Next in Media

In this episode of Next in Media, I sit down with Mike Law, CEO of Carat North America, to talk about one of the biggest tensions in modern media: the push for more targeted TV advertising versus the risk of going too narrow and losing brand growth. Mike and I discuss how brands have at times gotten too addressable, siloing themselves into repeat customers while forgetting to grow the top of the funnel. We dig into the fragmentation challenge across streaming, CTV, and social video, and why defining your audience has never been harder with a million data sets and walled gardens competing for attention. We also get into how YouTube is becoming more like TV every day, the evolving role of creators in upfront conversations, and whether creator media belongs in the same budget bucket as a big show on CBS. Mike shares how Carat is using AI agents to run multiple media plan scenarios in minutes instead of hours, and we explore what the next generation of media planners (AI native, digital native) will bring to the industry. We wrap up talking about measurement, why the industry needs to come together to solve identity and addressability, and what Go Addressable is doing to advance deterministic audience-based advertising at scale. __________________________________________________ Key Highlights   📺 CTV Targeting vs. Brand Growth: Mike argues that brands have sometimes gotten too addressable, squeezing existing customers dry before realizing they need to find new audiences to grow the business. 🔀 Fragmentation Is the Core Challenge: With a million data sets, walled gardens, and consumers bouncing between streaming, search, and LLMs in seconds, the media planning landscape is what Mike calls a "bowl of spaghetti." 📱 YouTube as TV Replacement: Mike sees YouTube becoming more like television every day, but its dual identity as both a TV replacement and a social video performance platform makes it tricky to plan against. 🎥 Creators in the Upfront: Long-form, episodic creators are increasingly part of upfront conversations, but the question remains whether they belong in the TV budget or require their own planning approach. 🤖 AI Agents for Media Planning: Carat is using AI agents to generate eight to ten versions of a media plan at once, letting planners compare trade-offs and craft strategy faster than ever. 📊 The Measurement Gap: Cross-platform measurement remains fragmented, and Mike believes the industry needs to come together to solve identity and comparability across CTV, linear, and digital. 🌐 Go Addressable and Industry Collaboration: The episode is part of a special series with Go Addressable, the trade organization working to advance deterministic audience-based advertising across the full TV ecosystem. __________________________________________________ Resources & Next Steps   🌐 Learn more about Go Addressable at GoAddressable.com 🔗 Follow Mike Law on LinkedIn 🎧 Subscribe to Next in Media on Apple Podcasts __________________________________________________ Timestamps   00:00 Cold open: the state of TV targeting and brand growth 01:07 Introducing Mike Law, CEO of Carat North America 01:43 Where we are with CTV targeting today 03:25 When brands get too addressable and forget reach 05:00 The cycle of squeezing audiences and finding new ones 06:50 Fragmentation, walled gardens, and identity challenges 08:50 How identity resolution tools are evolving 10:15 YouTube as a TV replacement and where it fits 12:53 YouTube in the upfront: TV bucket or something else? 14:47 Creators in upfront conversations and long-form episodic content 17:30 The premium creator economy and brand integrations 19:30 AI in media planning: what is changing day to day 22:00 AI agents running multiple plan scenarios at Carat 23:13 The next generation of media planners (AI and digital native) 25:30 Measurement challenges across platforms 27:30 Industry collaboration and lessons learned 28:42 Wrap up and Go Addressable sponsor message

In this episode of Next in Media, I sit down with Ryan Detert, CEO of Influential, the creator marketing company that was acquired by Publicis in 2024. Since the acquisition, Influential has seen massive growth, also acquiring Captiv8 to build out a global offering combining technology, services, and measurement all in one place. Ryan and I dig into how brands are structuring their creator teams, why a center of excellence led by media is where the most success is happening, and how technology (especially brand safety tools) has become the non negotiable foundation for scaling influencer campaigns. We also cover the measurement question that every marketer is asking: can you prove creator ROI? Ryan walks us through how MMMs are finally capturing creator value, why always on strategies beat tentpole campaigns, and how platforms like YouTube, TikTok, and Instagram are each fighting for attention in different ways. We get into the AI question too, from "slop" concerns to the future of creator likeness licensing and NIL rights. Ryan makes the case that AI will transform the back end of the business (speed, sourcing, brand safety) long before it replaces human creators in the feed. Plus, Ryan shares why the greatest ROI often comes from 100 micro creators rather than one mega deal. __________________________________________________ Key Highlights   🚀 Influential's Post Acquisition Growth: Since being acquired by Publicis in 2024, Influential has seen "massive multiples" of growth and also acquired Captiv8 to consolidate technology, measurement, and services into one global platform. 