A/B testing

Attribution & Analytics Accelerator 2022

The boldest and brightest minds joined us November 14 - 17 for Attribution & Analytics Accelerator 2022—the only event focused exclusively on attribution, marketing mix models, in-market testing and the science of marketing performance measurement. Experts led discussions to answer some of the industry’s most pressing questions and shared new innovations that can bring growth to your organization.

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Optimizing Interventions Along the Customer Journey

  • MSI

Random controlled experiments for A/B testing help improve things like a company's marketing or customer service. However, individually optimizing interventions may not always capture interactions across the entire purchase decision journey. To optimize interventions more holistically, use a Bayesian reinforcement learning model. It can integrate multiple historical experiments, which can improve both current impact as well as future learning.

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“CrossMedia ROAS – The Optimal Mix” – RMT

Our research uses A/B testing of diverse (social, native, mobile, video, addressable TV, zone TV, etc.) digital options on top of the national layer of brand TV as it exists.

It is anticipated that some of the A/B tests will include bold options such as social-dominant digital allocation, native-dominant, mobile-dominant, etc.

Questions to be addressed include:

-What is the optimal form of digital/advanced platform advertising/native to use synergistically with traditional TV?

-How does this differ by product vertical (CPG, Auto, Rx, Tune-in, Other)?

-How does this differ by brands in the same vertical?

-Are there so many variables that each brand has to continually test for optimal digital/advanced mix because new creative or other factors could change the optimal digital mix?

Review the Audience Measurement program and register.