Signal Break: The Real Take on the LiveRamp Acquisition by Publicis Groupe

Beyond the Pixel: Jer Tippets on AI, Customer Data, Privacy, and the Future of Digital Measurement

Every AI breakthrough begins with something far less glamorous: clean, trustworthy data. In this episode of Signal & Noise, Brett House and Rio Longacre sit down with Jer Tippets, Director of Digital Tagging & Implementation at Hyatt Hotels, to explore the invisible infrastructure that powers modern digital marketing. While everyone is talking about generative AI, personalization, and autonomous agents, Jer argues that none of it works without a solid data foundation—and after spending more than 15 years building customer data systems for global brands, he's uniquely qualified to explain why.  Rio first met Jer when they were both speakers at Tealium's Digital Velocity Conference, where Hyatt shared its customer data strategy and philosophy of treating customers like humans. Hyatt has long been a Tealium customer, and Tealium—one of Signal & Noise's valued sponsors—has played an important role in helping leading enterprises modernize their customer data infrastructure. That shared connection made this conversation a natural fit and one we've wanted to have ever since. Together, they dive into why poor data quality quietly kills AI initiatives, why organizations continue to collect mountains of unusable information, and why "collect everything" has become one of the biggest mistakes in modern marketing. Jer explains why first-party data is now one of the most valuable strategic assets a company can own—and why governance, identity resolution, and privacy have become board-level business issues rather than back-office technical concerns.  The conversation also pulls back the curtain on Hyatt's approach to digital experience, exploring how one of the world's largest hospitality brands balances personalization with consumer trust across millions of guest interactions. From persistent customer identities and consent management to CDPs, synthetic audiences, and the promise—and reality—of AI-driven personalization, Jer offers a refreshingly practical perspective shaped by years of real-world implementation. Rather than chasing hype, he focuses on what actually delivers better customer experiences.  Jer also shares why AI should be viewed as an amplifier—not a replacement—for human expertise, why data governance is becoming one of the most important competitive advantages organizations can build, and what the next generation of digital measurement will look like as AI agents increasingly become both the producers and consumers of marketing data. If you've ever wondered why some brands consistently deliver seamless, personalized experiences while others struggle with fragmented customer journeys, this episode explains what happens behind the scenes—and why the future of AI may ultimately depend less on better models and more on better data. * Why AI is only as good as the data beneath it * How Hyatt approaches customer identity and digital experience * Why first-party data has become a strategic business asset * The hidden costs of poor data quality * Privacy, consent management, and earning customer trust * Why "collect everything" is the wrong data strategy * The realities of CDPs, synthetic audiences, and identity resolution * How AI is changing digital implementation and analytics * Why governance is becoming a competitive advantage * What marketers should do today to prepare for an AI-first future Whether you're a CMO, MarTech leader, data engineer, product owner, analytics professional, or simply fascinated by the future of AI and customer experience, this conversation offers an inside look at the systems powering every click, every recommendation, and every personalized interaction. Guest: Jer Tippets Director of Digital Tagging & Implementation Hyatt Hotels

The Race to the Bottom: Media Quality, Attention, and Why Cheap Reach Is Costing Brands More Than They Think

