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Topic Descriptions

Call for Content

Help address and discern critical measurement issues by submitting your best research by February 20. It will be vetted through a two-round judging process by the ARF 2017-2018 Board of Curators. If selected, you will be the given the opportunity to present at 2018 AUDIENCExSCIENCE.

Topics

The (Near) Future of Media Measurement
The ongoing tidal wave of change, the relentless digitalization of all media, impacts the pre-digital media formats like radio/audio, newspapers/magazines, out of home and TV/video. It has also ushered in newer media formats like social media, just as it has given marketers many ways of connecting with consumers without bothering with media at all – a trend that will accelerate with the expansion of the Internet of Things. Virtual and augmented reality, artificial intelligence and smart speakers are upon us and will soon become familiar players in our global society. What lies ahead for the measurement of media and advertising in this complex milieu? What does “audience” even mean now? How will this new world impact researchers and data scientists employed by agencies and media companies, as well as those working for advertisers and research suppliers?

The State of Programmatic Accountability
Though described by some as a “murky media supply system” riddled with fraud, abuse and inaccuracy, programmatic display is estimated to hit another plateau in media investment this year (over $30 billion). Programmatic sells itself on efficiency, but can it prove itself to be accountable? The industry is seeking reliable new methods to affirm the accuracy of programmatic buys, including methods for validating identities, targeting segments accurately, filtering invalid traffic, eliminating fraud and reducing the opacity and cost of the ad-tech supply chain. Other key topics in the programmatic ecosystem include understanding the value of deterministic v. probabilistic data, the value of first vs. third party data, methods for managing brand safety and beneficial contextual environments, and the uses of blockchain and distributed ledgers to shine light on the “murky” system.

Cross-Platform Trends and Measures
The evolving, growing complexity of cross-platform requires both a clearer understanding of consumer behavior and tools for enhancing measurement of media usage and/or ad exposure. How effective are current methods for resolving user identity across device and across platform? To what degree do they rely upon participation of market participants and how solid are the numbers in the absence of that cooperation? There is an ongoing question of how to generate cross-platform industry currency, with tens of billions at stake. Or will there be myriad measures and no one currency?

Television/Video Today & Tomorrow
Multiple services are offering video viewing data generated from set top boxes, game consoles, mobile devices and over-the-top sources. The resulting audience estimates don’t yet converge to a consensual truth. There are patrons of probabilistic panels and others who prefer behavioral measures that provide a census of only a part of the relevant audience universe. There are different ways of processing these data and integrating inputs from probabilistic and non-probabilistic sources, including machine learning, fusion, and agent-based techniques to name a few. How do we validate the audiences behind the devices? What qualifies as “viewership?” If audience attention is the real object of interest, how does multi-tasking affect the search for “truth” in measurement?

MMM and MTA
Industry consensus is that “last click attribution” should be a thing of the past. But how far has practice advanced beyond that model? What are the latest approaches to aggregate market mix modeling and digital multi-touch attribution? How granular can marketing and media exposure variables get? For product categories outside of FMCG and direct response, do attribution models hold up? Social data, recommendation, and word of mouth often are factors in new brand decisions, but how do these fit into our current attribution models?

Location Data: What, Where and Why
The growing availability of location data begins to shift marketer focus from “audience” to “customer journey” and provides new ways of touching consumers independent of media. How robust are location-based approaches compared to more traditional media contexts? How can location-based data contribute to a more holistic view of the audience?