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# System prepended metadata

title: 'Churn: From prediction to prescription'

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# Churn: From prediction to prescription

## Utils
+ Instruccions sobre com editar aquest tipus de fitxers: https://hackmd.io/features?both
+ Blog interessant: https://motifanalytics.medium.com/bringing-more-causality-to-analytics-d378108bb15


## 0. Problem definition
### Churn (or Conversion)
### Type of causal problem
## 1. Problem understanding and Explainability
### Model the problem (as a prediction?)
### With the help of the model (explainability) find all factors afecting the outcome
#### Expert knowledge role
### Why prediction is not enough

## 2. Causal Inference
### Prescriptive analytics
### Define the causal graph
#### Expert knowledge role
### Identify the causal query
### Estimate
#### Experiments vs observational data
### Validate?

## 3. Optimal policy
### Exploration vs Exploitation
