Regression analysis is commonly used in predictive analytics to determine how product attributes and customer demographics affect purchase behavior. While predictive models are useful, managers should understand key assumptions and that the relevance of models can change over time as customer preferences and market conditions shift.

1. TRAILING THE NEXT STEP

3. LACK OF DATA IS A
CHALLENGE

4. USE ATTRIBUTES OF
PRODUCTS TO DEVELOP
MODELS

5. AND USING DEMOGRAPHIC
ATTRIBUTES OF THE CUSTOMER

6. KEY INSIGHT #2: Regression
analysis is the primary tool used for
predictive analytics.

7. IT TELLS US THE DEGREE TO
WHICH EACH VARIABLE
AFFECTS THE PURCHASE
BEHAVIOR

9. TIME AFFECTS MODELS

10. THE WHYS- RELEVANCE

11. Managers should always ask
analysts what the key assumptions
are.

14. THE HOWS RELEVANCE