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Predictive Customer Analytics

Introduction

Welcome
Expectations and course organization
Use the exercise files

1. Customer Analytics Overview

The importance of customer analytics
The customer life cycle
Apply analytics to the customer life cycle
Sources of customer data
The customer analytics process
Use case: Online computer store

2. Will You Become My Customer?

The customer acquisition process
Find high propensity prospects
Recommend the best channels for contact
Offer chat based on visitor propensity
Use case: Determine customer propensity

3. What Else Are You Interested In?

Upselling and cross-selling
Find items bought together
Create customer group preferences
User-item affinity and recommendations
Use case: Recommend items

4. How Much Is Your Future Business Worth?

Generate customer loyalty
Create customer value classes
Discover response patterns
Predict customer lifetime value (CLV)
Use case: Predict CLV

5. Are You Happy With Me?

Improve customer satisfaction
Predict intent of contact
Find unsatisfied customers
Group problem types
Use case: Group problem types

6. Will You Leave Me?

Prevent customer attrition
Predict customers who might leave
Find incentives
Discover customer attrition patterns
Use case: Customer patterns

7. Best Practices

Devise customer analytics processes
Choose the right data
Design data processing pipelines
Implement continuous improvement

Conclusion

Next steps