Overcoming Data Limitations and Enhancing Model Performance

Wednesday, July 17, 2024 | 12:00 - 2:00pm | LIVESTREAM

Overview

Predicting Tomorrow: Uses of Forecasting

Forecasting remains an important tool in the media, marketing and advertising analytics toolbox. We use forecasting models to predict consumer behavior, market shifts, competitive activity and shifts in demand. Our forecasting and scenario planning tools help our companies reduce risk and respond quickly to changing market dynamics.  And of course, we use forecasting models to predict uptake of new products and services – including media products and shows.

Yet forecasters face major challenges. Data sparsity is a growing problem due to privacy protections, distribution disruptions and signal deprecation. A large part of forecasting in marketing is trying to predict what things we will like (e.g., personalization, recommendations); but doing this right is hard enough when the data are solid. When the data signals are weaker, forecasts are weaker. Some companies have been doing work on this — aggregating individual-level data to become “cohorts” with similar tastes. The success of these approaches remains to be seen. But a big question hanging over all of it is whether consumers will still be offended and feel violated when the forecast is correctly made from privacy compliant sources. Can AI and “synthetic” modeled data offer an opportunity to overcome data limitations and enhance model performance? 

At FORECASTING 2024 on July 17, a variety of companies will share how they are building forecasting models despite data sparsity and other challenges to effective modeling. Learn from the leaders in this fascinating and important space. Note that this event will be virtual.

Forecasting is a valuable tool to help businesses reduce risk and operate more effectively and efficiently. At FORECASTING 2024, leading practitioners and academics shared how they are building forecasting models to understand purchase journeys, the impact of major events on businesses and how brands can reach buyers amidst the lack of first-party data. 

Jennifer Gold
SVP Media Solutions,
Circana

Jon Hood
VP Predictive Analytics, Kinesso

Liye Ma
Associate Professor of Marketing, Robert H. Smith School of Business, University of Maryland

Dan McCarthy
Incoming Associate Professor of Marketing, Robert H. Smith School of Business, University of Maryland

Dan Perez
VP of CPG Media Solutions,
Epsilon

Tim Reynolds
VP Predictive Analytics, Kinesso

Abhi Gupta
Senior Agency Analytical Lead, Google

Adam Weiler
SVP of Data and Analytics, Razorfish

Scott McDonald, Ph.D.
President & CEO,
ARF
MODERATOR

Michael Ellgass

EVP Global Media, CPG and Retail, Circana

Monica Longoria

Head of Marketing Insights, LG Ad Solutions

Raymond R. Burke

E.W. Kelley Professor of Business Administration Indiana University, Kelley School of Business

Erin Mitten

Analytics Manager, Arc Worldwide

E. J. Schultz

News Editor, Ad Age

Stephanie Pegler

eCommerce/omnichannel Marketing Director, PepsiCo

Jaclyn Williams

Research & Insights Manager, North America & Global Functions, TikTok

Brett R. Gordon

Professor of Marketing, Kellogg School of Management, Northwestern University

Jaime Martin

Managing Director, Commerce at GroupM's Mindshare

Bharath Gaddam

Founder and CEO,
Data POEM

Caroline Liu

Head of Insights & Analytics, Walgreens Advertising Group

Brendan Light

Global Head of Virtual Experiences, Ipsos

Keith Smith

Research Director, MSI

Earl Taylor

Chief Knowledge Officer, MSI

Paul Donato

Chief Research Officer, ARF

AGENDA

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

 

9:00-10:00amRegistration and Breakfast
 

MORNING

 

Opening Remarks 

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

 Overview of Attention Phase II Findings and Attention Survey Results
& Preview of Phase III
 Discussion & Feedback from Attention Phase II
 

Universal Guide to Attention, Emotion, Persuasion and Memory in Advertising

 

AFTERNOON

 

FOX/BHC/Wharton Neuro Study

 

Standards for Media Measurement Products

 

Presentations by Adelaide, eye square, Mediaprobe, Meta, Snap, Viomba

 

Closing Remarks

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

4:35-6:00pmCocktail Reception

 

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