The Yield Doctor with James Deaker

There are areas where you need to careful of using AI to help in Pricing and Yield in Digital Advertising. It will give you an answer, but without the right oversight that answer may hurt your business.⏱️ Timestamps[00:00] - Appropriate Use Cases for AI in Pricing[01:55] - Trap #1: Algorithmic Competitor Price Setting & Collusion Risk[03:35] - Trap #2: Relying on AI for Real Pricing & Product Innovation[06:18] - Trap #3: Designing Pricing Before Defining Your Objective Function[08:41] - Key Takeaway: Executing Strategy vs. Defining Strategy💡 Key TakeawaysWhere AI Belongs: Executing clear internal policies, enforcing deal approval thresholds, and accelerating analytics.Algorithmic Collusion: Why allowing AI agents to continuously monitor and react to competitor pricing creates unintended legal and operational gray areas.Innovation Bottlenecks: Why AI adapts existing models (CPMs, sponsorships) well, but human insight is needed for breakthrough models like Uber's "Cost Per Ride" (CPR).The Objective Function: Why asking AI to optimize pricing before management explicitly defines what success looks like yields great answers to the wrong questions.📌 About The Yield DoctorHosted by James Deaker (The Yield Doctor), this channel delivers practical yield frameworks, ad tech strategy, and AI governance insights for media and digital advertising executives.🔔 Subscribe for practical yield strategy & AI risk controls🌐 Connect & DiscussionAre you seeing companies hand over pricing decisions to AI that they shouldn't? Let us know in the comments!

Every year, the digital advertising industry gets outraged over the "AdTech tax"—the famous gap between what an advertiser spends and what a publisher actually receives. But are intermediaries actually stealing your gold, or are they providing a service you forgot you needed?In this video, I use a classic riddle about three pirates, an inkeeper, and a sneaky bellhop to break down the complexities of Supply Path Optimization (SPO).What you’ll learn:The mathematical misdirection behind the "missing dollar" problem.How to classify the ad tech value chain (Valet vs. Thief).Why cutting out the "bellhop" might mean you have to carry your own bags (and manage your own fraud, identity, and measurement!).The 3-step discipline every advertiser and publisher needs to master before getting outraged.If you want to stop guessing where your digital media spend is going, the formula is simple: Trace the dollar, classify the dollar, and decide if it was well spent.[00:00] The "Missing Dollar" Problem in AdTech[00:38] The Riddle of the Three Pirates[01:54] The Mathematical Misdirection Revealed[02:22] Mapping the Riddle to Advertisers, Publishers, and DSPs/SSPs[04:00] The Lumiscape Reality: Valets, Housekeepers, and Bartenders[05:58] The Hard Question: Does the Service Justify the Fee?[08:20] The Complexity of AdTech Currencies (CPM vs. Rev Share)[09:40] My Advice for Programmatic Buyers and Sellers[10:40] The Real Cost of "Carrying Your Own Bags" (Going Direct)[11:34] Summary: Trace, Classify, and Decide

Are you micro-tweaking your digital advertising rates every time market demand ripples? It’s time to stop.When sales demand softens, executive teams often panic and treat pricing as the only quick fix. But changing core rate structures out of panic usually creates operational chaos rather than real revenue.In this video, we break down three common digital media pricing traps you can eliminate immediately to simplify your ad operations, empower your sales team, and give your advertisers a predictable sense of value.What You’ll Learn:Why treating sell-through rates as a pricing trigger turns into a dog-chasing-its-tail scenario.The academic trap of over-modeling cross-elasticity in a fast-moving digital ad landscape.The hidden operational friction costs of rolling out minor rate card adjustments to direct sales teams.The crucial structural boundary between human-led rate cards and dynamic programmatic floors."Good pricing is not about constantly changing prices. It is about knowing when a price change is justified, making it clearly, and giving the market a predictable sense of value."💬 Join the Conversation: How does your team manage the balancing act between stable direct rate cards and automated programmatic floors? Drop a comment below—I’d love to hear your approach.

Predicting digital ad inventory shouldn't feel like guessing the future. In this video, we break down the key concepts of inventory forecasting and give you simple, actionable strategies to dramatically improve your accuracy without getting bogged down in unnecessary complexity.Whether you’re navigating the shift away from traditional search to agentic AI traffic, managing multi-tier publisher portfolios, or just trying to stop leaving millions of dollars on the table, this guide is built for digital media operators who want results.What you’ll learn in this video:0:00 - The Real Cost of Bad Inventory Forecasts1:30 - Finding the Right Level of Detail (Stop Wasting Time)3:15 - Accounting for Trends: The New Reality of Traffic5:00 - Why You Need a "Human in the Loop" (AI vs. Human)7:15 - 5 Simple Rules to Build a Smarter ForecastIf you want to maximize your ad layout potential, avoid the asymmetric risks of over-forecasting, and scale your digital yield confidently, hit that subscribe button!

