Power BI Marketing Data Analysis
Budget: $250 – $750 USD
I have a large set of sales and marketing data and I need a clear, insight-driven analysis that zeroes in on marketing campaign effectiveness. All raw tables are already exported to Excel; what’s missing is the story that shows which campaigns are working, which audiences respond best, and where budget can be trimmed or re-allocated.
Here’s the flow I’m aiming for:
• Clean and structure the existing Excel data, flagging any gaps or anomalies.
• Build a data model in Power BI that links campaigns, spend, impressions, clicks, conversions, and revenue.
• Create intuitive visualisations—think funnel views, ROI heat maps, and time-series performance trends—that allow me to slice by channel, region, and customer segment.
• Summarise key findings in a brief narrative so stakeholders can act on them immediately.
Accuracy matters more than flashy graphics: calculations for cost per acquisition, lifetime value, and incremental lift must reconcile to the penny between Excel and Power BI. I’ll provide sample pivot tables as a reference for expected numbers.
Final deliverables: the cleaned Excel file, the .pbix report, and a short slide deck highlighting the main takeaways. If you’ve previously measured campaign lift or optimised marketing spend using DAX and Power Query, you’ll be up to speed quickly.
Here’s the flow I’m aiming for:
• Clean and structure the existing Excel data, flagging any gaps or anomalies.
• Build a data model in Power BI that links campaigns, spend, impressions, clicks, conversions, and revenue.
• Create intuitive visualisations—think funnel views, ROI heat maps, and time-series performance trends—that allow me to slice by channel, region, and customer segment.
• Summarise key findings in a brief narrative so stakeholders can act on them immediately.
Accuracy matters more than flashy graphics: calculations for cost per acquisition, lifetime value, and incremental lift must reconcile to the penny between Excel and Power BI. I’ll provide sample pivot tables as a reference for expected numbers.
Final deliverables: the cleaned Excel file, the .pbix report, and a short slide deck highlighting the main takeaways. If you’ve previously measured campaign lift or optimised marketing spend using DAX and Power Query, you’ll be up to speed quickly.
Related categories:
Excel
Analytics
Statistical Analysis
SPSS Statistics
Data Visualization
Data Analysis
Power BI
Data Modeling