Marketing Email Campaign takehome challenge. From A Collection of Data Science Takehome Challenges by Guilio Palombo.
The marketing team of an e-commerce site has launched an email campaign. This site has email addresses from all the users who created an account in the past.
They have chosen a random sample of users and emailed them. The email let the user know about a new feature implemented on the site. From the marketing team perspective, a success is if the user clicks on the link inside of the email. This link takes the user to the company site.
You are in charge of figuring out how the email campaign performed and were asked the following questions:
- What percentage of users opened the email and what percentage clicked on the link within the email?
- The VP of marketing thinks that it is stupid to send emails to a random subset and in a random way. Based on all the information you have about the emails that were sent, can you build a model to optimize in future email campaigns to maximize the probability of users clicking on the link inside the email?
- By how much do you think your model would improve click through rate ( defined as # of users who click on the link / total users who received the email). How would you test that?
- Did you find any interesting pattern on how the email campaign performed for different segments of users? Explain.