1. Aprende
    2. /
  2. Proyectos
    3. /
  3. Analyzing Marketing Campaigns with pandas
  • 1

    Pandas

    Gratuito

    In this chapter, you will review pandas basics including importing datasets, exploratory analysis, and basic plotting.

  • 2

    Exploratory Analysis & Summary Statistics

    In this chapter, you will learn about common marketing metrics and how to calculate them using pandas. You will also visualize your results and practice user segmentation.

  • 3

    Conversion Attribution

    In this chapter, you will build functions to automate common marketing analysis and determine why certain marketing channels saw lower than usual conversion rates during late January.

  • 4

    Personalization A/B Test

    In this chapter, you will analyze an A/B test and learn about the importance of segmentation when interpreting the results of a test.

Initializing

Ejercicio

Calculating retention rate

In this exercise, you will calculate the retention rate, or the number of remaining subscribers from the users who converted to your product. This can give you a sense of whether your marketing campaign converted subscribers who were actually interested in the product.

Conversion rate and retention rate function hand-in-hand; you could create a business with a high conversion rate by giving users a free trial, but have a low retention rate once users are charged for your services. This isn't inherently a bad thing, but it is important to provide your business stakeholders with insight into what percentage of users remain subscribers.

The formula for retention rate is:

$$ \frac{\text{Number of people who remain subscribed}}{\text{Total number of people who converted}} $$

Instrucciones

100 XP
  • Calculate the number of subscribers using the user_id and converted columns in the marketing DataFrame.
  • Calculate the number of retained subscribers using the boolean columns user_id and is_retained.
  • Calculate the retention rate.