AI is rapidly reshaping digital advertising — but the biggest risk may not be what most people are talking about.In this presentation from Programmatic.AI in Las Vegas, James Deaker (“The Yield Doctor”) argues that the real challenge is not AI-generated creatives or job replacement. It’s what happens when autonomous systems begin making pricing, targeting, optimization, and commercial decisions without clear ownership, governance, or accountability.As AI systems increasingly influence revenue, inventory allocation, campaign optimization, and audience targeting, digital advertising companies need something many organizations still lack: a formal Control Layer.This session explores:• Why AI changes the risk profile of digital advertising• The difference between automation and autonomous decision-making• Why governance cannot simply sit inside IT• The growing importance of configuration authority, oversight, and reversibility• How AI can reduce small operational mistakes while increasing systemic tail risk• Why cutting oversight teams to fund AI may be dangerous• Practical frameworks for publishers, ad tech companies, and media organizationsThe presentation also discusses real-world examples, asymmetric risk, the MediaMath collapse, and why experienced operators may become more valuable — not less — in an AI-driven industry.I’m James Deaker. I’m The Yield Doctor. I work with clients on issues like these to help them make more money from their digital assets.#AI #Advertising #AdTech #Programmatic #DigitalAdvertising #YieldManagement #RetailMedia #AIGovernance #ProgrammaticAI

The creator economy is booming — but most creators still struggle to build durable businesses.In this episode, Monica Khan (Founder & CEO of Creator Revolution, former YouTube and Meta executive) joins The Yield Doctor to discuss:how creators actually make money in 2026,why YouTube still dominates creator monetization,the rise of micro-influencers,platform strategy,newsletters and audience ownership,and why follower count matters less than most people think.We also discuss the growing tension between creators, platforms, and brands — and what creators need to do to build sustainable long-term businesses.

DescriptionMost media companies think a rate card is just a price list.That’s wrong—and it’s one of the main reasons they quietly leak revenue.In this video, I break down how rate cards actually work, why structure matters more than pricing, and how the best operators use rate cards to shape demand—not just respond to it.We cover:Why “price list thinking” leads to revenue leakageThe correct sequence for building a rate card (segmentation → pricing model → price)Why rate cards need to be updated regularlyHow internal pricing (target + floor) should support your external rate cardA simple checklist to evaluate whether your rate card is actually workingIf you work in digital media, ad tech, or retail media, this is one of the most important commercial frameworks to get right.Connect / More ContentI write regularly about pricing, yield management, and digital media economics in The Yield Doctor.👉 Subscribe / follow for more frameworks like this.https://korukeamedia.com/newsletter/

Is your Retail Media Network actually generating new revenue, or just shifting trade spend around? In this episode, James Deaker (The Yield Doctor) sits down with retail media expert Kiri Masters to diagnose the "Retail Media Doom Loop" and uncover the blueprint for building a high-margin commerce media business.Whether you're a mid-sized retailer or a major network, we dive into the structural shifts required to move beyond basic ad units and start capturing real, incremental yield.In this video, you’ll learn:The critical difference between Retail Media and Commerce Media.Why reclassifying trade spend is a "short-term win, long-term fail."How smaller networks can compete (and win) against the giants.The specific "Yield Doctor" diagnosis for maximizing digital asset value.

What is dCPM—and why does it confuse so many people in digital advertising?In this video, I break down what dCPM (dynamic CPM) actually means, how it evolved from the ad network era to modern programmatic platforms, and why it’s still widely misunderstood today.We’ll cover:The difference between fixed CPM and dynamic CPMHow auction-based pricing works in practiceWhy platforms like The Trade Desk, Google, and Meta use different terminologyThe key tradeoff: efficiency vs predictabilityAnd most importantly… who controls pricing and who takes the riskIf you work in digital media, ad tech, or yield management, understanding dCPM is critical—not just as a pricing concept, but as a framework for how decisions are made in modern advertising systems.Key takeaway:dCPM isn’t a standardized industry term—it’s a concept that shifts control, risk, and pricing decisions in ways that aren’t always obvious.I’m James Deaker, The Yield Doctor.I work with clients on issues like these to help them make more money from their digital assets.

Most sales compensation plans are designed to drive revenue.But what if they’re quietly destroying profit?In this video, I break down a common but overlooked problem: the misalignment between sales incentives and business economics. When comp plans reward the wrong behavior, you don’t just get suboptimal outcomes—you get systematic leakage.We’ll walk through:Why revenue ≠ profit (and where the gap comes from)How common compensation structures create unintended consequencesReal examples of behaviors that look good on paper but hurt the businessWhat better alignment actually looks like in practiceThis isn’t about blaming Sales—it’s about designing systems that drive the right outcomes.If you’re responsible for pricing, deal structure, or revenue strategy, this is a problem you need to understand.We discuss:Sales incentives vs. business objectivesRevenue vs. margin tradeoffsDeal structuring and discount behaviorCompensation design pitfallsAligning incentives with long-term valueI’m James Deaker. I’m The Yield Doctor. I work with my clients on issues like these to help them make more money from their digital assets.----Related Video on aligning Sales Comp with Profit:https://youtu.be/WOAkrqT24qQ