This is a dataset of campaign exposure for a campaign that JetBlue ran with seve

This is a dataset of campaign exposure for a campaign that JetBlue ran with several types of tactics and channels combined with click and purchase data associated with the campaign.
Assignment:
1. Using Vlookups, append the values for Tactic_type, Digital_Campaign_Flag, Email_Flag, Social_flag and Domain_Type from the Lookups tab into the empty columns in the Data tab
2. Create a pivot table and calculate the Min Max Avg Sum for each Metric: Count of Customer_ID, sum of digital engagements, sum of clicks, sum of purchase, sum of cost_of_media. Add in Domain_type as a row or column and observe any obvious differences between the types of domains. Write down what you observe here and some theories about what it could mean.
3. In the pivot table and chart, create a daily trend for digital engagements and purchases by Tactic_Type and Exposure Type. What do you observe? Is the trend consistent day to day? Does the trend match between engagements and purchases? Explain what you’re seeing.
4. Calculate CPM in aggregate in the pivot table using calculated fields and observe the difference between Tactic_Types, Exposure_types and Domain_Types. What explanation is there for similarities or differences?
5. Dig deeper into the data and find something that could make a good story about a particular tactic, domain_type, group of customers, exposure types or anything else you find in the data. Write an anecdote about what this could mean supported by data and one chart. Two or three sentences minimum.
6. What kind of campaign optimization or insights would you recommend to the advertiser? Write two to three sentences supported by data and at least one chart.