My test task for SocialTech on Product Analyst postion in Nov 2022, translated to English by me. No raw data of the task, just my answers.
UPD 2023-05-19: Added solution for task 3.2 (mySQL query).
UPD 2023-05-21: Added comment to conclusion of task 1.
Given: A product, where a user can buy game currency with real money. The design team suggests to replace the current UI of the payment screen on mobile apps to increase the number of payments. Starting July 24th 00:00am, the new UI version has been published for split user group, and the rest of users remain with the old UI version. Based on the payments data, answer the following question:
Should the new UI version be published for all users, or it be rejected?
Using cohort ananlysis and provided data, answer the following questions:
- How many emails on average were sent to a single user:
-
within 3 months since the date of app instalation
-
within 6 months since the date of app instalation
-
within 1 year since the date of app instalation?
-
What is the average lifetime of a user?
-
Assuming the cost of 1 email delievery is $0.1, how much does the user retention for one year cost?
-
What is the average CTR for a year for users, that signed up between:
-
weeks 17 and 20
-
weeks 21 and 24
-
weeks 25 and 28?
Syntax -- mySQL.
Given: DB contains the following tables
users
— table with unique site users:
id
— unique user identifieremail
— string field containing user's emailid_country
— unique identifier of user's country (refers tocountries
.id
)date_reg
— user's registration date and time (i.e., «2017-02-27 10:58:05»)
emails_sent
— table with sent email in a campaign:
id
— email idid_user
— target user id (refers tousers
.id
)id_type
— email typedate_sent
— date and time the email was sent
emails_clicks
— table with email clicks:
id
— email click idid_email
— id of the clicked email (refers toemails_sent
.id
)date_click
— click date and time
countries
— list of countries:
id
— country unique idname
— human-friendly country namegroup
— country group
-
Calculate the number of registrations for new users by day and country group
-
Calculate the percent of emails, that were clicked during the first 10 mins after the email was sent, within the last 7 days;
Given: the table users_sessions
that contains data about users' online sessions on the product. Fiels:
id
- unique session identifierid_user
- unique user identifieraction
- field that specify the session openning or closing (‘open’ and ‘close’)date_action
- timestamp of oppening/closing depending on theaction
field
Calculate the total time (unrounded) of all user sessions for each user, for every day for the last 10 days (including the current day).