Why this matters
Marketing Analysts use Channel Performance Dashboards to answer weekly questions like:
- Which channels drive the most revenue efficiently this week?
- Did our CAC/CPA rise after a bid or creative change?
- Where should we reallocate budget today to hit targets?
- Which campaign, audience, device, or region needs attention?
The dashboard gives a single source of truth to prioritize actions, defend spend, and spot problems early.
Concept explained simply
A Channel Performance Dashboard is a scoreboard for your acquisition and retention channels (Paid Search, Paid Social, Display, Email, Affiliates, etc.). It pulls data from each source, aligns definitions, and shows KPIs over time and by breakdowns.
Mental model
- Inputs: Spend and impressions.
- Activity: Clicks/sessions and traffic quality (CTR, bounce, engaged sessions).
- Outcomes: Conversions and revenue (or sign-ups, MQLs).
- Efficiency: CPC, CPA/CAC, ROAS, LTV:CAC.
See a simple funnel
- Impressions → Clicks (CTR)
- Clicks → Conversions (CVR)
- Spend → Conversions (CPA/CAC)
- Spend → Revenue (ROAS)
Core metrics and formulas
- CTR = Clicks / Impressions
- CPC = Spend / Clicks
- CVR = Conversions / Clicks
- CPA (or CAC) = Spend / Conversions
- ROAS = Revenue / Spend
- Blended CAC = Total Spend / Total New Customers
- LTV:CAC = LTV / CAC (if LTV available; use cautious assumptions)
Note: Values vary by country/company; treat as rough ranges.
Data model and granularity
Recommended grain: Day × Channel × Campaign × Device × Country (adjust to your needs).
Common fields:
- Date, Channel, Source, Medium, Campaign, Ad Group/Set, Creative
- Device, Country/Region
- Spend, Impressions, Clicks
- Sessions, Conversions, Revenue (or Goal value), New Customers
Normalization tips
- Unify channel names (e.g., "meta" and "facebook" → "Paid Social")
- Map currencies to a single reporting currency
- Consistent attribution window and definition of "conversion"
- Use a Date dimension for flexible time filters (WTD, MTD, trailing 7/28)
Design the dashboard
- Define purpose: Budget allocation and performance monitoring.
- Audience: Growth manager, marketing analyst, channel owners.
- Key questions: What changed? Why? What to do next?
- Layout (suggested):
- Top row: KPIs (Spend, Revenue, Conversions, ROAS, CAC) vs last period
- Trends: ROAS, CAC, and Conversions by day
- Breakdown: Channel and Campaign performance
- Diagnostics: CTR, CPC, CVR, AOV; device/region split
- Actions: Budget shift suggestions or watchlist
Interaction design
- Global filters: Date, Country, Device, Funnel (Prospecting/Remarketing)
- Drilldown: Click channel → campaign → ad set/ad
- Threshold highlights: e.g., ROAS below target or CAC above target
Worked examples
Example 1: Rising CAC on Paid Social
Yesterday: Spend 8,000; Clicks 5,000; Conversions 200 → CPC 1.60; CVR 4%; CAC 40. Today: Spend 8,000; Clicks 4,000; Conversions 160 → CPC 2.00; CVR 4%; CAC 50. Diagnosis: CPC worsened (CTR down or CPM up). Action: Review creatives/targeting before raising bids.
Example 2: Which channel gets more budget?
Channel A: ROAS 4.0, CAC 25; Channel B: ROAS 1.75, CAC 40. If both meet quality thresholds, shift incremental budget toward A while testing B’s creatives to improve CVR.
Example 3: Blended ROAS sanity check
Total Spend 20,600; Total Revenue 71,000 → ROAS 3.45. If channel table sums to 3.45 but campaign table shows 3.7, you likely have exclusions (e.g., missing Affiliates). Reconcile totals before decisions.
Build it step-by-step (tool-agnostic)
- Connect data sources: ad platforms, analytics, and conversions.
- Normalize fields: currency, channel mapping, campaign naming rules.
- Create a Date table and mark relationships (Date → Fact table on day).
- Define measures: CTR, CPC, CVR, CAC, ROAS; ensure they use filters correctly.
- Add targets/benchmarks (e.g., CAC target per country).
- Design visuals and set consistent number formats and time comparisons.
- QA: total checks, spot anomalies, validate a sample against source platforms.
