Cohort metrics

Customer Segmentation in Python

Karolis Urbonas

Head of Data Science, Amazon

Customer retention: cohort_counts table

How many customers originally in each cohort in the cohort_counts table?

customer_counts_retention_1

Customer retention: cohort_counts table

How many customers originally in each cohort?
How many of them were active in following months?

customer_retention_2

Calculate retention rate

Store the first column as cohort_sizes
```
cohort_sizes = cohort_counts.iloc[:,0]
```
Divide all values in the cohort_counts table by cohort_sizes
```
retention = cohort_counts.divide(cohort_sizes, axis=0)
```
Review the retention table
```
retention.round(3) * 100
```

Retention table

retention_table

Other metrics

grouping = online.groupby(['CohortMonth', 'CohortIndex'])

cohort_data = grouping['Quantity'].mean()

cohort_data = cohort_data.reset_index()

average_quantity = cohort_data.pivot(index='CohortMonth', 
                                     columns='CohortIndex', 
                                     values='Quantity')

average_quantity.round(1)

Average quantity for each cohort

average_quantity

Let's practice on other cohort metrics!

Customer Segmentation in Python