One of the beauties of having your user base is that you can learn exactly who are the most engaged people.
If there are characteristics that influence your top subscribers (like the job they do or where they are located), you can find them and see what do they have in common.
Let’s say you write about alternative sources of income, looking to get drivers for your delivery company; it will pay off to know if the most interested members are coming from small towns or large cities.
The following python script will pull all the members for a given list, and print the name, city, rating, and stats of each:
> python3 email_analyzer/mailchimp_topmembers.py
Name: Leo Celis
City: Rosario
Rating: 5
Stats:
{
"avg_click_rate":0.0773,
"avg_open_rate":0.3591
}(Rating is a MailChimp’s pre-calculated score, from 1 to 5, to measure engagement.)
You can save the results in a database, or put it in a pandas data frame, and extract important characteristics about your top members.
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