Measure design tips
- Use filters to scope metrics (e.g., Prospecting only)
- Prefer calculated measures over pre-aggregated fields
- Keep a "Definitions" panel: metric formulas and data sources
Interactivity & filters
- Date presets: Today, Yesterday, WTD, MTD, trailing 7/28/90
- Segment toggles: Prospecting vs Remarketing; New vs Returning customers
- Drillthrough: From Channel to Campaign details
- Hover tooltips: show CTR, CPC, CVR to diagnose quickly
Visual choices that work
- KPI cards: Spend, Revenue, Conversions, ROAS, CAC with delta vs last period
- Time series line charts: ROAS, CAC, Conversions
- Bar charts: ROAS and CAC by Channel/Campaign
- Stacked bars: Spend mix by Channel
- Tables for granular diagnostics with conditional formatting
Data quality checks
- Totals match source platforms within acceptable tolerance
- No negative or null spend/revenue unless expected
- CTR within realistic bounds (0%–30% typical ranges by channel)
- Sudden level shifts explained by changes in tracking or campaigns
- Currency and timezone consistent with reporting policy
Exercises
These mirror the interactive exercises below. Do them in a spreadsheet or BI tool.
Exercise 1: Compute KPIs and pick a winner
Data (per channel):
- Paid Search: Impr 120,000; Clicks 6,000; Spend 12,000; Conv 480; Revenue 48,000
- Paid Social: Impr 200,000; Clicks 5,000; Spend 8,000; Conv 200; Revenue 14,000
- Email: Impr 30,000; Clicks 1,200; Spend 600; Conv 150; Revenue 9,000
Task: Calculate CTR, CPC, CVR, CPA, ROAS by channel. Select the channel to receive +10% budget and briefly justify.
Exercise 2: Blended view and trends
Using the same data, compute Blended CAC and Blended ROAS. Then, if tomorrow Paid Social clicks drop to 4,000 (other fields unchanged), recompute its CPC, CVR, and CAC. Identify the most likely root cause.
- Checklist to self-verify:
- Have you used the correct formulas?
- Do totals equal the sum of channels?
- Did you explain the likely cause of CAC change?
Need a nudge?
Start with CTR = Clicks/Impr, CPC = Spend/Clicks, CVR = Conv/Clicks, CPA = Spend/Conv, ROAS = Revenue/Spend. For blended metrics, use totals.
Common mistakes & self-checks
- Mixing attribution definitions across channels. Fix: align windows and conversion types.
- Judging efficiency only by CTR. Fix: prioritize CAC/ROAS with CTR and CVR as diagnostics.
- Ignoring data freshness/timezones. Fix: show data last refreshed and standardize zones.
- Over-aggregating. Fix: keep drilldowns to campaign/ad set to find root causes.
- Not benchmarking. Fix: add targets and highlight variance.
Quick self-audit
- Can you explain why a KPI moved using upstream metrics?
- Do your totals reconcile with sources?
- Are default filters clear and documented?
Mini challenge
Yesterday, Prospecting channels show: Spend 10,000; Impr 300,000; Clicks 9,000; Conv 270; Revenue 28,000. Remarketing shows: Spend 3,000; Impr 40,000; Clicks 2,000; Conv 240; Revenue 22,000. Which gets more budget tomorrow and why? Include at least two metrics in your justification.
Who this is for
- Marketing Analysts who monitor acquisition and retention performance
- Growth managers allocating budgets
- BI developers supporting marketing stakeholders
Prerequisites
- Comfort with basic marketing metrics (CTR, CPC, CVR, CAC, ROAS)
- Basic spreadsheet or BI tool skills
- Understanding of how your company defines a "conversion"
Learning path
- Start: Channel Performance Dashboards (this lesson)
- Next: Campaign and Creative Diagnostics
- Then: Attribution comparisons and incrementality basics
- Finally: Forecasting and budget allocation scenarios
Practical projects
- Build a one-pager with KPI cards and a channel bar chart
- Add drilldown to campaign and ad set
- Implement a traffic-light ROAS/CAC color scheme vs targets
- Create a "Budget shift" panel with suggested reallocations
Next steps
- Integrate LTV estimates for LTV:CAC monitoring
- Automate QA checks and data refresh status
- Schedule a weekly review and action log
Quick test note
The quick test is available to everyone. Only logged-in users get saved progress.