Codeflix, a streaming video startup, is interested in measuring their user churn rate. In this project, you’ll be helping them answer these questions about their churn:
- How many months has the company been operating? Which months do you have enough information to calculate a churn rate? What segments of users exist?
- What is the overall churn trend since the company started?
- Compare the churn rates between user segments. Which segment of users should the company focus on expanding?
The dataset contains one SQL table, subscriptions. Within the table, there are 4 columns:
id- the subscription idsubscription_start- the start date of the subscriptionsubscription_end- the end date of the subscriptionsegment- this identifies which segment the subscription owner belongs to
Codeflix requires a minimum subscription length of 31 days, so a user can never start and end their subscription in the same month.
The first 20 rows in subscriptions look like this:
| id | subscription_start | subscription_end | segment |
|---|---|---|---|
| 1 | 2016-12-01 | 2017-02-01 | 87 |
| 2 | 2016-12-01 | 2017-01-24 | 87 |
| 3 | 2016-12-01 | 2017-03-07 | 87 |
| 4 | 2016-12-01 | 2017-02-12 | 87 |
| 5 | 2016-12-01 | 2017-03-09 | 87 |
| 6 | 2016-12-01 | 2017-01-19 | 87 |
| 7 | 2016-12-01 | 2017-02-03 | 87 |
| 8 | 2016-12-01 | 2017-03-02 | 87 |
| 9 | 2016-12-01 | 2017-02-17 | 87 |
| 10 | 2016-12-01 | 2017-01-01 | 87 |
| 11 | 2016-12-01 | 2017-01-17 | 87 |
| 12 | 2016-12-01 | 2017-02-07 | 87 |
| 13 | 2016-12-01 | 30 | |
| 14 | 2016-12-01 | 2017-03-07 | 30 |
| 15 | 2016-12-01 | 2017-02-22 | 30 |
| 16 | 2016-12-01 | 30 | |
| 17 | 2016-12-01 | 30 | |
| 18 | 2016-12-02 | 2017-01-29 | 87 |
| 19 | 2016-12-02 | 2017-01-13 | 87 |
| 20 | 2016-12-02 | 2017-01-15 | 87 |