Use causal inference to evaluate the effect of pricing strategies on customer loyalty.

To begin with, the primary variable of interest here is customer loyalty, which can be operationalized in several ways. For the sake of clarity and specificity, let's measure customer loyalty as the frequency of repeat purchases within a fixed period, say, a year. This metric is direct and quantifiable, allowing us to track changes over time with precision.

The treatment in this scenario is the pricing strategy. Pricing strategies can vary widely—from discount pricing, tiered pricing, to dynamic pricing models. For our causal inference model, we can categorize these strategies into discrete groups (e.g., high, medium, low) or treat them as a continuous variable if we're considering price adjustments in terms of percentage change from a base price....