A/B-Test-

A/B Test Project:

Features in the dataset:

1. Campaign Name: The name of the campaign
2. Date: Date of the record
3. Spend: Amount spent on the campaign in dollars
4. #of Impressions: Number of impressions the ad crossed through the campaign
5. Reach: The number of unique impressions received in the ad
6. #of Website Clicks: Number of website clicks received through the ads
7. #of Searches: Number of users who performed searches on the website
8. #of View Content: Number of users who viewed content and products on the website
9. #of Add to Cart: Number of users who added products to the cart
10. #of Purchase: Number of purchases

Data sets

• control_group.csv
• test_group.csv

Exploratory Data Analysis

• Importing necessary Libraries
• Checking NULL Values
• Filling of NULL values with mean
• Merging the two Data sets (control_group and test_group)
• Check whether it have Equal number of samples

A/B test

• Checking number of impressions in both Campaigns
• Number of searches performed on website from both Campaigns
• Number of website clicks on both Campaigns
• Amount of content viewed from both Campaigns after reaching the website
• Number of products added to the cart from both Campaigns
• Amount spent on each Campaigns
• Purchases made from each Campaigns
• Website clicks v/s Content viewed
• Content viewed v/s Number of products added to cart
• Number of products added to cart v/s Number of sales

Authors

• @rathan-code