The Yield Doctor with James Deaker

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Improving Yield Management in Digital Media

  1. 1D AGO

    RampUp 2026: Three Signals About Where AI in Advertising Is Really Heading

    I recently attended RampUp 2026, LiveRamp’s annual conference, where AI dominated almost every session and conversation. But what struck me most wasn’t the technology itself — it was how early the industry still is in figuring out how AI will actually be implemented in digital advertising. In this video I share three takeaways from the conference: AI in advertising still lacks standards. Many of the protocols that will enable AI agents to operate in advertising markets are still being developed or competing with each other. As with past infrastructure waves, standards may ultimately determine how quickly AI can scale. AI currently faces little organized resistance in AdTech. Unlike earlier innovation waves such as programmatic buying, there is not yet a strong group pushing back against AI adoption. The conversation about AI is ahead of the operational reality. Despite the intense focus on AI, relatively few companies have actually implemented agentic workflows in production environments. Finally, I discuss the tension emerging between AI acceleration and increasing privacy regulation, and why governance, control, and structured data will likely become critical capabilities for companies navigating the next phase of digital advertising. If you work in ad tech, programmatic advertising, or digital media, I’d be curious to hear your perspective on how quickly AI adoption will actually happen. — James Deaker The Yield Doctor

    5 min

  2. 4D AGO

    AI Won’t Fix Bad Data — Identity Resolution & Enrichment Drive Revenue (Brian Silver)

    AI is everywhere in digital advertising right now. But as Brian Silver (EVP, Global Marketing Solutions at TransUnion) makes clear in this conversation — AI will not fix bad data. If your identity resolution is weak… If your data is fragmented across 16 systems… If your enrichment strategy lacks depth and scale… Then AI simply accelerates confusion. In this episode of The Yield Doctor podcast, Brian and I go deep on: Why the majority of AI initiatives fail due to poor data quality Identity resolution as the foundation of revenue strategy The growing power of publisher data in the ecosystem Data enrichment and connectivity as competitive advantages Why fragmentation in CTV and global markets still matters How leading companies are using AI for propensity modeling and real business outcomes The emerging risk of synthetic traffic and AI agents We also revisit lessons from our Yahoo days and explore how the supply-side is beginning to rethink its leverage in a world dominated by demand-side scale. If you are a publisher, ad tech executive, or marketing leader trying to prepare your organization for an AI-driven future, this conversation will challenge you to focus on fundamentals — not features. Because in the end: AI won’t fix bad data. But high-fidelity identity, enrichment, and measurement can drive real revenue. Learn more about TransUnion Marketing Solutions: https://transunion.com/clarity https://www.youtube.com/@transunion

    24 min

  3. FEB 3

    Stronger Data Controls Let Companies Move Faster

    Most executives assume stronger data controls, privacy processes, and governance frameworks slow a business down. In practice, the opposite is often true. In this conversation, I’m joined by Devan Brua, Founder & CEO of PrivacyWise, to explore why weak data practices quietly create friction across product, sales, and leadership teams — and how stronger data controls actually give organizations the confidence to move faster, not slower. We discuss: Why many companies lack true visibility into their data flows, data usage, and data ownership How data privacy and data governance issues often surface late, after key product, sales, or partnership decisions are already made The gap between believing you’re “fine on data” and the operational reality inside ad tech and digital media organizations Why stronger data controls, privacy processes, and governance frameworks reduce hesitation and speed up business decision-making How AI, scale, and automation amplify existing data governance weaknesses rather than creating entirely new risks This isn’t a conversation about box-checking compliance or slowing innovation. It’s about building shared visibility, clearer decision-making, and operational confidence — so teams can move quickly without constantly second-guessing data risk. If your business relies on data for growth, this conversation will likely challenge some assumptions. I’m James Deaker — The Yield Doctor. I help digital media and ad tech companies diagnose the structural issues that quietly cap growth, and design systems that let teams operate faster with confidence. Edge Tool: https://privacywise.tech/edge/ Devan Brua: https://www.linkedin.com/in/devan-brua/

    25 min

  4. JAN 23

    Bad Ads are Good Signals

    Bad ads are rarely the real problem. They’re symptoms. Symptoms of weak incentives, poor decision-making, or ad operations teams stuck firefighting instead of optimizing. In this video, I walk through a set of external signals — things anyone can observe using nothing more than a standard browser — that often point to deeper problems in a publisher’s ad operations and yield management. When I look at a website or app for the first time, I’m not guessing. I’m looking for signals in the ad experience itself: what’s broken, what’s showing up, and what that reveals about how the business is really being run. This isn’t about naming and shaming. It’s about learning what to look for — whether you’re a publisher, an investor, an analyst, or someone evaluating an acquisition. What this video covers I break down a set of observable ad-level signals and explain what each one might indicate internally, including: Ads that fail to load or render correctly High-value placements filled with house ads or PSAs The same creative appearing in multiple ad slots Lack of advertiser diversity Aggressive ad refresh behavior Sticky ads vs. pop-ups Overall ad and advertiser quality For each signal, I evaluate: Ease to Detect — how easy it is to spot just by using the site Strength of Signal — how strongly it suggests deeper yield or operational issues Some signals are easy to spot but weak on their own. Others are harder to catch, but very concerning when you do see them. What matters isn’t any single issue — it’s the pattern across multiple signals.

