Why this matters
Marketing leaders rely on dashboards to spot wins, diagnose drops, and allocate budget. As a Marketing Analyst, you design dashboards that answer three questions fast: Are we on track? Why or why not? What should we do next?
- Weekly performance reviews: Track revenue, CAC/ROAS, and channel mix.
- Campaign launches: Monitor early leading indicators (CTR, CPC, CPA) before lagging outcomes settle.
- Budget shifts: Move spend to top-performing channels with guardrails in place.
Concept explained simply
A Marketing KPI Dashboard is a single page showing outcomes (e.g., revenue, signups), drivers (e.g., traffic, conversion), and guardrails (e.g., CAC, spam complaints) with trends and breakdowns.
Mental model
- North Star → Outcomes → Drivers → Inputs. Example: Revenue → Orders → Sessions × Conversion × AOV → Channels, Creatives, Bids.
- Three viewing layers: Overview (are we okay?) → Diagnose (where is the gap?) → Explore (which lever to pull?).
- Guardrails: Metrics you must not break while pursuing growth (e.g., CAC target, unsubscribe rate).
KPI selection rules
- One north-star KPI plus 3–6 supporting outcomes; keep the page scannable.
- Mix lagging and leading indicators. Lagging: revenue, LTV. Leading: CTR, add-to-cart rate.
- Be controllable: select KPIs influenced by marketing, not only macro factors.
- Make definitions unambiguous: attribution model, lookback window, currency, timezone, dedup rules.
- Set targets and thresholds; show variance and status (on track/at risk/off track).
Data readiness checklist
- Attribution: model (last non-direct, data-driven), window (e.g., 7/28 days).
- Time: timezone, business calendar, week start, holiday handling.
- Identity: user/session dedup, UTMs/Channel taxonomy normalized.
- Currency: exchange rate date, gross vs net revenue, returns/cancellations treatment.
- Latency: refresh schedule stated (e.g., hourly), backfill behavior.
- Quality: outlier rules, missing data placeholders, footnote for caveats.
Design patterns that work
- Hero strip (top): 4–6 Big Number cards with variance vs target and YoY/ WoW.
- Trend panel: lines for key outcomes and guardrails with comparison period.
- Breakdown panel: bars or tables by channel, campaign, geo, device.
- Funnel panel: stage rates with absolute counts and conversion.
- Diagnostics: cost and efficiency (CPC, CPA, ROAS), creative performance, search terms.
- Context: annotations for launches, outages, algorithm updates.
- Controls: date range, channel, geo, product, device; saved default view.
Chart picker (when to use what)
- Line: time trends and comparisons (Actual vs Target, This vs Last period).
- Bar: ranked contributions (Top channels by revenue).
- Stacked bar: mix share (Channel mix %).
- Funnel: stage conversions (Sessions → Cart → Checkout → Purchase).
- Heatmap: cohort retention, day-of-week performance.
- Scatter: spend vs CPA trade-offs, outlier creatives.
Worked examples
Example 1 — Paid acquisition performance
- North star: New customers
- Outcomes: Orders, Revenue, CAC, ROAS
- Leading: Impressions, CTR, CPC, CVR (Click→Purchase)
- Guardrails: CAC ≤ target, frequency cap, creative fatigue
- Layout: Hero BANs (Orders, Revenue, CAC, ROAS); Trend lines for CAC/ROAS; Breakdown bar by channel; Scatter (Spend vs CPA); Funnel from Clicks→Purchase.
- Formulas: CAC = Spend / New Customers; ROAS = Revenue / Spend; CVR = Orders / Clicks.
Example 2 — Lifecycle/email KPI board
- North star: Activated users
- Outcomes: Activation rate, 7-day retention, Revenue per user
- Leading: Open rate, Click-to-open rate (CTOR), Onboarding step completion
- Guardrails: Bounce %, Spam complaints %, Unsubscribe rate
- Layout: Hero BANs (Activation, Retention); Trend (Open, CTOR, Unsub); Heatmap by day since signup; Table by journey step.
