1) First ask: What question are you answering? (Fast decision guide)
✅ A) Compare values across categories
➡️ Use Bar/Column chart
Examples:
- “Which product sold the most?”
- “Which region has highest revenue?”
✅ B) Trend over time (change, seasonality)
➡️ Use Line / Area / Combo chart
Examples:
- “Monthly revenue trend last 24 months”
- “Tickets trend day-by-day”
✅ C) Part-to-whole (composition)
➡️ Use Treemap / 100% stacked bar (avoid pie unless very few categories)
Examples:
- “Revenue contribution by product category”
- “Spend by cost head”
✅ D) Relationship / correlation
➡️ Use Scatter/Bubble chart
Examples:
- “Does discount % increase sales?”
- “Does delivery time impact customer rating?”
✅ E) Distribution (how values spread)
➡️ Use Histogram (custom) / Box plot (custom) / Column with bins
Examples:
- “Order value distribution”
- “Response time distribution (SLA)”
✅ F) Progress vs Target / KPI tracking
➡️ Use KPI / Card / Gauge (limited use) / Bullet chart (best if available)
Examples:
- “Sales vs Target”
- “SLA compliance %”
✅ G) Flow / stages (pipeline)
➡️ Use Funnel (only when it truly narrows stage-by-stage)
Examples:
- “Leads → Qualified → Proposal → Won”
✅ H) Contribution to change
➡️ Use Waterfall chart
Examples:
- “Why profit changed from last month to this month?”
✅ I) Ranking changes over time
➡️ Use Ribbon chart
Examples:
- “Top 5 products rank by month”
✅ J) Detailed reporting / audit view
➡️ Use Table / Matrix
Examples:
- “Invoice-level detail”
- “P&L with hierarchy (GL → Sub-GL → Account)”
✅ K) Geography-based insights
➡️ Use Map / Filled map (only when geography matters)
Examples:
- “Sales by state/district”
- “Service tickets by city”
2) Visuals explained with when to use + real case
2.1 Bar / Column (Most used)
Best for: Comparing categories; ranking.
When to choose:
- More than 5–7 categories? Prefer bar (horizontal) for readability.
- Need Top N? Use bar + Top N filter.
Real case: Retail Sales Dashboard
- Visual: Bar chart
- Question: “Top 10 SKUs by Revenue”
- Slice by: Region, Channel, Month
✅ Clear ranking, easy to compare.
Avoid: Too many categories without Top N (becomes clutter).
2.2 Line chart (Trend over time)
Best for: Time series (daily/weekly/monthly).
Real case: Support Ops
- Visual: Line
- Metric: Tickets created vs resolved per day
- Insight: Identify backlog growth or improvements.
Best practice: Add moving average or trend line for noisy data.
2.3 Combo chart (Line + Column)
Best for: Two metrics with different behavior (e.g., volume + rate).
Real case: Sales Performance
- Columns: Monthly Sales
- Line: Gross Margin %
This helps answer: “Sales increased but did margin drop?”
2.4 Stacked / 100% Stacked
Best for: Composition across categories (and change over time).
- Stacked bar: shows absolute + composition
- 100% stacked: shows share % only
Real case: HR Analytics
- 100% stacked by Month: Attrition split (Voluntary / Involuntary)
Shows “attrition mix changing?” irrespective of total.
2.5 Treemap (Part-to-whole with many categories)
Best for: Many categories where you want quick proportional view.
Real case: IT Spend
- Treemap: Cost by Vendor → Service Type
Instantly shows biggest spend blocks.
Avoid: Precise comparison (humans struggle comparing rectangle areas).
2.6 Pie/Donut (Use carefully)
Use only if:
- Max 2–5 categories
- One category clearly dominates
Real case: Payment Method Share (UPI, Card, COD, Wallet) if only 4.
Avoid: 10 slices = unreadable. Use bar instead.
2.7 Waterfall (Explaining variance)
Best for: “What changed and why?”
Real case: Finance
- Profit change from Q1 to Q2 explained by: Price effect, Volume effect, Cost increase, FX impact.
Perfect for bridge analysis.
2.8 Scatter / Bubble (Correlation + outliers)
Best for: Relationship between 2 measures, detect clusters/outliers.
Real case: E-commerce pricing
- X: Discount %
- Y: Units sold
- Bubble size: Revenue
Helps answer: “Which products respond to discount and which don’t?”
2.9 Funnel (Stage drop-off)
Best for: Sequential stages with drop-offs.
Real case: Sales CRM pipeline
- Leads → Qualified → Proposal → Closed
Shows conversion and leakage.
Avoid: If your process isn’t sequential (then use bar).
2.10 KPI / Card / Gauge (Single number)
Card: “Total Sales”, “Total Tickets”, “MTTR”
KPI visual: shows value + target + trend
Gauge: okay for exec view, but limited comparison (bullet is better).
Real case: SLA Monitoring
- KPI: SLA compliance % vs target 95% with trend over time
- Cards: Open tickets, Avg resolution time
2.11 Table vs Matrix (Detail & Hierarchies)
Table: flat row-level detail (invoice list, ticket list)
Matrix: hierarchical (Region → Country → City, or GL hierarchy)
Real case: P&L report
- Matrix: Revenue, COGS, Opex with drill-down
- Conditional formatting for variance % (green/red)
2.12 Decomposition Tree (Root cause analysis)
Best for: “Why is this high/low?” with drill-based explanation.
Real case: Manufacturing defects
- Start: Total Defects
- Drill: Plant → Line → Shift → Operator → Defect type
Great for operations and RCA.
2.13 Key Influencers (Driver analysis)
Best for: “What factors influence churn / late delivery / defect?”
Real case: Customer churn
- Target: Churn = Yes/No
- Explain by: Tenure, plan type, complaints, region
Gives data-driven drivers quickly.
2.14 Maps (Geography)
Use if location matters and you have geo fields (state/city/lat-long).
Real case: Service Coverage
- Filled map by state: ticket density
- Drill to city hotspots
Avoid: If geography is just a label and doesn’t add insight.
3) Common mistakes (and what to do instead)
❌ Using Pie for everything
✅ Use bar/treemap for many categories.
❌ Too many visuals on one page
✅ Use 3–6 strong visuals, then drill-through for details.
❌ No context (no target, no benchmark)
✅ Add target lines, previous period, variance %, tooltips.
❌ Same scale issues in combo charts
✅ Use combo only when it makes sense; ensure right axis is clear.
4) Recommended “real dashboard layouts” (templates)
Template A: Sales Performance (Exec)
- Cards: Revenue, Profit, Margin%, YoY%
- Line: Revenue trend (Monthly)
- Bar: Top 10 Products
- Map: Revenue by state (optional)
- Waterfall: Profit variance vs last quarter
- Matrix: Region → Channel breakdown with drill
Template B: Ops / Support
- KPI: SLA%, MTTR
- Line: Created vs Resolved tickets
- Bar: Tickets by Category
- Scatter: Resolution time vs CSAT (outliers)
- Table: Ticket-level drill-through
5) Quick cheat-sheet (one-liners)
- Compare categories: Bar/Column
- Trend: Line
- Trend + Target: Line + constant line / KPI
- Part-to-whole (many): Treemap / stacked
- Explain change: Waterfall
- Correlation/outliers: Scatter
- Pipeline stages: Funnel
- Geography: Map
- Root cause drill: Decomposition tree
- Drivers: Key influencers
- Details/audit: Table/Matrix
