2022 Q1 Marketing Report
In this Python project, I analyzed marketing data (90 records of analytics data, 45,211 records of leads data, and 20,736 records of campaign data) at a fictional small online seller and presented my findings to the marketing team at the end of the first quarter.
The questions I answered include:
- What were the KPI values for the quarter?
- Which demographic groups generated the most revenue?
- What does our sales funnel look like going into the second quarter?
- What was our ROI for the purchase of those leads if they cost $50K?
- Were our email campaigns at the end of January (A) and beginning of March (B) effective?
- Which marketing campaign was more successful, A or B?
In summary:
- Purchase more leads. The recent purchase led to a 326% return on investment.
- Target high-income 30-50-year-olds. They generate the most revenue.
- Continue email campaigns. Both campaigns were successful in increasing views and purchases. Campaign B somewhat performed better than Campaign A based on KPIs; therefore, our next step is to determine the reason for this outcome.
Tools: Excel, Python, PowerPoint