🛡️ Brand Safety as the Foundation: Ryan calls it the "Hippocratic Oath" of influencer marketing. With 15 million plus creators in their database, technology is essential for vetting creators across profanity, nudity, hate speech, and reputational risk before any campaign launches. 📊 Proving Creator ROI Through MMMs: Influencer marketing is a $35 billion TAM because it works. Ryan explains how media mix models are finally capturing creator value, and why brands need to break down creator spend by platform, paid vs. organic, and on vs. off social to get accurate measurement. 📺 The Platform Attention Wars: YouTube dominates long form because it pays creators the most. TikTok owns the meteoric rise. Instagram is aspirational. Meta is a messaging platform. Every platform has both a live strategy and a TV strategy, and all are competing for the same attention. 🤖 AI and Creator Content Transparency: AI is "not a dirty word" as long as it augments a real human. Ryan believes brands will embrace AI generated creator content only when NIL licensing ensures creators are compensated and consumers don't feel duped. 🎯 Micro Creators vs. Mega Deals: For brands with a $2 million budget, 100 targeted micro creators often outperform a single mega creator deal. Ryan compares it to buying one Super Bowl ad vs. going deep across cable networks. 🔄 Always On Beats Tentpole Campaigns: Brands that only activate around the Super Bowl, summer, and holidays are letting competitors eat their lunch in between. Long term creator partnerships drive both efficiency and authenticity. __________________________________________________ Resources & Next Steps 🌐 Learn more about Influential 🎧 Subscribe to Next in Media on Apple Podcasts __________________________________________________ Timestamps   00:00 Cold open on creator marketing growth and AI 01:13 Meet Ryan Detert, CEO of Influential 02:07 Life after the Publicis acquisition 04:04 Where creator teams fit inside brand organizations 06:04 Technology's role in scaling influencer marketing 07:00 Brand safety as the non negotiable first step 08:52 Managing creator campaigns at scale 09:44 Proving creator ROI through measurement and MMMs 12:43 YouTube on TV and the platform attention wars 16:11 Micro vs. macro creators and where the real ROI lives 18:22 AI transparency and the slop problem 20:46 Creator likeness, NIL, and AI generated content 23:05 Episodic content and always on brand partnerships 25:04 The future of creator marketing in three to five years

In this episode of Next in Media, I sit down with Adam Roodman, General Manager of Yahoo DSP, to talk about how Yahoo has quietly built one of the most compelling demand side platforms in the market. Adam walks through Yahoo's positioning in the ongoing DSP wars, why their identity graph and ConnectID solution give advertisers an edge in a world of increasing signal loss, and how the platform's deep roots in connected TV and live sports are creating new opportunities for performance marketers. We also get into Yahoo's massive supply path optimization efforts and why having fewer, higher quality paths to inventory is becoming a real differentiator. Adam and I also dig into the rapidly evolving world of agentic AI in advertising and what it actually means today versus the hype. He shares Yahoo's perspective on the protocol debate between A2A and MCP, why data quality and content accuracy are table stakes for AI agents, and how Yahoo is building an "AI librarian" function to ensure agents can operate with the right context. We also explore how CTV inventory has exploded on the platform, why live sports are changing the addressable advertising landscape, and Adam's take on whether AI will truly reduce headcount or just shift how teams operate. __________________________________________________ Key Highlights   🏆 Yahoo DSP in the DSP Wars: Adam explains why Yahoo is committed to the DSP business for the long haul, leveraging their unique combination of owned and operated properties, a massive identity graph, and deep integrations with premium supply. 