Announcing the Call for Content for 2020 Attribution & Analytics Accelerator
Now in its fourth year, Attribution & Analytics Accelerator is the only event focused exclusively on attribution, marketing mix models and the science of marketing performance measurement. The boldest and brightest minds take the stage to share their latest innovations and case studies. The audience is comprised of marketers searching for solutions and analytics gurus who can provide them.
This unapologetically rigorous forum will continue to focus on business outcomes, but there will be four changes for 2020:
- It will be virtual. We have reinvented the Accelerator format for a highly engaging and effective online experience.
- It will be run over four consecutive days for 90 minutes each. While tighter, there will be exactly the same amount of content as in previous years.
- It will be broadened. Encompassing a bit more of the analytics space, without losing focus.
- It will be produced with the Advertising Research Foundation.
The 2020 Attribution & Analytics Accelerator will be presented on four consecutive days, November 16-19, at 12:30-2:00 ET.
This gathering of the modelers, marketers, researchers and data scientists will quicken the pace of innovation, fortify the science and galvanize the industry toward best practices and improved solutions. This is the place where B to C and B to B marketers across a wide variety of categories share their experience and new perspectives, advance practical ideas, and innovative techniques and applications.
We have set four topics for the 2020 event, one per day, and are calling for case studies, experimental results, or empirically determined best-practices that can be linked to business success. Each must be addressed diligently, from the end-user perspective – marketers, media, industry bodies – no sales pitches. Only proposals that include participation by end-users will be considered.
Day 1: Accelerating Recovery
How do we leverage models, attribution, experimentation and other analytics to guide brands to a successful recovery following Covid-19 and the recession?
Day 2: Accelerating Data Science
We talk endlessly about data challenges: privacy, identity, the demise of cookies, walled gardens, discordant television data and on and on. These obstacles fundamentally undermine the success of attribution & analytics. What solutions have been tried? Which have failed; which have succeeded? What are the short-term solutions that should be considered? Where should the industry focus to produce long term solutions?
Day 3: Accelerating Analytics-Driven Business Results
How are the leading end-users applying attribution and analytics to Improve marketing decision-making? Who is successfully optimizing creative mix and media selection … beyond digital and television… beyond media to encompass the full marketing mix? Which analytics capabilities and processes have proven to drive business performance?
Day 4: Accelerating Modeling the Full Value of Marketing Investments
Narrow focus on immediate foot/web traffic, even sales, leaves behind everything we know about how advertising and the rest of the marketing mix actually work together to influence consumer attitudes and behaviors, short-term and long-term. Key concepts that cannot be left by the wayside include synergies, halos, carryover, learning, reinforcing, emotional response, long term impact, getting brand on a consideration set, loyalty, price, distribution and every other marketing KPI essential to business success. Do we have the analytics toolkit to produce the complete view of marketing effects? How do they work together and do we know how to orchestrate their use holistically? Where are we seeing success with: more granular MMM, more aggregated MTAs, unified modeling, AI/Machine Learning/Neural Nets, Lift Studies or RCT?
Send your submission to:
Alice K. Sylvester (firstname.lastname@example.org)
Jim Spaeth (email@example.com)
- The topic your paper addresses:
- Brief Description:
- Presenters, including a brand or other end-user (name, company, title):