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.