🔐 Identity as a Competitive Moat: Yahoo's ConnectID and proprietary identity graph give advertisers access to durable, individual-based data across browsers, devices, and CTV, driving better performance in a signal-loss world. 📺 CTV and Live Sports Explosion: The amount of live sports on Yahoo's platform has doubled in nine months, and addressable, biddable premium CTV and audio inventory continues to surge, opening new opportunities for performance marketers. 🤖 Agentic AI and the Protocol Debate: Adam shares Yahoo's view on the A2A vs MCP protocol discussion, emphasizing that agentic AI is not a strategy in itself. It's about how you operate it and ensuring agents have access to accurate, contextual data. 📚 The AI Librarian Function: Yahoo is evolving from a "tech writer" approach to an "AI librarian" model, ensuring that content, documentation, and data fed into AI systems are high quality, accurate, and written with good context. 🔗 Supply Path Optimization at Scale: Yahoo has reduced tens of thousands of supply paths down to focused, high quality routes, improving auction dynamics and giving advertisers cleaner access to premium inventory. ⚡ AI Won't Replace Teams, It Will Reshape Them: Adam argues that AI adoption in advertising is less about replacing people and more about conviction and operational change, predicting that early movers will see compounding advantages. __________________________________________________ Resources & Next Steps   🌐 Learn more about Yahoo DSP and ConnectID 🔗 Follow Adam Roodman on LinkedIn 🎧 Subscribe to Next in Media on Apple Podcasts __________________________________________________ YouTube Chapter Timestamps   00:00 Cold open: identity, CTV, and agentic AI in advertising 01:46 IntentIQ ad: privacy-first identity resolution 02:10 Meet Adam Roodman, GM of Yahoo DSP 03:30 Yahoo's commitment to the DSP business 05:20 ConnectID and Yahoo's identity advantage 07:30 How identity drives better CTV performance 09:45 Live sports doubling on the platform 11:30 Supply path optimization and auction quality 13:40 The DSP wars and competitive positioning 16:00 Agentic AI: what it means today vs the hype 18:30 The A2A vs MCP protocol debate 20:45 Building the AI librarian function at Yahoo 23:00 Data quality as table stakes for AI agents 25:30 Will AI reduce headcount in advertising? 28:00 CTV inventory explosion and addressable audio 30:30 Advice for brands getting started with AI 33:00 Wrap up: Yahoo's Adam Roodman, Sabio, and IntentIQ

In this episode of Next in Media, I sit down with Sam Garfield, Head of Digital Strategy for CMT Data and AI Platforms at Adobe, to explore how Adobe is quietly becoming the backbone of modern marketing. Sam breaks down how Adobe operates across three core layers: the creative layer (Creative Cloud and Firefly AI), the content supply chain layer (Workfront and asset management), and the data and experience layer (customer data platforms and analytics). Together, these tools form what Sam describes as an operating system for marketers -- a full-stack solution that takes a brand from ideation all the way through activation and measurement. We also dig into the rise of creative intelligence and what it means for brands, agencies, and the future of advertising. Sam unpacks Adobe's Winterberry Group research showing a 23% increase in investment in creative intelligence, and explains why creative can no longer be treated as a fixed cost. We cover how generative AI is accelerating asset production at scale, why agencies are leaning into Adobe's platform rather than building from scratch, and how agentic AI is beginning to appear inside existing workflows. Sam also reveals that traffic to brand sites and publishers is down 40% as LLMs reshape discovery, and shares how Adobe's new LLM Optimizer tool is helping brands regain visibility in a generative search world.   Key Highlights 🖥️ Adobe's Marketing Operating System: Sam breaks down how Adobe's three-layer platform -- creative, content supply chain, and data -- functions as an end-to-end OS for brands and agencies. 🤖 Generative AI and the Asset Scale Problem: Sam walks through the math problem facing global brands -- producing assets across formats, languages, and channels -- and why generative AI is the only scalable solution. 📊 Creative Intelligence Is the Next Frontier: Adobe's research with Winterberry Group found a 23% increase in creative intelligence investment -- and Sam explains why understanding why content performs is becoming as systematic as audience targeting. 🏢 Agencies Are Building on Top, Not From Scratch: Major holding companies are integrating Adobe into their proprietary platforms rather than building from scratch -- including a recently expanded WPP partnership. 