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The main idea of this project, is to predict the ARPU (Average Revenue Per User) 11 month after subscription of a cohort with a monthly subscription, using minimum number of delays (a delay is a month of data of a cohort, i.e.: delay 0 --> first month of data for cohort A, delay 1 --> second month after subscription ...), now the idea is to predict the ARPU using maximum 3 months of data, in a way everytime a cohort has another month of data we predict the ARPU of 12th month :

  • cohort A subscribed in 01/2021 --> Predict ARPU of 12/2021 using data of 01/2021
  • in 02/2021 --> Predict ARPU of 12/2021 using data of 01/2021 and 02/2021
  • in 03/2021 --> Predict ARPU of 12/2021 using data of 01/2021 and 02/2021 and 03/2021

(more data = better accuracy, but for business requirements we cant wait more than 3 month of data for a cohort to get good predictions) I'm wondering how to make this possible, considering that data is stored in Snowflake.

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    $\begingroup$ ARPU = Average revenue per user $\endgroup$
    – noe
    Commented Jun 13, 2023 at 10:11
  • $\begingroup$ yes exactly ARPU is average revenue per user $\endgroup$
    – wassimdiai
    Commented Jun 13, 2023 at 10:19
  • $\begingroup$ For the connection to Snowflake connection you can check: docs.snowflake.com/en/developer-guide/python-connector/… $\endgroup$
    – Memristor
    Commented Jun 15, 2023 at 21:08

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