Propensity modelling uses a wide range of datasets to predict user behaviours, including:
Demographics: Age, gender, location and any other accessible data that helps paint a picture of who users are.
Behavioural data: Such as product pages viewed, content engaged with, conversions completed, etc.
Purchase history: Historical patterns that can be used to make recommendations and predict future purchases.
Brand engagement: Such as website visits, app usage, email engagement and purchase frequency. These can be used to predict engagement and potential churn.
Third-party data: By comparing the data with similar audiences, we can predict actions with greater accuracy. This will help you make better marketing decisions.
With a deeper understanding of what your customers are doing, you can better optimise campaigns. And respond to their changing needs with greater speed and accuracy.