🔍 LLMs Are Reshaping Brand Discovery: Adobe's research shows traffic to brand sites is down 40% as AI changes how consumers find information. Sam shares how Adobe's new LLM Optimizer helps brands monitor and improve their visibility inside AI-generated results. ⚡ Agentic AI Is Here but Still Early: There is no end-to-end agentic advertising solution yet. Adobe's approach is to embed agentic tools inside existing workflows so teams can get started without overhauling their entire operation. Resources & Next Steps 🌐 Explore Adobe's Marketing and AI Solutions 🔗 Follow Sam Garfield on LinkedIn 🎧 Subscribe to Next in Media on Apple Podcasts   YouTube Chapter Timestamps 00:00 Cold open -- AI's impact on advertising and brand discovery 01:00 Mike introduces Sam Garfield and Adobe's role in ad tech 01:30 Sam's background and Adobe's history in advertising 02:00 Adobe's three-layer marketing platform explained 03:00 The 'operating system for marketers' concept 03:50 Who is Adobe's customer -- brands, agencies, or publishers? 04:20 The expanded WPP and agency partnership announcement 05:10 Where creative AI optimization stands today 05:40 The asset scale math problem facing global brands 06:20 Laying the generative AI foundation for creative 07:10 From production efficiency to intelligent automation 08:00 Precor creative intelligence and variation at scale 08:40 How conservative vs. progressive brands approach AI 09:10 Adobe Firefly and legally obtained training data 09:40 Workflow integration as the real barrier to adoption 10:10 Humans as creatives, AI as the production layer 10:50 How Adobe fits alongside platform-native AI tools 11:30 Why CMOs won't hand over full creative control to platforms 13:30 Adobe's Winterberry Group creative intelligence research 14:00 Creative as a performance driver, not a fixed cost 14:30 The 23% increase in creative intelligence investment 15:00 Where creative intelligence works -- display, social, CTV 15:30 Early findings and the testing and learning phase 16:10 Are creative agencies threatened or empowered by AI? 16:30 How major holding companies are building on Adobe's OS 17:10 Automating rote work to free up strategic creative thinking 18:20 Creative AI and media buying converging 19:00 Data and creative intelligence coming together at Adobe 19:40 The future of always-on marketing vs. campaign flights 20:20 The network operations center vision for marketing 21:00 Agentic AI in advertising -- where things actually stand 21:30 Adobe's approach to building agentic tools inside workflows 22:00 What agentic audience pulling looks like in practice 22:30 The future of media agencies in an algorithmic world 23:10 People doing higher-value strategic work, not less work 23:40 How brands are showing up inside LLMs 24:00 Adobe's research -- traffic to brand sites down 40% 24:30 Introducing the LLM Optimizer tool 25:00 Structuring content for generative engine optimization 25:40 Will search ad budgets shift to LLM visibility strategies? 26:20 The unknown future of advertising inside AI-generated results 27:10 Wrap-up -- the fulfillment of advertising's long-promised future

In this episode of Next in Media, I sit down with Philip Inghelbrecht, Co-Founder and CEO of Tatari, to unpack why one of the most innovative companies in TV advertising has built its entire thesis on a contrarian idea: that programmatic CTV is the wrong tool for most of the television market. Philip walks through how Tatari operates as a full infrastructure holding company, combining a demand-side platform, a supply-side solution called Upstream, and a privacy and identity layer called Vault. From day one, Tatari has argued that unlike display advertising, connected TV is dominated by a small number of premium publishers, and that automating around them rather than through open exchanges is the smarter path forward. Philip breaks down the $30 billion US CTV market, explaining how roughly half flows through programmatic channels and how up to half of that programmatic slice is fraud or low-quality inventory. The premium inventory that actually drives results, including sports, tentpole events, and top-tier streaming placements, lives almost entirely outside programmatic pipes and has historically required massive budgets and manual negotiation to access. That is exactly the gap Upstream was designed to close. By building custom, direct integrations with the five biggest TV publishers, including Disney, Warner Bros., NBCUniversal, and Paramount, Tatari has automated that direct buying process end to end, giving a much broader range of brands access to premium TV inventory without sacrificing pricing control, brand safety, or transparency.   Key Highlights 📡 Programmatic CTV Is Built on the Wrong Foundation: Philip explains why the SSP/DSP model designed for display advertising is a poor fit for connected TV, where 90% of streaming impressions come from the same top 10 publishers and the most valuable inventory never appears in an open exchange. 