Example 3 — E-commerce trading dashboard
- North star: Revenue
- Outcomes: Orders, AOV, Gross margin
- Leading: Sessions, PDP view rate, Add-to-cart rate, Checkout completion
- Guardrails: Stockouts, Return rate
- Layout: Hero BANs (Revenue, Orders, AOV, Margin); Funnel; Trend Revenue vs Target; Breakdown by product category; Price vs Conversion scatter.
Step-by-step: build your first dashboard
- Define audience and decisions. Example: for channel managers making daily spend moves.
- Choose north star + supporting KPIs. Cap at 6–8 total on page.
- Map KPI tree from outcome to drivers and inputs.
- Write metric definitions (attribution, windows, formulas, thresholds).
- Draft a wireframe: hero → trend → breakdown → funnel → diagnostics.
- Select filters and benchmarks (target, last period, YoY).
- QA with scenarios: missing data, outliers, channel taxonomy edge cases.
- Annotate launches and finalize footnotes for assumptions.
Exercises
Do these. They mirror the graded exercises below.
Exercise 1 — Build a KPI tree for a subscription app
Pick the north star, define 5 KPIs (mix of lagging/leading), and write simple formulas and targets.
- North star suggestion: Paid conversions
- Include: Trials started, Trial→Paid rate, CAC, 7-day retention, LTV:CAC
Exercise 2 — Wireframe a marketing KPI dashboard
For an e-commerce site, sketch the layout in words. Specify sections, chart types, and filter set. Include at least one guardrail metric and one diagnostic view.
Self-check and common mistakes
Common mistakes
- Too many KPIs: makes the page noisy. Fix: limit to essentials and push detail to drill-downs.
- No targets: hard to judge performance. Fix: add target/forecast lines and variance.
- Mixed definitions: inconsistent attribution windows across sources. Fix: standardize and footnote.
- Only lagging metrics: slow to act. Fix: include leading indicators.
- Unclear time context: missing comparison period. Fix: show WoW/YoY and seasonality notes.
- Color misuse: red/green only. Fix: add icons/labels and colorblind-safe palette.
- Hidden anomalies: axes that truncate or auto-scale oddly. Fix: consistent scales or explicit annotations.
- No guardrails: growth at any cost. Fix: track CAC, quality, and compliance metrics.
- Static design: no filters. Fix: include date, channel, geo, device.
- No footnotes: users misinterpret. Fix: add clear metric definitions and caveats.
Quick self-check
- Can someone answer "Are we on track? Why? What to do?" in under 60 seconds?
- Is each KPI defined, target-backed, and refresh-cadenced?
- Is there at least one leading indicator and one guardrail?
- Do trends have meaningful comparison (target/YoY)?
- Do breakdowns match how teams make decisions (channel/campaign/geo)?
Practical projects
- Project 1: Create a paid performance dashboard with hero KPIs, CAC/ROAS trend, and channel breakdown.
- Project 2: Build a lifecycle dashboard for onboarding with funnel and retention heatmap.
- Project 3: Design an e-commerce funnel board and add a diagnostic scatter for Spend vs CPA by campaign.
Who this is for
- Marketing Analysts who present performance and drive budget decisions.
- Performance marketers who want reliable, actionable dashboards.
- Product marketers and CRM managers needing lifecycle visibility.
Prerequisites
- Basic marketing concepts: acquisition channels, conversion, CAC/ROAS.
- Comfort with metrics and simple formulas.
- Basic BI familiarity (filters, charts, calculated fields).
Learning path
- Start: This subskill to learn what to show and why.
- Next: Data modeling for reliable metric definitions.
- Then: Experiment dashboards (A/B, incrementality) and forecasting.
Mini challenge
Pick a recent campaign. Add one leading metric and one guardrail to your dashboard. Write the exact definition, target, and where it appears. Review impact after one week.
Next steps
- Draft a dashboard wireframe for your current team and review in a 15-minute session.
- Instrument annotations and targets; schedule refreshes.
- Iterate monthly—retire one metric, add one better diagnostic.
Quick Test
Anyone can take the Quick Test for free. If you log in, your result and progress will be saved.