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Kenan Institute 2024 Grand Challenge: Business Resilience
Market-Based Solutions to Vital Economic Issues
Jun 6, 2024

Marketing at a Crossroads, Part II: Personalization vs. Privacy and the Rise of First-Party Data

Part of our series on Business Resilience

With an ever-expanding ocean of consumer data at their disposal, firms must balance methods that unify customer journeys and profiles with building trust that consumer information is safe with them. Continuing the conversation on the current watershed moment for marketing practices, the Kenan Institute sits down with Longxiu Tian, UNC Kenan-Flagler Business School assistant professor of marketing, to discuss how brands can build resiliency and capitalize on emergent opportunities.

Covering issues related to first-party data and the shifting relationships between platforms and publishers, Tian provides insights on the new frontiers of advertising media and AI. Tian’s responses and supporting research were jointly developed with Nikhita Bhoopati, Forte Fellow and UNC Kenan-Flagler MBA Class of ’24.

In our last Q&A discussing the recent “privacy paradigm shift,” you mentioned that the sunsetting of third-party cookies has elevated first-party data’s importance, especially for the crucial task of identity resolution. Would you tell us a bit more about these changes?

Longxiu Tian: The recent “privacy paradigm shift” regarding consumer data reflects a transformation in how societies and regulators approach this issue, and now more than ever before there is a widely expressed cultural and legal emphasis on prioritizing user privacy and data protection. With privacy and data protection’s centrality as the new norm, first-party data – information collected directly from customers – will be the key to solving the puzzle of personalization and accurate targeting from here onward. In recent decades, effective marketing has relied on the promise of precision that comes from increasingly fine-grained third-party data. That data regime is ending, and the emerging standard will instead have to build its information ecosystem using improved predictive capabilities.

Major web browsers have begun to phase out third-party cookies, which had long been used for tracking users across websites. In the absence of user tracking, marketers are increasingly employing contextual advertising, which targets ads based on the content being viewed rather than past behavior. This method respects user privacy in accordance with the current emphasis on data protection. Savvy marketers are also turning to first-party data to tailor experiences without breaching privacy norms. Retailers and even media platforms like Netflix have leveraged their treasure trove of first-party data into a revenue source by using their unique behavioral data to help advertisers identify and market to high-value customers. These sorts of novel approaches have led to a sea change in how firms, especially incumbent players with long histories in the retail space, collect and store first-party data.

Amid the evolving landscape of data collection practices, how do companies find the appropriate balance between delivering personalized experiences and upholding consumer privacy?

Longxiu Tian: The considerations and tradeoffs regarding personalization and privacy have become very complex, nuanced and, in some cases, opaque. Companies must simultaneously navigate technological shifts, changes in consumer expectations and regulatory environment transformations. First-party data is the critical asset in this balance, necessitating a business focus on building robust data management systems that prioritize user consent and transparency. Data “clean rooms,” for example, allow for the secure processing of information, minimizing the risk of breaches and ensuring compliance with privacy laws.

The world of consumer data, however, is expanding beyond first-party data. There is an emerging approach that uses “all-party data,” by which the integration of first- and third-party data creates a richer, layered personalization. This method, when done transparently and with proper consent, respects user privacy while enabling effective marketing.

Firms cannot afford to remain passive observers in the development of new data collection methods but need to become advocates for privacy and transparency. The push for federal privacy regulation in the U.S. is indicative of an industrywide shift toward prioritizing consumer privacy rights. By proactively engaging in these discussions and advocating for clear, consistent privacy regulations, firms can help shape a landscape of regulations and norms that respects user privacy while still allowing for innovative and effective marketing practices.

As companies strive to balance personalized marketing with stringent privacy standards, what innovative methods and practices are proving most effective in aligning these objectives?

Longxiu Tian: As we move toward a cookie-less future, data clean rooms and differential privacy are set to expand their roles. Data clean rooms provide a secure environment where firms can share sensitive data, whereas differential privacy provides algorithmic guarantees that downstream analyses cannot single out any single customer. These methods address a critical aspect of modern marketing: delivering personalized experiences without breaching consumer trust or privacy regulations.

To be clear, these technologies are not merely compliance tools; by safeguarding data against potential breaches and misuse, these processes enhance consumer trust​​. Indeed, data clean rooms and differential privacy are now recognized not only as an alternative but also as a necessary evolution in data handling and a model offering more sophisticated, flexible and scalable solutions for marketers. This adaptability allows for applications in shifting regulatory environments, with various technological solutions, and adhering to marketer’s dynamic needs, creating a holistic approach to personalization and privacy.