💰 The $30 Billion Reality Check: Of the roughly $30 billion US CTV market, about $15 billion flows through programmatic. Philip reveals that up to half of that programmatic pool is fraud or low-quality supply, meaning only $7 to $8 billion represents genuinely premium inventory. 🚀 Upstream Brings Automation to Direct TV Deals: Tatari spent nearly two years building one-to-one tech integrations with Disney, Warner Bros., NBCUniversal, and Paramount, enabling fully automated direct buys that preserve the brand safety and pricing control of traditional direct sales while eliminating manual overhead. 📺 Premium TV Is Now Within Reach for More Brands: Upstream shifts TV advertising from a big-budget brand privilege to something accessible to a much broader set of advertisers. Brands that never could have accessed premium placements now have a real path in, and early publisher partners have already seen doubled transaction volume during the test period. 🤖 AI in TV Advertising Has Promise But Real Limits: Philip is measured about AI's near-term impact on TV. He sees immediate wins in automating creative pre-approval and longer-term potential in data-driven yield optimization for publishers, but pushes back on the idea that AI will quickly transform the TV creative production process.   Resources & Next Steps 🔗 Follow Philip Inghelbrecht on LinkedIn 🌐 Explore Tatari 🎧 Subscribe to Next in Media on Apple Podcasts   Chapter Timestamps 00:00 Cold open - the programmatic CTV reality check 01:18 Introducing Philip Inghelbrecht and Tatari 01:58 Tatari's three-product infrastructure stack explained 03:30 Why programmatic does not fit connected TV 05:00 The problem with SSP aggregation in a concentrated market 06:17 How Upstream was born from supply-side tech 07:22 Breaking down the $30 billion CTV market 08:06 Half of programmatic CTV is fraud or low quality 09:44 Building direct integrations with Disney, Warner, NBCU, Paramount 10:17 How automation benefits publishers and speeds up transactions 11:45 Doubling volume with early publisher partners 12:28 Is TV right for SMBs? Philip's honest take 13:47 Where Upstream takes the market next 15:00 Using first-party data to drive higher publisher yield 16:21 Programmatic still has a role, just not the biggest one 17:17 What Dentsu and WPP's open path retreat signals 18:26 Will the walled gardens ever join Upstream? 18:52 What changes for existing Tatari advertisers 20:00 AI and the future of TV advertising 22:11 AI creative tools: impressive but still five days of editing 22:56 AI for creative pre-approval: what works today 24:16 First-party data capture is harder than it looks 25:36 Measurement, look-alike audiences, and machine learning loops 26:13 Closing thought - the biggest TV inventory is not in programmatic

Leanne Perice, founder and CEO of Made by All and creator-management pioneer, built a creator-first agency that doubled revenue yearly and now spans Dubai. She explains the DASI framework and why brands stop at distribution. Conversations cover creator-led storytelling via Made By Us, YouTube long-form opportunity, platform-driven brand deals, and bridging Hollywood and creator business models.

In this episode of Next in Media, I sit down live at the Kochava Summit in Sandpoint, Idaho, with Charles Manning, founder and CEO of Kochava. We go deep on one of the most pressing questions facing the industry right now: how profound is the shift to agentic advertising and AI-driven workflows? Charles argues it is not a decade-long evolution like programmatic was. It is breathtakingly faster, and the companies that understand how to use their first-party data as a competitive kernel, rather than leaking it to the walled gardens, are the ones that will come out ahead. He draws a compelling analogy: if programmatic changed the auction, AI is about to change the workflow.We also dig into Kochava's CTV journey, from its mobile app roots to building measurement tools adopted by LG, Samsung, Vizio, and Roku, and how the view-and-do combo between the TV screen and the mobile device is creating powerful new outcome-based measurement opportunities for brands. Charles breaks down what holding companies should fear (and fix), why the ad tech supply chain is due for serious consolidation, and why he predicts a wave of take-privates and roll-ups followed by a bonanza of public offerings over the next two years. He also introduces Station One, Kochava's integrative AI hub that acts like a Slack for AI workflows, designed to help teams transform how they work without giving up control of their data. Key Highlights:⚡ AI vs. Programmatic: Charles explains why the shift to agentic advertising is moving breathtakingly faster than programmatic did. While programmatic took over a decade to fully reshape the auction, AI is set to transform the entire workflow within the next 16 months.