While generative AI is expected to revolutionize many aspects of marketing, so far large language models (LLMs) may not be sufficient to tackle search engine advertising (SEA) all on their own. Using a hybrid AI model that incorporates human judgement instead can help optimize SEA, allowing marketers to do far more with less.
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During the last five years, we have seen an upswing and change in the inclusion of values in advertising, especially the increase in cause-related marketing (CRM) which includes messages about societal goals such as sustainability, ESG (environmental, social and governance) and DEI (diversity, equity/equality and inclusion).
Given marketers’ interest in these issues—ranging from wanting to express support for causes to being concerned about a possible backlash—the ARF has reviewed the research on cause-related marketing as well as related issues, such as ads with more general pro-social and altruistic messages. ARF researchers conclude that ads with cause-related messages can be effective, but many are not. Future research should focus on which kinds of messages are most effective among different consumer groups.
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On July 26, measurement practitioners discussed how to adapt to this new era of privacy with tools for measuring ad performance effectiveness. Panelists explored new considerations for existing methods, such as marketing mix modeling (MMMs) and multi-touch attribution (MTAs), and discussed the pros and cons of various privacy enhancing technologies (PETs), including multi-party computation, clean rooms, and more.
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Will an ad that makes fun of the very consumers it targets offend or appeal to them? So-called “audience-targeted negative advertisements” (ATNAs) are the subject of new research that examines ATNAs through the lens of empathy. It also tests their effectiveness for promoting low- and high-status products.
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