Addressable advertising on television enables better targeting and measurement of TV ad campaigns, but gaining access to consumer data is essential for its effectiveness and development. So, what can advertisers do to make people more willing to share their data? New research offers insights into developing personalization initiatives aimed at alleviating privacy concerns.
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Data clean room technology has had a place in the advertising ecosystem for years but has become increasingly prominent in today’s landscape where major disruptions in data governance and privacy are emerging. Data cleanroom companies provide environments for two or more companies to share first-party data in a neutral, secure, privacy-compliant manner. They are used for activation, media measurement, and insights. At this event, Working Group Chair Sable Mi (VP of Analytics, Epsilon) moderated a powerful discussion with guests Alya Adelman (Director of Product, Blockgraph), Devon DeBlasio (VP of Product Marketing, InfoSum), Matt Karasick (Chief Product Officer, Habu), and Alysia Melisaratos (Head of Solutions Engineering, LiveRamp) to unpack the value that data clean rooms can provide.
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The ARF’s Paul Donato guided the panelists through a number of topics related to reconciling privacy with targeting.
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Kevin Whitcher (DISQO) provided an overview of current identifier availability and their use in measuring ad outcomes.
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In the evolving privacy landscape, companies are continuing to look for solutions that offer cookieless targeting. Advertisers seek cross-platform targeting options enabling scale and KPIs to drive campaign performance. However, potential solutions have weaknesses:
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Insights across all touchpoints during the customer journey reveal an optimal allocation of the marketing budget and enables personalized messaging to specific targets. Marketers must be able to analyze the customer engagements during this journey for attribution and to maximize ROI. However, there are challenges for marketing due to GDPR, as well as U.S. privacy regulations and the cookie deprecation actions of Google and Apple. Additionally, 76% of consumers are concerned about how their data is being used. These challenges have resulted in the loss of scale and addressability, as well as targeting and measurement limitations.
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A multi-billion dollar pet food manufacturer analyzed its audience targeting strategy with the goal of ensuring efficient online ad spending, according to Souptik Datta and Zulema Doiny-Cabre of GroupM. The analysis with GroupM evaluated the performance of existing audience segments, pinpointed profiles of high-performing audience segments for additional opportunities and determined the optimal ad impression frequency.
Member Only AccessDatagraphs capture how people work, play, learn, socialize, transact, travel and any other activity that can be associated with commerce. Leading technology companies are using datagraphs to personalize customer recommendations, update products, optimize advertising and more. The most successful examples include Amazon’s purchase graph, Google’s search graph, Facebook’s social graph, Netflix’s movie graph, Spotify’s music graph, Airbnb’s travel graph, Uber’s mobility graph, and LinkedIn’s professional graph. Each of these leverage the ongoing collection of customer engagement data, coupled with proprietary algorithms, to outcompete rivals in every way, from product creation to user experience. We’ve all seen the signs in front of McDonald’s announcing “Over 99 Billion Served” and have watched the number rise over the years. But tracking how many burgers are sold every day, month or year is a relic of the past. Today what is asked is: Do we know where each consumer buys their burgers? At what time? What do they drink with it? What do they do before or after buying a burger? How can we satisfy more of their needs so that they keep coming back? Datagraphs capture this information, helping to reshape competition in every sector. Leaders must invest in upgrading their data architecture to enable a real-time, comprehensive view of how consumers interact with their products and services, so that they can develop unique ways to solve customer problems. Thanks to its rich data and industry-leading personalization, Amazon now owns 40% of the U.S. e-commerce market. Its closest rival, Walmart, has a market share of only 7%. Source: Govindarajan, V. and Venkatraman, N. Venkat. (May-June 2022). The Next Great Digital Advantage. Analytics and Data Science, Harvard Business Review.
Member Only AccessMany consumers don't want advertisers to collect their personal information and shopping data. Are there also privacy concerns when streaming services collect and analyze viewing data to make recommendations? The ARF has done extensive research on privacy (the latest report was issued earlier this year). One issue was not addressed in it and similar studies: How do viewers who use streaming services feel about the fact that those services collect and analyze their viewing data? Recently, the ARF conducted a little experiment in a survey — asking a question about this issue in two different ways. One version asks about levels of “concern”. In the other version, the question focused on the benefits of streaming services collecting this data: better recommendations.
Sources: The ARF. (2022, January 20). The ARF’s 4th Annual Privacy Study. The ARF.
More detail on the new HUB data (ARF proprietary questions) will be released after the AUDIENCExSCIENCE conference next week.
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Changes in privacy legislation, the deprecation of the third-party cookie, and new rules on Google and Apple platforms have set the stage for the impending data disruption in the advertising industry, as outlined in IAB’s State of Data 2022 report and OptiMine’s overview on Google Topics. Both presentations and the subsequent panel discussion in this Insights Studio session emphasized the unavoidable impact the loss of individual tracking will have on measurement and attribution and urged marketers to act quickly to prepare for the effects on revenues.
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