Predictive Analytics Intro

Description

Marketing data becomes useful when it helps predict what customers will do next. Fourteen PDF lessons start with the fundamentals of predictive analytics, data sources and collection methods for marketing, and customer segmentation.

They then show how to build a first predictive model and measure campaign effectiveness, followed by customer lifetime value, lead scoring and churn prediction. Further lessons cover A/B testing, marketing mix modeling and return on investment, and data ethics and privacy. The final lessons explain how to implement analytics in an organization and turn results into insights and a strategy. Exercises appear in several lessons.

Who it is for: marketing professionals who want to use data to anticipate customer behavior.

What’s included
14 PDF lessons · 79 pages · about 25,000 words
One ZIP download that is yours to keep — read on any device, no subscription or app needed.

Course programme

1. Understanding Predictive Analytics Fundamentals
2. Data Sources and Collection Methods for Marketing
3. Customer Segmentation and Audience Analysis
4. Building Your First Predictive Models
5. Measuring Marketing Campaign Effectiveness
6. Customer Lifetime Value Calculation
7. Lead Scoring and Conversion Prediction
8. Churn Prediction and Retention Strategies
9. A/B Testing and Experimentation Design
10. Marketing Mix Modeling and ROI Analysis
11. Data Ethics and Privacy Considerations
12. Implementing Predictive Analytics in Your Organization
13. Creating Actionable Marketing Insights
14. Developing Your Predictive Analytics Strategy