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๐ƒ๐ข๐ฌ๐œ๐ฎ๐ฌ๐ฌ๐ข๐ง๐  ๐๐จ๐ฐ๐ž๐ซ ๐๐ˆ ๐ฌ๐œ๐ž๐ง๐š๐ซ๐ข๐จ ๐›๐š๐ฌ๐ž๐ ๐ช๐ฎ๐ž๐ฌ๐ญ๐ข๐จ๐ง ๐Ÿ’ก

๐‘บ๐’„๐’†๐’๐’‚๐’“๐’Š๐’ ๐Ÿ‘‡
You are a data analyst for a global e-commerce company. You need to analyze the performance of your marketing campaigns across different regions and identify which campaigns have the highest return on investment (ROI). Additionally, you want to see how customer acquisition costs (CAC) vary by region and campaign.

๐‘ธ๐’–๐’†๐’”๐’•๐’Š๐’๐’ ๐Ÿ‘‡
How would you use Power BI to create a comprehensive report on marketing campaign performance and ROI analysis?

๐‘จ๐’๐’”๐’˜๐’†๐’“:
For this we are provided with three datasets:

๐‚๐š๐ฆ๐ฉ๐š๐ข๐ ๐ง๐ฌ: CampaignID, CampaignName, Region, StartDate, EndDate, Budget
๐’๐š๐ฅ๐ž๐ฌ: SaleID, CampaignID, SaleAmount, SaleDate
๐„๐ฑ๐ฉ๐ž๐ง๐ฌ๐ž๐ฌ: ExpenseID, CampaignID, ExpenseAmount, ExpenseDate

โ–ถ ๐‘บ๐’•๐’†๐’‘ 1: Analyze the dataset thoroughly and perform some data cleaning and transformation steps ๐Ÿ“ˆ

โ–ถ ๐‘บ๐’•๐’†๐’‘ 2: Create Measures that are required in accordance with scenario given.

Total Sales = SUM(Sales[SaleAmount])
Total Expenses = SUM(Expenses[ExpenseAmount])
ROI = DIVIDE([Total Sales] - [Total Expenses], [Total Expenses])
Customer Acquisition Cost (CAC): CAC = DIVIDE([Total Expenses], DISTINCTCOUNT(Sales[SaleID]))

โ–ถ ๐‘บ๐’•๐’†๐’‘ 3: Use appropriate filters and visuals according to your requirements. You may use clustered column chart for CAC by region, line chart for sales and expense trends, can add slicers for region, campaign name, and date range, etc.

โ–ถ ๐‘บ๐’•๐’†๐’‘ 4: Analyze the project for some informative insights and trends.

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