Cassandra library
Project description
Cassandra
Cassandra's library for Marketing Mix Modeling
To best perform an mmm, you will need to perform these processes in order:
- Data Processing
- Data Analysis
- Trasformations
- Models
- Model Evaluation
Build your MMM
Create your settings variables (settings_csv, settings_variables, settings_models) as shown below:
- settings_csv
settings_csv = {
'pathcsv': 'path/to/dataset.csv',
'delimiter': ',',
'subset_columns': ['ordine_data','revenue','transazioni','google_search_spent','google_performance_max_spent','google_display_spent','fb_retargeting_spent','fb_prospecting_spent','bing_spent','bing_organico','google_organico','referral','email_sessioni','cambio_eur_dollaro','ios_14','Offerte'],
'rename': {'ordine_data':'data'},
'data': 'data',
'target': 'revenue'
}
- settings_variables
settings_variables = {
'medias': ['google_search_spent','google_performance_max_spent','google_display_spent','fb_retargeting_spent','fb_prospecting_spent','bing_spent'],
'organic': ['bing_organico', 'google_organico', 'referral', 'email_sessioni', 'cambio_eur_dollaro', 'ios_14',
'Offerte', 'lun', 'mar', 'mer', 'gio', 'ven', 'sab', 'dom', 'month', 'year'],
'seasonal_categorical': ['month', 'year', 'lun', 'mar', 'mer', 'gio', 'ven', 'sab', 'dom'],
'general_categorical': ['ios_14', 'Offerte'],
'general_numeric': ['bing_organico', 'google_organico', 'referral', 'email_sessioni', 'cambio_eur_dollaro']
}
- settings_models
settings_models = {
"model": 'nevergrad',
"linear_metric": ['accuracy', 'nrmse', 'mape'],
"linear_coeffs": True,
"ols_constant": True,
"log_linear_metric": ['accuracy', 'nrmse', 'mape'],
"log_linear_coeffs": True,
"ridge_metric": ['accuracy', 'nrmse', 'mape'],
"deep_learning_metric": ['accuracy', 'nrmse', 'mape'],
"nevergrad_metric": ['accuracy', 'nrmse', 'mape'],
'nevergrad_variables': {
'google_search_spent': {
'lower':0,
'upper':3
},
'google_performance_max_spent': {
'lower':0,
'upper':6
},
'google_display_spent': {
'lower':0,
}
},
'nevergrad_budget': 2500
}
Run your MMM
main.build(settings_csv, settings_variables, settings_models)
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