Marketing Mix Analysis with Python
Campaign impact and ROI visualization
About the project
This success story shows how jordan_digital approaches measurement when performance data is spread across channels. We structured the data, clarified the metrics that matter, and created visuals that make tradeoffs easy to understand—so teams can reallocate budget with confidence.
- 3 KPIs
- ROI, CAC, contribution
- 100%
- Channel visibility
- 3+
- Decision views
Project Type
Analytics & BI
Data Visualization
MarTech
Tech Stack / Toolbox
Python
Pandas
NumPy
Matplotlib
Plotly
SQL / ETL
Reporting
How jordan_digital Delivered Value
jordan_digital translated multi-channel campaign data into a clear measurement framework—connecting spend to outcomes and making optimization decisions easier for stakeholders.
- Consolidated campaign and channel data into an analysis-ready dataset.
- Defined consistent KPI logic (ROI, CAC, contribution) to reduce reporting ambiguity.
- Built visuals that highlight marginal impact and diminishing returns by channel.
- Identified optimization opportunities and created a repeatable reporting structure.
- Packaged findings in a stakeholder-friendly narrative for decision-making.