Predicting customer conversion with tree-based algorithms
Predictive analytics or modeling can be applied at various stages of the customer life cycle. If you recall from Chapter 2, there are largely five stages that we can break down a customer life cycle into: Awareness, Engagement, Conversion, Retention, and Loyalty, as shown in the following diagram:
Figure 6.1: Customer life cycle diagram from Chapter 2
The applicability of predictive modeling is broad, depending on your marketing goal. For example, if you have a new brand or product launch and would like to improve new product awareness via ads on social media, you can build predictive models that can help you identify the target customers who are likely to click on the ads. On the other hand, if you would like to improve product purchase conversion rates, you can build predictive models that can identify customers who are more likely to make purchases in the next X number of days and target them. This results in...
