Gary Bailey is the founder at The Talent Capitalist, where he teaches monetization as a discipline, and serves as a finance and monetization consultant at FinTech Strategic Advisors. 

With a background that spans from banking and derivatives pricing in the 1990s to coaching the rise of AI monetization product managers today, Gary brings a unique perspective to value capture and pricing strategy. 

In this episode, Gary shares his insights on the distinction between pricing and monetization, drawing from his experience pricing hundreds of thousands of different financial instruments to help modern AI companies think about value capture. He explores the controversial topic of contextual pricing - why companies like Google and Facebook price millions of micro-transactions differently based on context, time, and user behavior. 

Together with Mark, they dive deep into the Jobs-to-be-Done framework, debate whether it's different from problem-solution thinking, and tackle the thorny issue of when dynamic pricing crosses the line from smart segmentation to sleazy manipulation.

 

Why you have to check out today's podcast:

• Learn the difference between pricing and monetization, and why value capture is the real game-changer for sustainable business growth.
• Discover how AI companies can price thousands of different use cases without overwhelming customers or appearing manipulative.
• Understand when contextual pricing is smart segmentation versus when it becomes unethically sleazy.

 

"Hire a pricing person, and that's it really, because they're going to throw some things that you hate, throw some things that you like in the same way that you wouldn't ordinarily try and clear your drain all the time on your own. Why would you not [have] someone clear your pricing issues?"

– Gary Bailey

 

Topics Covered:

01:32 – From banking derivatives to AI: Gary's pricing journey through 100,000+ financial instruments

03:28 – Monetization vs. Pricing: Why value capture matters more than price points

06:26 – The Jobs-to-be-Done debate: Are foundational problems the same as jobs?

12:14 – The umbrella test: Distinguishing core jobs from feature-level problems

15:32 – Why SaaS companies struggle: The 10,000 use cases pricing challenge

16:48 – Google and Facebook's secret: Pricing millions of micro-transactions contextually

18:00 – The factorial complexity problem: When features create exponential pricing opportunities

21:30 – When pricing becomes sleazy: The ethics of contextual price discrimination

23:27 – Airlines and Amazon: When dynamic pricing crosses the line

25:52 – AI for strategic moats: How Gary helps founders identify key monetization metrics

29:09 – Using AI as a pricing sounding board: Context + diagrams = better insights

30:19 – Final advice: Why every company needs a pricing person

 

Key Takeaways:

"Monetization is really how much of the value that you create are you capturing, and what is the system behind you consistently capturing that value." – Gary Bailey

"Most of the companies that we know, startups that talk about generating revenue, but very few talk about value capture." – Gary Bailey

"In reality, the most optimal pricing would be to price every single one of those problems individually." – Gary Bailey

"When it gets scammy... I think in some of the healthcare stuff, the PBM stuff and some of the other things do I think, well, that's a little bit risky with healthcare and stuff, but I think people are used to it because they experience it in everyday life." – Gary Bailey

 

Resources and People Mentioned:

• The Talent Capitalist: https://www.linkedin.com/company/the-talent-capitalist/
• FinTech Strategic Advisors: https://www.ftadvisory.co.uk/
• Salesforce: https://www.salesforce.com/
• HubSpot: https://www.hubspot.com/
• Google/Facebook/Meta: Examples of companies with sophisticated contextual pricing
• Amazon: https://www.amazon.com/
• OpenAI/ChatGPT: https://openai.com/

 

Connect with Gary Bailey:

• LinkedIn: https://www.linkedin.com/in/gary-bailey-monetization-cfo/

 

Connect with Mark Stiving:

• LinkedIn: https://www.linkedin.com/in/stiving/
• Email: [email protected]