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Survey Fatigue Impacts Business

An analysis by Bloomberg concludes that declining response rates on surveys conducted by government agencies could have significant implications for financial markets.

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What Does AI Mean for Advertising Research?

  • TOWN HALL

We’ve all heard about the growing use of artificial intelligence in advertising research and doom and gloom predictions that it will knock out jobs, but is this really the case? Agency leaders joined us for an ARF Town Hall to discuss the upsides and possible downsides of generative AI, as well as how they’re utilizing it in their businesses to boost efficiency. Attendees heard predictions on how AI will change the business model of advertising and what it could mean for media agencies.

TV Deconstructed: Latest Findings from DASH

The ARF Universe Study of Device and Account Sharing (DASH) is a nationally projectable enumeration study of consumer behavior in TV and digital media. DASH records in granular detail how US households connect to and consume TV, use digital devices, and interact with and share streaming media and ecommerce accounts. Launched in 2021, this syndicated study is designed to serve as an industry standard truth set for insight and data calibration. The report just released by the ARF highlights findings from the first wave of DASH 2022. Data and findings from the full 2022 data set will be available in January 2023.

Implications of Changing Privacy Frameworks on Measurement & Marketing (Part II)

During Part 2 of our Insights Studio on Privacy experts from Neustar, Sallie Mae and the ARF examined what privacy changes mean for marketers. They discussed the importance of a mutually agreed upon value exchange between the consumer and the brand and the implications of the changing privacy frameworks for the targeting and measurement of advertising. Although there are challenges related to consumer privacy, regulatory issues and measurement, the panelists were optimistic about the potential for resolution.

View Part I here.

Explainable AI (XAI) Helps Minimize the Impact of Errors

  • MSI

The use of AI-based voice assistants is becoming ubiquitous, and this technology continues to develop at a rapid pace. Now, Explainable AI (XAI) can help customers understand things better and help mitigate certain kinds of errors. This research discovered that XAI can help consumers forgive minor social faux pas (violations of social norms) but not minor technical errors (failures of the algorithm interface). The series of studies also found that XAI helps consumers overcome their reluctance to use such AI-assisted technologies.

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