The importance of customer analytics is rising: because access to customer data became easier for many businesses, and also customers now have easier access to data and information on similar products and contents provided by other competitors, it is critical to many businesses to be able to understand and predict what their customers are likely to purchase or view. The deeper the understanding your company has about its customers, the better competitive power it will have against its competitors.
TheRenewOfferTypecolumn inthis DataFramecontainsthe typeof therenewalofferpresented to the customers. We are going to look into what types of offers worked best for the engaged customers.
We are going to understand how customers with different attributes respond differently to different marketing messages. We start looking at the engagements rates by each offer type and vehicle class.
We will get to know Agent works better in term of getting responses from the customers, and then sales through Web works the second best. Let’s go ahead in breaking down this result deeper with different customers’ attributes.
As we can see, customers with medium size vehicles respond the best to all sales channels whereas the other customers differs slightly in terms of engagement rates across different sales channels.
logy=True transform the scale to log scale and it is often used for monetary values as they often have high skewness in their values. We have repeated the code for the plot.scatter 4 times because we have created 4 segments.