Why don’t publishers have good pricing software anymore?

Back in 2007, Yahoo, AOL, and Microsoft used a tool called Rapt to optimize rate cards in real time. Today? That software is gone—and no one has replaced it.

In this video, I explain why Rapt disappeared, why nothing has filled the gap, and what it would take for a new solution to emerge. Drawing on my own experience working at Rapt, I break down the key challenges—including programmatic dominance, product complexity, and the lack of transparent market signals.

📈 If you're a publisher or ad tech leader grappling with pricing, yield, or programmatic strategy, this one’s for you.

⏱️ Chapters

00:00 – The 2007 Era: When Rapt Ruled

00:20 – Why I Know This: My Time at Rapt

00:47 – What Pricing Software Should Do

01:32 – How Rapt's Price Director Worked

02:16 – Microsoft Acquisition and Decline

02:23 – Why No One Replaced It: My Take

02:34 – Reason #1: Rise of Programmatic

03:25 – Reason #2: No Public Pricing Signals

04:11 – Reason #3: Ad Products Are Too Complex

05:38 – The Need for Customization (Compliance)

05:58 – Why Ad Tech Hasn’t Solved This Yet

06:16 – What the Future Might Look Like

06:35 – Closing Thoughts & Call to Comment

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📬 Need help with pricing, inventory, or programmatic strategy?

Reach out via LinkedIn or at theyielddoctor.com

#DigitalAdvertising #YieldManagement #AdTech #RateCards #JamesDeaker #TheYieldDoctor #Programmatic #PricingSoftware

There’s a lot of hype around AI in ad tech — but where is it really having an impact today?

In this episode, I speak with Nagarajan Chakravarthy, Chief Digital Officer and founding team member at iOPEX Technologies. We go deep into practical examples of AI transforming advertising revenue operations — from media planning to campaign optimization, and even creative generation.

You’ll hear:

What “Agentic AI” really means in Ad Tech

Which parts of the ad ops workflow are being automated

The biggest cultural and organizational blockers to adoption

Why AI may actually level the playing field for smaller advertisers

📧 Contact Naga: [email protected]

🌐 Learn more: https://www.iopex.com

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Timestamps:

0:00 - Introduction: Why AI in ad tech needs more real examples

1:01 - Meet Nagarajan Chakravarthy, CDO at iOPEX

2:07 - What iOPEX does and their approach to transformation

3:35 - What are “command agents” and how do they work?

3:52 - AI use cases in advertising revenue operations

6:41 - How AI accelerates creative and campaign execution

7:35 - From media plan to standardized IOs

8:02 - Speed vs. oversight: the new trade-off

10:08 - Skill shifts: From execution to prompting

11:08 - Quality control and changing error patterns

13:02 - Real-world example: AI-generated media plans

16:07 - Where AI still falls short: the EQ of creative

17:22 - Where human judgment remains indispensable

19:02 - Common misconceptions about AI in ad tech

21:31 - 4 areas where AI will be most disruptive

24:35 - Internal blockers: Skills, data, and expectation-setting

27:39 - Will AI level the playing field or boost the giants?

29:41 - Why AI is a net positive for publishers

31:38 - Final thoughts and how to connect with Naga

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More content coming soon from the front lines of ad tech and monetization.

Meta Goes All-In on AI Ads: What It Means for Advertisers & Agencies

Meta just announced plans to fully integrate AI into its advertising platform by the end of next year — enabling brands to create and target ads using artificial intelligence with little to no manual input.

In this video, I break down what this shift means for:

Facebook/Meta advertisers

Agencies whose value lies in creative and targeting

The broader digital advertising ecosystem

I’ll also share my perspective on how this move fits into the long-term trend of AI in ad tech, and why it might give Meta — and other walled gardens — an even greater advantage.

Timestamps:

0:00 – Meta’s AI Ad Announcement

0:42 – Implications for Facebook Advertisers

2:10 – How Agencies Should Respond

3:45 – Industry-Level Disruption

5:20 – My Speculation: What Meta Might Do Next

6:30 – Final Thoughts + Your Input

If you’re in ad ops, media buying, or agency strategy — this one’s for you.

Let me know in the comments: Do you think this makes Meta more effective — or more dangerous?

In this episode of The Yield Doctor, James Deaker sits down with Alanna Laforet—CEO of Laforet Productions and former head of the IAB Tech Lab—to unpack where AI is actually transforming digital advertising today, and where it's headed next.

With experience spanning DoubleClick, Google, Omnicom, and Conde Nast, Alanna brings deep insight into how AI is reshaping media planning, creative optimization, and the ad tech stack itself.

We explore:

What’s real vs. hype in current AI implementations

How startups and holding companies are approaching AI differently

Whether AI will democratize the industry or entrench the big players

The potential for AI tools like ChatGPT to act as publishers

The risks of fraud, fake content, and over-optimization in a post-AI world

Whether you're a publisher, advertiser, or just curious about the future of ad operations, this conversation is packed with insight and candid perspective.

📌 Chapters included in the description below

🔗 Connect with Alanna Laforet:

LinkedIn: [Insert Link]

Email: [email protected]

Alanna discusses the areas where GenAI will have the most impact on the AdTech ecosystem

00:00 Introduction & Guest Background

01:07 Current AI Impact in Digital Advertising

03:01 Real AI Adoption Inside Companies

04:45 Startup Frenzy & Market Fragmentation

06:00 The “Layer Cake” Problem in Ad Tech

08:13 Toward End-to-End Systems with AI Plugins

09:45 Where AI Will Have the Most (and Least) Impact

11:08 Could AI Platforms Become the Next Big Publishers?

13:36 Democratization vs. Walled Gardens

15:33 AI and the Return of Imagination

16:54 Publishers: Winners or Losers in the AI Shift?

17:38 The Ethics & Dangers of AI-Generated Content

19:53 What Excites Alanna About AI's Future

21:31 Where to Find Alanna + Closing Remarks

Alex Roucourt discusses the challenges to effective advertising measurement in a post-cookie environment and offers solutions to address these challenges

Shiv Gupta from the U of Digital breaks down the trends from the Q1 Earnings cycle in Digital Advertising and Ad Tech

A short story on the problems with setting a "sell-through" goal for a website and what should be done instead to maximize revenue through good Yield Management

Publishers struggle with when and how to run their own ads ("House Ads"). This video outlines the best approach to run House Ads for maximum efficiency

A short story about a lesson-learned in Yield Management - when increasing Price Realization was the wrong goal

Short story on Yield Management in Digital Advertising - An example of problems from running House ads in the wrong way