    21 min

  5. JAN 15

    Three Ways Publishers Go Programmatic (And Why Most Get It Wrong)

    Most publishers don’t struggle with programmatic because of bad technology — they struggle because they never decided what programmatic is for. In this video, I break down three distinct “programmatic operating models” (not tactics), so you can recognize which one you’re actually running today — and whether it’s the one you intend to run. You’ll learn: Model 1: Programmatic as Insurance — direct sales protects premium value; programmatic just catches what’s left. Model 2: Programmatic as the Business — inventory value is maximized through scale, competition, and continuous market feedback. Model 3: The Hybrid — where most publishers live, balancing relationship-led selling with market-driven price discovery (and the complexity that comes with it). We’ll cover what each model implies for: The role of sales vs. ad ops Market exposure (and what demand you’ll never see) The quality of your pricing signal Clearance logic (waterfalls, auctions, PMPs) The risks that show up first (often before revenue moves) The big takeaway: every model can work, and every model can fail — the problems start when the model you’re running doesn’t match the model you think you’re running. If you want a second opinion on your current setup — especially if you’re in the hybrid middle-ground — reach out. I’m James Deaker. I’m The Yield Doctor.

    22 min

  6. JAN 6

    Retail Media Networks Grow in Predictable Stages — and Each One Has a Trap

    Retail Media Networks (RMNs) don’t grow in a straight line. In this video, I break down the predictable stages of growth that every Retail Media Network goes through — from early launch momentum to scaled, complex operations — and, more importantly, the challenges and traps that tend to appear at each stage. My focus here is on Retail Media Networks because they’re the fastest-growing part of our industry right now. But if you’re working at any publisher or platform experiencing rapid growth, you’ll recognize many of these same patterns. I’ve seen these stages play out repeatedly across publishers, platforms, and monetization teams. The specifics change, but the underlying dynamics don’t. In this video, we cover: • The core stages of RMN growth • Why early success often creates future bottlenecks • The operational and pricing challenges that emerge as scale increases • Where teams most often get stuck — and why • How to think ahead so today’s wins don’t become tomorrow’s problems This is a framework video — not a set of tactics. The goal is to help you recognize where you are now, and what problems you should expect next, before they catch you by surprise.

    16 min

  7. 12/08/2025

    Retail vs Commerce Media Networks: Growth, Data & AI with Danilo Tauro

    Every publisher wants a bigger slice of ad revenue. In retail, that only happens if you can prove ads drive incremental sales, not just clicks. In this conversation, I sit down with Danilo Tauro (ex–Global Director of Media, Tech & Data at Procter & Gamble; former Head of Product for Amazon Ads; ex–GM of Uber Eats Advertising; now Managing Partner at Cardigraphy AI) to unpack how retail media networks (RMNs) and commerce media networks (CMNs) really grow. We cover: The difference between retail media and commerce media – and why RMNs are a subset of CMNs Where each model has the “right to win” and how to break through growth plateaus The next wave: off-site, CTV, sponsorships, and data products Why ROAS alone is a terrible North Star and how to think in terms of incrementality, margin, and LTV How to build smarter data partnerships and clean room strategies Build vs buy: where to differentiate, where to partner, and how to keep your stack modular Where AI is actually being used today in retail and commerce media (creative, optimization, and beyond) If you work on a retail media network, commerce media network, or you buy media from them, this is a deep dive into the strategies and trade-offs that will matter over the next few years. I’m James Deaker, The Yield Doctor. I advise publishers, app developers, and ad tech companies on yield, pricing, and operations. If you’d like help applying these concepts to your business, feel free to reach out.

    39 min

  8. 12/05/2025

    Dynamic Pricing - An abused technique

    Dynamic pricing is one of the most overrated tactics in programmatic yield management—not because it doesn’t work, but because most teams try it far too early. In this video, I break down why dynamic pricing often backfires, the risks you need to understand, and the foundational yield management practices you must have in place before you even think about changing floors dynamically. We cover: What “dynamic pricing” actually means in programmatic Why it creates revenue leakage when done too early The guardrails, rate cards, deal desks, and segmentation you need first How algorithms and marketplaces can react in unexpected ways When dynamic pricing does make sense The risks of outsourcing dynamic flooring to SSPs or intermediaries Dynamic pricing can work—but only when your strategy is mature, your data is strong, and your product hierarchy is crystal clear. Otherwise, it becomes a random walk that can damage your brand, your PMPs, and your long-term revenue. If you’re facing these challenges, this is exactly the kind of work I do with clients. —James Deaker, The Yield Doctor

    6 min
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Improving Yield Management in Digital Media

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