $[X] (trend: [up/down/flat])
- Quick Ratio: [X] (target: >4)
- LTV: $[X] (trend)
- Revenue churn: [X%] gross, [X%] net
### 3. Retention & Engagement (15 min)
- Cohort retention: [latest cohort month-1 retention: X%]
- vs. previous cohorts: [better / worse / same]
- Engagement trends: DAU growth [X%], feature adoption changes
- Churn analysis: [top 3 reasons from churned users this month]
### 4. Conversion Funnel (10 min)
- End-to-end conversion: [X%] (vs. target [X%])
- Per-step analysis: [which step had the biggest improvement/decline]
- Experiments this month: [what was tested, what were the results]
### 5. NPS & Satisfaction (5 min)
- NPS: [X] (trend)
- Top positive theme: [X]
- Top negative theme: [X]
- Notable verbatim feedback: "[quote]"
### 6. Next Month Focus (10 min)
- Metric to improve: [X]
- Target: [X] → [Y]
- Actions planned: [1, 2, 3]
- Experiments to run: [1, 2]
- Risks to watch: [1, 2]Purpose: Strategic assessment of product health, goal setting for next quarter, board-level reporting.
Duration: 90-120 minutes
Audience: Leadership team, potentially board
Data sources: All dashboards + qualitative research + competitive analysis
## Quarterly Metrics Review — [Q# Year]
### 1. Quarter in Review (10 min)
- Starting MRR → Ending MRR: $[X] → $[Y] ([Z%] growth)
- Starting customers → Ending: [X] → [Y]
- North Star: [start] → [end] (target was [X])
- NPS: [start] → [end]
### 2. Goal Assessment (15 min)
| Goal | Target | Actual | Status |
|------|--------|--------|--------|
| [Goal 1] | [target] | [actual] | Hit / Missed / Exceeded |
| [Goal 2] | [target] | [actual] | |
| [Goal 3] | [target] | [actual] | |
| [Goal 4] | [target] | [actual] | |
### 3. Growth Analysis (20 min)
- MRR growth: [X%] quarter — breakdown by new, expansion, churn
- Customer acquisition cost: $[X] (vs. target, vs. LTV)
- Payback period: [X months]
- Channel performance: which channels drove growth, which underperformed
- Retention curve comparison: [this quarter's cohorts vs. previous quarters]
### 4. Product Health (20 min)
- Feature adoption trends: which features grew, which declined
- Platform reliability: uptime, p95 latency, incident count
- Support ticket volume and categories: [trends]
- User research findings this quarter: [top 3 insights]
### 5. Competitive Landscape (10 min)
- Notable competitor moves: [new features, pricing changes, acquisitions]
- Win/loss analysis: why did we win/lose deals this quarter?
- Market positioning: has anything changed?
### 6. Next Quarter Goals (15 min)
| Goal | Target | Owner | Key Inputs |
|------|--------|-------|------------|
| [Goal 1] | [target] | [person/team] | [what drives this] |
| [Goal 2] | [target] | | |
| [Goal 3] | [target] | | |
### 7. Risks & Opportunities (10 min)
- Top 3 risks to next quarter's targets
- Top 3 opportunities to accelerate growth
- Resource needs: [any headcount, budget, or tooling requests]Set up automated alerts for these conditions:
| Metric | Alert Condition | Urgency |
|---|---|---|
| DAU | Drops >15% from 7-day average | High — investigate same day |
| Signup conversion | Drops below 3% for 3+ consecutive days | Medium — investigate within 48 hours |
| Trial-to-paid | Drops below 15% for a cohort | Medium — investigate within 1 week |
| MRR churn | Exceeds 5% in any single month | High — investigate immediately |
| NPS | Drops below 20 | High — investigate within 1 week |
| Onboarding completion | Drops below 60% | Medium — investigate within 1 week |
| Error rate / downtime | Exceeds 1% error rate or 5+ minutes downtime | Critical — investigate immediately |
| ARPU | Drops >10% MoM | Medium — investigate within 2 weeks |