🔒 Protect Your Data: Charles identifies the two biggest risks brands face in the AI era. First, leaking proprietary data to platforms like Meta and making them smarter without benefiting your own organization. Second, failing to develop a unique "how" that cannot be replicated when everyone has access to the same AI tools.📺 CTV Measurement Evolution: Kochava's Atlas Performance product now powers CTV measurement for LG, Samsung, Vizio, and Roku by connecting the view on the television screen with the action on the mobile device, giving brands a clear picture of real business outcomes from their CTV spend.🤖 Station One, a Slack for AI: Charles introduces Kochava's Station One platform, an integrative AI hub that lets teams connect models, codify skills, build knowledge bases, and containerize workflows into shareable workspaces, all while keeping data ownership firmly in the hands of the brand.📉 Ad Tech Consolidation Is Coming: Charles predicts a significant collapse in the ad tech supply chain, with SSPs and DSPs already moving into each other's territory. He also foresees a wave of take-privates and roll-ups over the next 16 months, as companies use the cover of private ownership to restructure for the AI era, followed by a major IPO bonanza.💼 The Future Workforce: As AI handles more of the analytical grunt work, Charles argues the most valuable skill in the industry is shifting away from data science and toward clear communication. The ability to articulate your goals to an AI model is becoming the defining talent of the next generation of media professionals. Resources & Next Steps:🌐 Explore Kochava and learn more about Atlas Performance and Station One🔗 Follow Charles Manning on LinkedIn🎧 Subscribe to Next in Media on Apple Podcasts Chapter Timestamps:00:00 Cold open - AI disruption and the next 16 months01:00 Welcome and introducing Charles Manning of Kochava01:20 Revisiting a past conversation and what has changed01:45 Setting the stage - agentic advertising and the metaverse PTSD problem02:20 The next decade is really the next 16 months03:10 How fast is this vs. the programmatic shift?03:50 MCP, APIs, and how AI wraps the workflow05:20 Machine learning from reach optimization to business outcomes06:10 From post-campaign briefs to real-time workflow automation07:20 Why big platforms like Meta and Google got even stronger with AI08:00 The two biggest risks brands face in the AI era09:00 The "how" is as important as the "what" - competitive differentiation09:50 Can agencies avoid being commoditized by AI?10:20 Vertical AI and why domain expertise matters12:00 Measurement as an odometer vs. measurement as a decision engine13:20 The racing clutch analogy - agile measurement for agile goals14:00 Who fills the seats next? The shift from data scientists to communicators15:00 Tasks that get reallocated and skills that become more valuable16:00 How far away is autonomous agentic media buying?16:30 Guardrails, budget constraints, and agent managers17:10 Introducing Station One - Kochava's AI workflow hub18:10 How teams transition from human workflows to AI-assisted execution19:00 Kochava's CTV journey - from mobile app roots to the living room20:10 The 80-inch mobile device and why OEMs saw the pattern21:20 Why OEMs pushed back and how Atlas Performance was born22:10 LG, Samsung, Vizio, Roku - how they became Kochava customers23:00 Is CTV performance TV? How should we measure it?23:40 The view-and-do combo - TV impressions and mobile actions24:10 QSR and loyalty programs - CTV driving real consumer behavior25:00 Why AI optimization has not hit CTV the way it has Meta and Google26:00 Station One as the connective tissue for CTV and the broader ecosystem27:20 Will more ad dollars flow to television? Charles says yes, and soon28:30 Audience Q&A - how to prove CTV incrementality to your CFO29:00 The Machine Zone story and what it taught Charles about media mix31:30 Why media mix modeling finally works in the AI era32:10 What happens to ad tech? The daisy chain gets disrupted33:00 SSPs and DSPs are already moving into each other's territory34:00 More money in media, less ad tax - where the dollars go next35:00 Premium inventory, exclusive access, and the sports betting parallel36:10 IO-level programmatic guaranteed - a bold prediction37:00 The biggest obstacle ahead - take-privates, roll-ups, and an IPO bonanza38:30 Wrap-up and closing thoughts

