Opening Remarks
Scott McDonald, Ph.D. – President & CEO, ARF

Understanding Purchase Journeys Using AI
Consumers leave digital footprints through their frequent interactions with companies. The digital footprint data contain important information about their purchase preference and intent. In this presentation, we discuss how advanced machine learning and AI methods can be used to extract insights from such data and to refine our understanding of customer purchase journeys.
Liye Ma – Associate Professor of Marketing, Robert H. Smith School of Business, University of Maryland

Estimating the Long-Term Impact of Major Events: Evidence from COVID-19
Learn about a flexible new way to understand the long-term effects on your business of major events that suddenly impact a firm’s entire customer base all at once. Dan McCarthy shows an application of this method to an analysis of how the COVID-19 pandemic affected customer purchase behavior across 12 diverse sectors in the short run and the long run. By looking at the behaviors of individuals who first became customers at various times, he measures how the COVID-19 pandemic influenced customer behavior. In most categories, behavior has largely returned to “normal,” but there are some categories that have fallen persistently below this.
Dan McCarthy – Incoming Associate Professor of Marketing, Robert H. Smith School of Business, University of Maryland

How Purchase Data Can Help your Brand Reach more Active Buyers
When it comes to CPG Brands, not having much 1st party data traditionally meant an inability to strategically coordinate messaging to the individuals who matter most at the times that make a difference. But what if that didn’t have to be the case? Learn how brands can make up for these shortcomings by leveraging the power of verifiable transactional datasets in conjunction with a sophisticated media delivery engine to find customers at the right time and in the right channels. 
Jennifer Gold – SVP, Media Solutions, Circana
Dan Perez – VP of CPG Media Solutions, Epsilon

Forecasting Brand and Performance Wellness with R-Index
Razorfish’s recently announced R-Index is a proprietary data solution that brings all brand activities into a unified experience, allowing marketers to quickly gauge marketing’s effect on business outcomes. The approach aims to transform marketing analytics by providing a unified, actionable view of brand activities. Consumer response is an always-on signal, not an isolated outcome and that requires monitoring sentiment, brand health and weigh different ways to impact marketing activities consumers and segments. Rather than attempt to understand how consumers are responding to marketing, this solution is designed to understand how marketing can best respond to consumer signals so that marketers can pro-actively adjust their marketing approaches across paid, owned and earned activities.
Abhi Gupta – Senior Agency Analytical Lead, Google
Adam Weiler – SVP of Data and Analytics, Razorfish 

Squaring Success (Minimal Error) in Forecasting in an Era of Quick Turn Requests
Kinesso explains how their forecasting approach offers flexibility and versatility while still grounded in sound econometrics/MMM. Their client portfolio has provided ample opportunities to creatively work through forecasting techniques across a wide variety of clients and industries.  Forecasting for business purposes can range from simplistic to detailed to innovative.  While we know forecasts are only as good as the modeling inputs and its assumptions, the ability to feel good about input forecasts will depend on the broader situation and that situation may have changed especially around the recent pandemic.
Jon Hood, VP Predictive Analytics, Kinesso
Tim Reynolds, VP Predictive Analytics, Kinesso

Closing Remarks
Scott McDonald, Ph.D. – President & CEO, ARF