Analytics & Data Science

Welcome & Introductions (11:00- 11:15AM ET)
Tina Jordan, Vice President, Data Excellence & Privacy, Association of National Advertisers
Joan Fitzgerald, Vice President, Data Excellence & Privacy, Association of National Advertisers

I. DATA MANAGEMENT AUTOMATION: OPTIMIZING PROCESS TO ENSURE QUALITY & EFFICIENCY (11:15am - 11:45am ET)

In this session, we’ll explore how Lenovo’s Corporate Marketing Operations, Insights and Analytics team has successfully leveraged automation and data visualization to enhance data quality and boost team efficiency. By implementing custom automation tools, Lenovo has streamlined data processes, reducing manual work and minimizing errors. We’ll dive into the specific strategies Lenovo has used to enable quicker decision-making and achieve a more seamless, effective marketing operation. Attendees will leave with a deeper understanding of how automation and data visualization can optimize workflows, improve collaboration, and drive better business outcomes.

Speaker: Sarah Collins, Senior Marketing Operations Analyst, Lenovo

II. MAXIMIZING REAL TIME ANALYTICS TO PRIORITIZE, YIELD HIGH ROI, AND DELIVER FORECASTING INSIGHTS (11:45am - 12:15pm ET)

With rising cost and declining revenue in healthcare, it is crucial for marketing leaders to focus on high-yield initiatives to counter this issue. In Cleveland Clinic, we have developed a marketing campaign tracking system that is aligned with finance, strategy, institute and enterprise analytics standards. This system has not only provided real-time analytics and insights in high ROI initiatives but also years of historical data to support forecasting, incrementality test and MMM models. This unified and streamlined process has also enabled a more efficient process for securing investments. Looking forward, in this AI era, we are exploring how AI can enhance this system as well as its next phase.

Speaker: Lin Xie, Director, Marketing Data Science, Cleveland Clinic

III. HARNESSING MACHINE LEARNING FOR MARKETING INSIGHTS: FROM CUSTOMER RETENTION TO PREDICTIVE MODELING (12:15pm -12:45pm ET)

As marketing evolves, the integration of statistical techniques and machine learning (ML) offers powerful tools for customer acquisition, retention analysis, sales forecasting, and optimization. While traditional statistical analysis remains invaluable for hypothesis testing in consumer research and survey analytics, machine learning has emerged as a game-changer in AI-driven and predictive marketing applications. In this session, we explore key ML techniques such as feature engineering, classification models, regression modeling, and deep learning, examining how they are leveraged to gain insights into customer behavior, predict future trends, and optimize marketing strategies. Attendees will also learn about advanced methods like ensemble modeling and dimension reduction, which enhance the effectiveness and accuracy of marketing analytics. This session will provide a comprehensive understanding of how machine learning can transform marketing analytics and guide data-driven decision-making, blending the power of both statistical rigor and innovative predictive models.

Speaker: John Friedmann, Manager, Analytics, Deloitte

IV. CLOSING REMARKS (12:45pm - 1:00pm ET)