This week on Next in Media, I sat down with Matt Spiegel, EVP of Marketing Solutions Growth Strategies at TransUnion, to unpack one of the most pressing questions in advertising right now: what's actually changed since cookies started disappearing and privacy laws started piling up? And just as importantly, what hasn't changed? Matt brings a refreshingly practical perspective to the conversation, explaining how disconnected data infrastructure remains the biggest obstacle for most brands, even as everyone races to adopt AI-powered marketing. He breaks down why walled gardens still have an inherent advantage, how signal loss is forcing marketers to rethink their strategies, and why the industry's obsession with the "easy button" might be holding progress back.We also tackled some uncomfortable truths about where the industry is headed. Matt shared his thoughts on agentic advertising and whether bots will really replace media planners, the noisy MarTech landscape that's overwhelming CMOs, and why he believes the next economic downturn could trigger massive layoffs in marketing and advertising. Throughout our conversation, Matt emphasized that while the tools and technology are evolving rapidly, the fundamentals of good marketing haven't changed. It's about understanding your customers, connecting your data, and applying that intelligence at scale. This is a conversation for anyone trying to make sense of the chaos in modern marketing, wondering how to navigate identity resolution in a post-cookie world, or just trying to figure out which AI tools are actually worth the hype._______________________________________________________Key Highlights🔌 The Infrastructure Problem: Most brands lack connected data ecosystems. Their CRM, transaction records, and marketing databases exist in silos, making it nearly impossible to achieve the precision marketing everyone's chasing.🏰 Walled Gardens Still Win: Large platforms have a scaled, dimensional view of consumers that few brands can match. The "easy button" appeal is real, but it comes at the cost of transparency and cross-platform measurement.🤖 AI Won't Replace Humans (Yet): Agentic advertising is coming and will automate significant portions of media buying, but Matt believes we'll keep humans in the loop. The idea that bots will fully control everything is overdone, at least for now.📊 Data Hygiene Still Matters: Simple things like ensuring "Matt" and "Matthew" are recognized as the same person remain real obstacles. Many organizations are still working through basic data cleaning before they can even think about advanced AI applications.📉 Layoffs Are Coming: Matt predicts the next economic downturn will trigger massive job losses in marketing and advertising as automation takes over manual tasks. New roles will emerge, but there will be a painful transition period.📈 The Measurement Mess: Between attribution debates, walled garden metrics, and inconsistent cross-platform views, CMOs are struggling to prove ROI. The complexity isn't just technical, it's political inside organizations.🎯 Outcomes Over Tactics: Despite all the noise around cookies, signal loss, and AI, the fundamentals haven't changed. Great marketing still comes down to understanding consumers holistically and applying that intelligence strategically.⚡ It's a Noisy Time: Marketers are juggling CIOs demanding new tech, CFOs questioning results, platforms promising exclusive deals, and measurement reports that don't add up. It's chaotic, but navigable with the right analytical mindset._______________________________________________________Resources & Next Steps🌐 Learn more about TransUnion Marketing Solutions🔗 Follow Matt Spiegel on LinkedIn🎧 Subscribe to Next in Media on Apple Podcasts_______________________________________________________YouTube Chapter Timestamps00:00 Intro -- Consumer insights and AI limitations00:35 The complexity of modern marketing01:00 Episode introduction and Matt Spiegel01:34 Where we are in the identity and data landscape02:15 The marketer's challenge -- Disconnected data03:45 Why data infrastructure is the core problem05:20 The reality of data hygiene issues06:30 Signal loss and privacy regulations07:45 Platform advantages in identity resolution09:10 Walled gardens vs transparency11:00 The programmatic ecosystem revisited12:40 How agencies are investing in data capabilities14:20 The measurement and attribution challenge16:00 AI's impact on marketing decisions17:30 Why consumer insights still matter18:45 The current state of MarTech noise20:15 Startup consolidation and hype cycles21:50 Will agentic advertising replace media planners?23:20 Keeping humans in the loop24:40 The coming wave of marketing layoffs26:10 New opportunities emerging from automation27:30 The complexity brands face daily28:50 CMO tenure and pressure29:40 Final thoughts and wrap-up

David Freeman, founder of Kynetic Media Partners and former CAA digital lead, built the bridge between creators and enterprise value. He discusses turning fandom into scalable businesses. Conversations cover mega-creators like MrBeast, why creators keep control of distribution, the rise of tech-as-Hollywood, the need for operators and infrastructure, and how AI will reshape content creation.

