The media landscape continues to evolve, arguably at a faster rate than ever. Leading media and measurement experts presented research-based insights on how viewers use different forms of TV/video on various platforms. Attendees joined us at the Warner Bros. Discovery Studios in California and via livestream to understand the latest data and discussions of the data’s implications.
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The practice of marketing mixed modeling (MMM) is increasing, research finds, partially because of the implementation of privacy restrictions. Today, finding appropriate providers to optimize marketing investments remains challenging. This was the impetus behind the Marketing Science Institute (MSI)’s Blue Ribbon Report on MMM. This free preview of the full white paper outlines what best practices to employ in a rapidly changing landscape. It identifies challenges for MMM veterans and ways to meet them. It also introduces executives to the opportunities that exist when introducing MMM into their firm. The report preview provides a brief overview of the top-level findings found in the full report, which is only available to MSI members.
Member Only AccessIn this session, Yannis Pavlidis of consumer insights and CX firm DISQO tackled the challenges of benchmarking, cross-media outcomes and brand lift due to incomplete data from siloed platforms and media channels. In the opening, Yannis provided a refresher on the importance of benchmarks and obstacles from existing approaches to benchmarking (e.g., inconsistent methodologies, outdated data and collection techniques). The discussion examined solutions to address issues in data collection concerning benchmarking ad impact, which streamlines the process using consented, single-source data. The presentation also examined calculating benchmarks based on data taken from one source group (rather than two unaffiliated groups), considered the recency of the campaign used and subsequent behavior(s) which then can be correlated with survey responses. The advantage of using consented single-source data is that it can lead to more insightful, relevant and consistent outcomes in benchmarks.
In this session, speakers Bennett M. Kaufman, Kyle Holtzman and Michelle Smiley of Google explored a two-pronged approach to cross-media measurement and planning that considered the full-funnel impact across traditional TV and streaming video (YouTube), to make sense of all the “disparate forms of data and measurement.” The approach considered a geo-based experiment and audience incrementality to demonstrate and solve the following challenges: to retain current loyal customers, to age down the brand and to appeal to new consumers (Generation Z). The speakers presented a study done by Google in partnership with Burger King to test a new experimentation strategy to understand and measure the relationship between Linear TV and YouTube. The speakers touted the benefits of this method as repeatable and customizable across a variety of media channels, in addition to being timely, omni-channel and privacy safe.
Kyle Holtzman – Business Lead Restaurant Vertical, Google
Bennett M. Kaufman – Cross-Media Measurement Lead, Google/YouTube
Michelle Smiley – Analytical Lead Restaurant Vertical, Google
Key Takeaways
Yannis Pavlidis – VP, Data Science and Analytics, DISQO
In this session, Yannis Pavlidis of consumer insights and CX firm DISQO tackled the challenges of benchmarking, cross-media outcomes and brand lift due to incomplete data from siloed platforms and media channels. In the opening, Yannis provided a refresher on the importance of benchmarks and obstacles from existing approaches to benchmarking (e.g., inconsistent methodologies, outdated data and collection techniques). The discussion examined solutions to address issues in data collection concerning benchmarking ad impact, which streamlines the process using consented, single-source data. The presentation also examined calculating benchmarks based on data taken from one source group (rather than two unaffiliated groups), considered the recency of the campaign used and subsequent behavior(s) which then can be correlated with survey responses. The advantage of using consented single-source data is that it can lead to more insightful, relevant and consistent outcomes in benchmarks.
Key Takeaways
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.
GPS and other new, digital technologies have given companies capabilities like never before. They also bring up new questions. For instance, if a company using GPS can see a small service failure is about to occur, should it proactively apologize in real-time or let it go? Proactive apologizing can backfire, which may cause the customer to perceive this service experience as lackluster, leading to decreased satisfaction, trust, recommendations and patronage. What can be done to help managers decide if and when to apologize, and when appropriate, how to do so in the right manner? This study offers some insights.
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Ever wonder what the impact of one negative review is on a product? Researchers in this MSI award-winning working paper were able to quantify this recently, from a retailer’s “newest first” review display policy. In technology and home and garden products, a single critical opinion had a detrimental impact that was two-fold, the study found. It increased the probability of continuing to search and to competitors while decreasing the purchase probability.
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