Reporting & Performance
Reporting & Performance tests how you measure marketing against outcomes rather than activity. Expect attribution, dashboards, lifecycle reporting, campaign ROI, and experiment design.
Core rules
- Attribution assigns credit across touchpoints. First-touch favors awareness, last-touch favors conversion, and multi-touch models (linear, U-shaped, full path) spread credit. No model is the single truth; state the model when you report.
- Campaign ROI = (revenue - campaign cost) / campaign cost. Also track qualified pipeline, CAC, MQL-to-SQL rate, close rate, and LTV.
- Dashboards should answer a decision question. Separate traffic, conversion, and revenue views; use consistent date ranges and lifecycle definitions.
- A/B tests need one variable, a clear hypothesis, and enough sample to avoid false positives.
Worked example
Campaign A costs $2,000 and returns $10,000, so ROI is 400%. Campaign B costs $8,000 and returns $24,000, so ROI is 200%. A only sees A is more efficient. For a decision, compare qualified pipeline and close rates: if B produced 40 SQLs and A produced 6, B may be the better growth investment despite lower ROI. Reasoning: ROI is a ratio; absolute pipeline and payback matter for scaling.
Traps
- Reporting last-touch only and cutting awareness content.
- Celebrating impressions and clicks without pipeline.
- Comparing teams that use different attribution models.
- Changing multiple variables in one test.
- Using too short a window for a long sales cycle.