As DTC brands struggle to find new customers amid the economic crisis, expanding the possibilities of variables can be beneficial.
The importance of harnessing variables become increasingly crucial for direct-to-customer brands as they move from simple audience segmentation to more precise predictive models. Effectively using variables can help marketers target genuinely interested audiences without annoying them.
While building predictive models, they should consider – consumer behaviour variables – which range from interest and affinity propensities to transactions. These insights, along with KPIs like conversion, clicks and views should be used to optimise algorithms of the model.
Marketers should begin with their first-party data and eventually use second-party and third-party data to build these models. These custom-built models can help brands evaluate thousands of variables and assign a predictive value. They can then use analytics to monitor and modify marketing campaigns to improve performance.
[5 minute read]