This repository contains the analysis and implementation of A/B tests aimed at optimizing product sales and service offerings.
The hypothesis is that the current pricing of the product might be on the higher side, which could be impacting sales. Reducing the product price is believed to potentially increase the sales frequency and overall profitability.
An A/B test is conducted with two groups:
- Control Group: Products are sold at the original price.
- Test Group: Products are sold at a reduced price.
The objective of this A/B test is to validate if reducing the price indeed increases the product's profitability.
- Significance Level (Alpha): 5%
- Minimum Detectable Effect: 5% change in the target metric
- Statistical Power (1 - Beta): 80%
The Central Bank has eased certain regulations that previously limited the options for selling services. There is an opportunity to adopt a more aggressive sales approach for the services. However, there are concerns that this might have a negative impact on the core product (credit card) economics due to possible customer dissatisfaction.
An A/B test is conducted by dividing the customer flow into two groups:
- Control Group: Service is offered in the current manner.
- Test Group: Service is offered aggressively.
The objective of this A/B test is to determine whether a more aggressive sales approach for services leads to positive or negative changes in the core product's (credit card) economics.
- Significance Level (Alpha): 5%
- Minimum Detectable Effect: 5% change in the target metric
- Statistical Power (1 - Beta): 80%
It is essential to carefully plan and analyze A/B tests for optimizing product sales and service offerings. Adherence to statistical principles and significance criteria is key to obtaining reliable results.