/AB_testing

Primary LanguageJupyter Notebook

A/B Testing for Price Analytics

The goal of work is to glean actionable insight from an A/B test data to determine the effects of increasing the price of a software product.

This work tackles the following 3 questions:

  1. What impact does increasing the software price have on the conversion rate?
  2. What impact does increasing the software price have on the total revenue?
  3. What additional insights from the data could be use to retain or increase conversion rate ?

Insights

  • The increase in the price of the software negatively affected the conversion rate. Increasing the software price by $20 over three months results in a decrease in the conversion rate by 22%.

  • The increase in the price of the software positively affected the total revenue. By increasing the software price by $20 over three months, results in an increase in the net revenue per user by 16% relative to control group.

  • Incentive program could help retain conversion rate under the new software price. For the test group, the number of conversion from google ads increased while the number of conversion from facebook ads decreased. Perhaps, an incentive programs might help maintain the conversion rate from facebook ads. Moreover, we could also explore the possibility of increasing google ads campaign to reach potential new customers.