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Platform Analysis

Input

CSV file with the columns:

  • date: date of data colection.
  • money_size_users: total users on the money size of the platform (at the end of the day).
  • subsidy_size_users: total users on the subsify size of the platform (at the end of the day).
  • money_size_new_users_by_campaign: new users adquired on money size by performing comercial / marketing actions.
  • money_size_new_users_by_network: new users adquired on money size by network behaviour.
  • subsidy_size_new_users_by_campaign: new users adquired on sudsidy size by performing comercial / marketing actions.
  • subsidy_size_new_users_by_network: new users adquired on sudsidy size by network behaviour.
  • investement_in_money_size_campaigns: total money invested in the growth of money size.
  • investement_in_sudsidy_size_campaigns: total money invested in the growth of sudsidy size.

A example CSV simulated data could be created with the ´simulate_base_data.py´ file.

Pipeline

  1. Create data file.
  2. Create a campaign_control object based on campaigns investement.
  3. Create a simulator object.
  4. Use the ´simulate´ method, which return two values
  • The number of periods simulated.
  • If the critical mass was reached in the simulated periods.

Objects:

  • Simulator.
  • model_trainer.
  • campaign_control.