In this episode of Next in Media, I sit down with Kiri Masters, host of the Retail Media Breakfast Club podcast, to explore the biggest shifts happening in retail media advertising. We dive into the recent announcement about ads coming to ChatGPT and what that means for brands trying to meet consumers where they are. Kiri shares her perspective on whether AI-powered shopping will truly disrupt the retail media landscape - and why she's optimistic that LLM-based ads could actually be more relevant and less annoying than traditional formats. We also unpack the Walmart-Google partnership and discuss what it signals about the future of conversational commerce.Beyond the AI conversation, we tackle some of the industry's most pressing questions. Will we see consolidation in retail media networks this year? Can shoppable TV finally gain traction? And what happens when offsite retail media faces competition from platforms with their own transactional data? Kiri brings both historical context - including a fascinating story about Piggly Wiggly's self-service revolution - and forward-looking insights about how brands and retailers need to collaborate differently. Whether you're a marketer navigating this space or just curious about where AI and commerce intersect, this conversation offers a clear-eyed look at what's real, what's hype, and what's coming next._______________________________________________Key Highlights 🤖 Ads in AI Assistants: Kiri explains why she's optimistic that ads in LLMs like ChatGPT could actually enhance the user experience rather than detract from it - as long as they're contextually relevant and leverage the deep personal insights these platforms have.🛒 The Walmart-Google Partnership: Why retailers want to maintain control as the merchant of record even as they experiment with AI-powered shopping surfaces, and what this means for the competitive landscape between retailers and tech giants.📊 Amazon's Retail Media Dominance: How Amazon has trained brands to expect exceptional reporting and data-driven insights, creating a high bar that other retailers struggle to match - and why CFOs love the platform's transparency.🔄 Consolidation is Coming: With over 250 retail media networks globally but brands only wanting to work with 5-7 partners, Kiri predicts we'll see more partnerships like Macy's and Amazon this year as the market rationalizes.💡 The Piggly Wiggly Lesson: A fascinating historical parallel about how the first self-service grocery store in 1916 got consumers to change behavior by passing savings directly to them - a lesson for how AI shopping might need to work.⚠️ Offsite Media at Risk: If AI-powered shopping takes off, offsite retail media networks could face serious competition as LLMs gain access to transaction and intent data that retailers previously controlled.🎯 Back to Category Growth: Kiri advocates for retailers and brands to move beyond performance-focused land grabs and return to collaborative trade marketing strategies that grow entire categories together._______________________________________________Resources & Next Steps 🎙️ Follow Kiri Masters and subscribe to Retail Media Breakfast Club🎧 Subscribe to Next in Media on Apple Podcasts_______________________________________________Chapter Timestamps 00:00 Introduction - Ads in AI assistants00:40 This week on Next in Media01:00 Meet Kiri Masters of Retail Media Breakfast Club01:40 Ads coming to ChatGPT and conversational search02:10 How brands follow consumers to new platforms03:30 Will AI commerce disrupt retail media?04:00 Will ads in LLMs work like Google and Facebook?04:40 The importance of trust in AI assistants05:00 Why AI ads could be better than traditional ads06:00 Context and relevance in LLM advertising07:00 The trust equation in conversational AI08:00 Understanding AI ads won't necessarily suck08:10 Walmart and Google partnership announcement08:30 Are people ready to shop through AI interfaces?09:00 Building trust through repeated exposure to LLMs09:40 Story time - buying an iPod on eBay in 199911:00 Testing Instacart on ChatGPT11:40 Sao CTV ad12:40 Why Walmart partnered with Google13:20 Retailers want to remain merchant of record14:40 Can every retailer integrate with AI platforms?15:20 Consumer choice and retailer selection criteria16:00 The Piggly Wiggly story - self-service revolution17:00 Consumer behavior change requires value proposition17:40 State of retail media today18:20 Amazon's dominance in retail media19:20 Offsite retail media and in-store opportunities20:00 How AI threatens offsite retail media networks20:40 Open web and retail media advertising21:30 Competition for audience data between retailers and LLMs22:20 Could LLMs build offsite media businesses?23:10 Will we see consolidation in retail media networks?24:00 The Macy's and Amazon partnership example24:40 Shoppable TV and CTV shopping outlook26:00 How AI shopping might impact retail media26:30 Moving beyond land grabs to category growth27:20 Wrap-up and thanks