A/B Testing: Case Study

Download the dataset below to solve this Data Science case study on A/B Testing. (Dataset source: Kaggle)

A/B Testing Case Study

A/B testing helps in finding a better approach to finding customers, marketing products, getting a higher reach, or anything that helps a business convert most of its target customers into actual customers.

Here is a dataset based on A/B testing submitted by İlker Yıldız on Kaggle. Below are all the 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

Two campaigns were performed by the company:

1. Control Campaign
2. Test Campaign

Perform A/B testing to find the best campaign for the company to get more customers.

References to Solve this Data Science Case Study

• A/B Testing by Aman Kharwal
• A/B Testing by Mohammed Elshennawy
• Complete Guide to A/B Testing Design, Implementation and Pitfalls