Highlights from this week’s conversation include:

Previewing Today’s Topic (0:14
Machine Learning Discussion (1:44)
Conditions for Machine Learning Worthiness (6:59)
Simplicity in Modeling (8:43)
Predictive Analytics vs. Machine Learning (10:42)
Optimization and Investment Problems (13:03)
Practical vs. Theoretical Saturation (15:16)
Building Relationships with Marketing Teams (19:52)
Reporting Metrics and Attribution Models (22:49)
Tracking Common Metrics (25:40)
Understanding Profit Generation (27:46)
ROI Calculation Challenges (29:49)
AI in Customer Data Analysis (31:23)
Execution Challenges in Marketing Automation (35:23)
API Limitations in Marketing Tools (36:50)
Optimizing Ads with AI (37:50)
Challenges of Real-Time Data Integration (40:01)
Final thoughts and takeaways (41:13)

The Data Stack Show is a weekly podcast powered by RudderStack, the CDP for developers. Each week we’ll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.

RudderStack helps businesses make the most out of their customer data while ensuring data privacy and security. To learn more about RudderStack visit rudderstack.com.

228: The Machine Learning Reality Check: When AI Makes Sense for Marketing Attribution with Lew Dawson of Momentum Consulting

The Data Stack Show

228: The Machine Learning Reality Check: When AI Makes Sense for Marketing Attribution with Lew Dawson of Momentum Consulting