Beyond innovative methods, what are some technologies that companies can deploy – or are already using – to maximize both personalization and privacy in their consumer data management?

Longxiu Tian: Google’s Privacy Sandbox initiative is one solution gaining prominence, yet it is far from perfect. This technology uses on-device processing and other privacy-preserving techniques to serve relevant ads without sharing user-level data with third parties. Similarly, the Unified ID 2.0 (UID2) identity initiative enables targeted advertising while giving users more control over their data sharing preferences.

As third-party cookies are phased out, we are seeing cost per thousand, or CPM, values increase for cookie-free inventory as user-level targeting becomes more difficult. Even advertisers working with authenticated audiences like email lists or logged-in users are seeing CPMs increase. In response, advertising budgets will likely shift closer to the originating sources of first-party data. For example, connected TV platforms, retail media networks and publishers with authenticated users can work together to provide personalization while adhering to privacy regulations.

In pursuit of this synergy, Walmart recently acquired Vizio, a move that will revamp its retail media business, Walmart Connect. With over 18 million active accounts and a robust advertising business, Vizio’s strong presence in the smart TV market will provide Walmart with a wealth of viewer data and advertising inventory. Walmart will also be able to leverage Vizio’s technology to enhance its omnichannel advertising offerings, allowing advertisers to engage consumers across different platforms and devices. Walmart’s expansive retail reach combined with Vizio’s technological assets will likely produce marketing innovations that will boost Walmart Connect’s profile in the advertising ecosystem. The Vizio and Walmart union is likely a harbinger of things to come, signaling structural realignment and the realization of synergies in the digital economy.

For marketers standing at the current crossroads, what lies around the bend?

Longxiu Tian: This year marks a pivotal moment, as advertising and consumer engagement undergo wholesale transformations, and the relationship between incumbent players and their roles changes in profound ways.

Take, for example, the dynamic between demand-side platforms, or DSPs, and media agencies. Agency representatives have become increasingly vocal about DSPs encroaching on their space, effectively becoming competitors rather than solely platform providers. Most prominently, fairly or unfairly, agency execs have (off the record) called out The Trade Desk, a company that helps advertisers place ads on internet enabled platforms, for this encroachment. This shift, where collaborators become competitors, stems mainly from DSPs’ expanding capabilities, particularly related to data-driven artificial intelligence and machine learning, which allow these platforms to assume major roles in the advertising and media buying landscape, areas traditionally dominated by media agencies.

DSPs have laudable arguments in their defense, as they have been first movers emphasizing data transparency and performance efficiency. This emphasis appeals to marketing groups that are increasingly tasked to commit to clear, data-driven attribution and incrementality while faced with the sunsetting of third-party cookies. This confluence of forces is drawing marketers into direct engagement with technology providers like The Trade Desk, who have offered Unified ID 2.0, which allows advertisers to manage their data and target customers with greater independence.

As I discussed earlier, modern marketing was built on the premise of having access to fine-grained third-party data. As that data regime is ending, the alternative must rely on improved predictive capabilities. This means that firms cannot afford to sit on the sidelines as AI and machine learning rise. Managers must move out of their comfort zone and stop pigeonholing data science as merely a tool for report and dashboard generation. Rather, data science is central to the emerging paradigm of managerial decision-making: one in which decisions are automated, scaled and personalized to the individual customer.

This AI-centered model is already the reality for some of the most tech-savvy and profitable firms in the world, and novel technology integration has accelerated this year as AI is widely embraced and adopted. Given the importance and sensitivity of first-party data, building relationships with consumers and communicating to them how they benefit from the use of their data is more important than ever. I learned in recent conversations with Meta executives that targeting effectiveness has, by many metrics, returned to the levels experienced before Apple’s “opt-in” policy upended things in 2017, and this reversion to greater efficacy is thanks to innovations in AI-based models that learn complex patterns in ad preferences without needing third-party data. The challenge now is how to feasibly scale these technologies across the digital economy.

The challenges arising from the continuing sea change amplify the incentives for marketing organizations to use data science and AI systems, approaches that have already demonstrated astounding capabilities for innovation and cost-cutting. End-to-end AI and machine learning solutions hold the promise of clarifying identity resolution, and educational institutions, including the University of North Carolina at Chapel Hill  and UNC Kenan-Flagler Business School, are now able to equip students with the skill sets needed to build and deploy such tools. The managers and organizations who can synergize these technologies and labor while investing in first-party data collection will gain a competitive edge.

This article is part of our Grand Challenge series on business resilience.

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