For nearly two decades, digital advertising has optimized around one primary objective: finding the cheapest possible way to reach the right person. Programmatic buying, identity signals, attribution, and performance marketing have created extraordinary efficiency—but they may also have trained the industry to systematically undervalue one of the most important variables in advertising effectiveness: the quality of the media itself. In this episode of Signal & Noise, Rio Longacre and Brett House welcome back friend of the podcast Erez Levin for his third appearance and his second full-length conversation. Erez is one of the industry's most respected voices on media quality, attention, and advertising effectiveness. A former Google executive and now Founder of Emet Advisory Advisory, he recently co-authored CIMM's landmark report, Quality Matters: Navigating Quality in Media Buying and Measurement, an effort to establish a common industry framework for evaluating media quality. The conversation explores a simple but powerful premise: Not all impressions are created equal. While the industry has become exceptionally good at optimizing for identity, CPMs, and short-term outcomes, it has largely ignored the environments where advertising actually appears. As deterministic identity signals become less reliable and privacy regulations reshape digital advertising, Erez argues that marketers must begin treating media quality as a first-class buying signal—not merely a brand safety filter. Topics include: * Why optimizing exclusively for ROAS and CPMs can quietly destroy long-term brand growth * How the industry's obsession with attribution created a "race to the bottom" in media buying * Why attention alone is an incomplete measurement framework * The difference between audience quality, media quality, and creative quality—and why all three matter * Why premium inventory isn't binary, but exists on a spectrum of value * The hidden problems with averaging performance across wildly different media environments * Why CTV has an opportunity to avoid repeating the mistakes of display advertising * How marketers should rethink media planning as identity signals continue to weaken * Why procurement incentives often work against advertising effectiveness * Practical ways brands can begin incorporating media quality into buying decisions today * The future of AI-driven media buying and whether automation will improve—or worsen—advertising quality * Why marketers—not platforms or agencies—must ultimately lead this shift The discussion also expands into broader industry questions, including the future of the open web, the role of private marketplaces, the economics of connected television, media governance, AI-generated advertising, and whether today's measurement systems are rewarding the wrong behaviors. Throughout the conversation, Erez makes the case that quality is not a "nice to have." It is a pricing signal. One that may become increasingly important as AI, automation, and privacy reshape the advertising ecosystem. If you've ever wondered why digital advertising often feels more optimized than effective—or why brands continue chasing cheaper impressions while premium publishers struggle to monetize quality—this conversation explains why. Whether you're a CMO, agency executive, media planner, AdTech leader, publisher, or simply interested in where digital advertising is headed next, this is an essential discussion about one of the industry's most important strategic shifts. Guest: Erez Levin, Founder, Emmett Advisory; former Google executive; co-author of CIMM's Quality Matters report. Connect with Erez: https://www.linkedin.com/in/erezlevin/ [https://www.linkedin.com/in/erezlevin/]

Signal Break: Agentic Trading Is Here

This week, the future of digital advertising arrived. Following Boostr and Vox Media’s landmark announcement of one of the industry’s first public agentic media buys using AdCP, Signal & Noise sits down for an exclusive conversation with Patrick O’Leary, Founder & CEO of Boostr, to unpack exactly what happened—and why it matters. For months, we’ve argued that agentic trading wasn’t a distant vision. It was already beginning. This announcement is one of the clearest signals yet that AI agents are moving beyond copilots and into autonomous negotiation, with buyer and seller agents working directly together to execute media transactions. This isn’t another AI hype discussion. Patrick walks us through the transaction in detail: how the agents negotiated, what humans still controlled, how long the process took, what the pilot revealed, and why this could fundamentally reshape the economics of digital advertising. We also tackle the bigger questions: * Does agentic trading replace programmatic or evolve alongside it? * What happens to DSPs, SSPs, and today’s ad tech ecosystem? * How do identity, fraud prevention, brand safety, and measurement work in an agent-driven world? * Which companies stand to benefit—and which business models are suddenly at risk? At Signal & Noise, we don’t do hot takes. We bring together the people who are actually building the future and give them the time to explain what they’re doing, why they’re doing it, and what it means for the rest of the industry. If you’ve been wondering whether agentic trading is real, this is the conversation you’ve been waiting for. Guest: Patrick O’Leary, Founder & CEO, Boostr If you enjoy conversations that go beyond the headlines, subscribe to Signal & Noise on YouTube, Spotify, Apple Podcasts, or visit SignalAndNoise.ai [http://SignalAndNoise.ai] for more executive interviews, analysis, and original research.

Can We Still Trust Attribution? Brian Quinn on AppsFlyer, Privacy, and Measurement

