Predicting with Customer Analytics
In This Appendix
Predictive analytics comprises several methods to analyze what happened in the past to predict what will most likely happen in the future. You use your historical and transactional customer data to identify risks and opportunities.
You’ve almost surely encountered the results of predictive analytics as a customer yourself. Some examples you likely encounter include
- Amazon’s recommendation: Probably one of the most famous examples of predictive analytics that touch the customer is Amazon’s recommendation engine. This includes the “customers who purchased this book, also purchased this book.”
- Facebook and LinkedIn: Social media websites like Facebook and LinkedIn use algorithms to determine both whom you might want to connect to and which stories and updates you want in your timeline based on patterns in your viewing behavior and people with similar behavior to you.
- Netflix: Netflix recommends which movie or TV show you’ll like based on your past views and matching that to customers with similar behavior.
- Return rates: I worked with a mobile carrier to predict which phones customers would return most often based on the opinion of customers evaluating the phone’s usability. ...