دانلود فیلم آموزش آنالیز مشتریان قابل پیش بینی

Use big data to tell your customer’s story, with predictive analytics. In this course, you can learn about the customer life cycle and how predictive analytics can help improve every step of the customer journey.

Start off by learning about the various phases in a customer’s life cycle. Explore the data generated inside and outside your business, and ways the data can be collected and aggregated within your organization. Then review three use cases for predictive analytics in each phase of the customer’s life cycle, including acquisition, upsell, service, and retention. For each phase, you also build one predictive analytics solution in Python. In the final videos, author Kumaran Ponnambalam introduces best practices for creating a customer analytics process from the ground up.
Topics include:
Understanding the customer life cycle
Acquiring customer data
Applying big data concepts to your customer relationships
Finding high propensity prospects
Upselling by identifying related products and interests
Generating customer loyalty by discovering response patterns
Predicting customer lifetime value (CLV)
Identifying dissatisfied customers
Uncovering attrition patterns
Applying predictive analytics in multiple use cases
Designing data processing pipelines
Implementing continuous improvement
Courses :
Introduction
Customer Analytics Overview
Will You Become My Customer
What Else Are You Interested In
How Much Is Your Future Business Worth
Are You Happy With Me
Will You Leave Me
Best Practices
Conclusion