Attribution was supposed to get easier. Instead, marketers today operate in a world of disappearing identifiers, privacy restrictions, walled gardens that increasingly measure themselves, and consumer journeys that unfold inside environments few advertisers can fully observe. So how much confidence should we still have in the numbers? In this episode of Signal & Noise, Brett House and Rio Longacre sit down with Brian Quinn, President & GM of AppsFlyer, one of the most influential—but often least understood—companies in digital advertising. For more than a decade, AppsFlyer has been at the center of mobile measurement, helping brands understand where users come from, which campaigns actually drive installs and engagement, and how to measure effectiveness in an ecosystem transformed by Apple’s ATT framework, signal loss, and evolving privacy regulations. Together, we unpack one of the industry’s most important questions: Can attribution still be trusted? The conversation explores why mobile remains the dominant yet underappreciated consumer environment, whether multi-touch attribution still has a future, and why marketers are increasingly turning toward incrementality, clean rooms, and econometric approaches to understand what really drives business outcomes. We also discuss: • Why AppsFlyer became much more than an attribution company• Whether the walled gardens are effectively grading their own homework• The lasting impact of Apple’s App Tracking Transparency changes• Why fraud remains a massive hidden tax on digital advertising• The growing role of clean rooms and independent measurement• Whether privacy has made advertising measurement better—or simply more uncertain• How AI may reshape attribution and optimization over the next five years• What a modern measurement strategy should look like in a world where signal loss may be permanent Apps account for nearly 90% of mobile time, consumers spend hours each day inside apps, and marketers collectively spend more than $150 billion annually on mobile advertising. Yet many advertisers still struggle to explain how mobile attribution actually works—or what replaces it when deterministic signals disappear. Brian offers a candid and practical perspective on where measurement is heading next, what marketers misunderstand about attribution, and what parts of today’s measurement stack may disappear entirely. If you’ve ever wondered whether the industry’s most trusted metrics deserve your trust—or what comes after attribution—this episode is for you. #SignalAndNoise #AppsFlyer #Attribution #Measurement #Privacy #AdTech #MarTech #MobileMarketing #CleanRooms #MTA #Incrementality #DigitalAdvertising

The Anti-Tech Era? Al Regulation, Data Centers & America's Growing Governance Clash

Colorado has become ground zero in one of the most important debates shaping the future of technology: how do we regulate AI without slowing innovation? In this episode of Signal & Noise, Brett House and Rio Longacre sit down with Srinivas "Chinnu" Parinandi, Associate Professor of Political Science at the University of Colorado Boulder, to unpack the growing clash between government oversight, technological progress, and economic competitiveness. The conversation begins with Colorado's controversial AI legislation and expands into a broader discussion about privacy regulation, federalism, interstate commerce, and the unintended consequences of state-by-state technology governance. Chinnu explains why populism on both the political left and right is driving increased scrutiny of technology companies, how fragmented regulation affects startups versus large incumbents, and why policymakers often struggle to keep pace with rapidly evolving technologies.  The discussion also explores the influence of GDPR and other privacy frameworks, whether regulatory uncertainty is becoming a barrier to entrepreneurship, and how businesses can engage more constructively with policymakers rather than simply opposing regulation. Chinnu offers a nuanced perspective on whether America needs a national AI framework and why the answer may be more complicated than many in the tech industry assume.  In the second half of the episode, the conversation turns to one of the most overlooked aspects of the AI boom: data centers. As AI workloads drive unprecedented demand for computing power, local opposition to data center projects is growing across the country. Chinnu explains the politics behind energy consumption, power generation, utility regulation, zoning battles, and the increasing tension between infrastructure development and community concerns.  The episode closes with a discussion of whether America is entering an "anti-tech era," what role government should play in shaping emerging technologies, and whether the United States can strike the right balance between consumer protection and innovation in the age of AI.  * Colorado's AI laws and privacy regulations * SB26-134 and SB26-189 * GDPR, CCPA, and state-level privacy frameworks * AI regulation and interstate commerce * Federal vs. state governance * Populism and technology policy * Startup innovation and regulatory burden * Data centers, energy, and infrastructure * NIMBYism and local opposition movements * America's AI competitiveness versus China * The future of AI governance Srinivas Parinandi is an Associate Professor of Political Science at the University of Colorado Boulder whose research focuses on political economy, American political institutions, public policy, technology governance, and the interaction between government regulation and business innovation. His work examines how political incentives and institutional structures shape economic outcomes and emerging technology markets. #AI #ArtificialIntelligence #Privacy #GDPR #CCPA #Colorado #DataCenters #TechnologyPolicy #Regulation #PoliticalEconomy #SignalAndNoise #AdTech #Innovation #TechPolicy #AIRegulation