Data drift, feature drift, covariate drift and input drift all refer to a shift in the statistical properties of the independent variable(s), i.e. a drift in the feature distributions and the correlations between variables. This drift can result in data changes due to seasonality, consumer preferences, the addition of new products or other factors.
Example:
With a churn model, data drift might occur if users decide to cut back on their cable subscriptions due to a new popular show on a channel that the company’s service does not carry.
