Ad impressions metrics
An advertising company has developed a new ad to increase users' engagement with their questionnaire. The new ad was shown to a percentage of users in the exposed
group and a dummy ad was shown to the control
. Consider yourself the Data Analyst responsible for interpreting the results of the test. The first step you decide to take is to define and estimate useful metrics to begin evaluating the success of the marketing initiative.
Use what you've learned in the video to design success metrics and analyze the differences between the two experiment types in the experiment
column. The AdSmart
Kaggle dataset is loaded for you.
This exercise is part of the course
A/B Testing in Python
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Filter on users who responded
AdSmart_Responded = AdSmart[(AdSmart['____'] == ____) ____ (AdSmart['____'] == ____)]