Note: Original article is available here.
Multilevel modelling is particularly useful in the context of market research, whereby segmenting customers by category (e.g. demographics, purchasing habits) is important in understanding how a business can both attract new customers and improve customer loyalty among existing ones.
The lme4 library in R is used to create multilevel models. One significant example of a multilevel modelling exercise within this library is that of the sleepstudy example, whereby a multilevel model was used to analyse how reaction times across sleep deprived individuals differed between participants given the number of days of sleep deprivation.
How would we apply such a model to analysing customer data? Let’s take a look!
An e-commerce site wishes to analyse some recent sales data that they have collected regarding activity on their site. Specifically, they wish to determine factors that influence spend per customer.
They provide a dataset containing the following information: