Impact Pricing

#CLASSIC Why I Teach Pricing: My Journey and Mission

Whether you've been with us since the beginning or you just discovered Impact Pricing last week, this episode is for you. If you're one of our longtime listeners, you know Mark's voice, you've heard his insights, and maybe you've even implemented some of his strategies in your own business. But have you ever wondered what drives him to keep showing up week after week, year after year? If you're new here, welcome. You're about to meet the person behind the podcast—not just as a pricing expert, but as someone who genuinely loves teaching and believes that understanding value can transform your business and your career. Mark Stiving is the host of Impact Pricing and founder of Impact Pricing LLC. But before he was a pricing expert, he was a teacher—of scuba diving, kayaking, and marketing. That passion for helping people learn never left him. Even after retiring in 2019, Mark couldn't stop sharing what he knows about pricing and value. In this heartfelt solo episode, Mark pulls back the curtain on his journey. He shares why he chose to dedicate his post-retirement life to pricing education, what keeps him energized after blogging every week since 2010, and the two critical topics that consume his attention right now. This isn't just another pricing lesson—it's an invitation to understand the "why" behind everything we do here at Impact Pricing. For our loyal listeners: Thank you for being part of this community. This episode is Mark's way of reconnecting with you and reaffirming his commitment to your success. For our new listeners: This is the perfect place to start. You'll understand not just what we teach, but why it matters so deeply to the person teaching it.   Why you have to check out today's podcast: Discover why teaching and sharing pricing knowledge became Mark's post-retirement mission and driving passion. Learn about the two critical topics dominating modern pricing strategy: AI pricing and context-driven pricing. Understand how value impacts decisions across sales, marketing, product development, and packaging—not just pricing.   "Probably my single most favorite thing is when I share something with someone and it has an impact on their life. I absolutely love that." - Mark Stiving   Topics Covered: 00:30 - Mark's Retirement and Continued Mission. Why Mark retired in 2019 but couldn't stop sharing pricing knowledge, and how his blogging streak since 2010 kept him connected to his passion. 01:15 - The Joy of Teaching. Mark's history as an instructor across multiple disciplines—from scuba diving and kayaking to university-level marketing—and why teaching is his core passion. 02:00 - The Pricing Knowledge Gap. Why pricing and value are critical business topics that remain poorly understood, and Mark's mission to change that. 02:45 - Working with Different Organizations. How Mark's work differs between large enterprises (focusing on sales teams) versus small and mid-sized businesses (focusing on executive teams). 03:30 - Two Current Focus Areas. Deep dive into Mark's concentration on AI pricing and context-driven pricing, including the concept of value architecture. 04:45 - Context-Driven Pricing Framework. How buying contexts differ for every purchase and how companies can structure their product portfolios to deliver and capture more value.   Key Takeaways: "Pricing and value are such important topics in all of business and so few people understand it. And that's almost my mission now is just to see how many people I can get to have a better understanding." - Mark Stiving "All buying is contextual. Every purchase that's made is made in a different way than any other purchase has ever been made." - Mark Stiving "When we start thinking through context-driven pricing, that drives me to something I call a value architecture, which is how do you structure the way you think, the way you built your product portfolio, the way you have packaged your greatest features?" - Mark Stiving   Resources Mentioned: Impact Pricing Blog (since 2010): https://impactpricing.com/blog/ Mark's Substack newsletter Impact Pricing monthly newsletter   Connect with Mark Stiving: LinkedIn: https://www.linkedin.com/in/stiving/ Email: mark@impactpricing.com Website: https://impactpricing.com  

Blogcast: Pricing AI: Three Levels of Value Visibility

This is an Impact Pricing Blog published on December 15, 2025, turned into an audio podcast so you can listen on the go. Read Full Article Here: https://impactpricing.com/blog/pricing-ai-three-levels-of-value-visibility/ If you have any feedback, definitely send it. You can reach us at mark@impactpricing.com.  Now, go make an impact.   Connect with Mark Stiving: Email: mark@impactpricing.com LinkedIn: https://www.linkedin.com/in/stiving/

Synthetic Data in Pricing: Trust It, Test It, or Ignore It? with Steven Forth

Steven Forth is a pricing strategist and AI innovator with decades of experience building value-based pricing models.  As the founder of Value IQ, he blends rigorous pricing theory with emerging AI applications—often pushing the boundaries of how pricing professionals think about data, modeling, and buyer behavior. In this episode, Mark and Steven step into another live debate aka 'intellectual challenge' about AI-generated synthetic data  with real pushback, not polite agreement. They challenge whether synthetic data is a breakthrough for pricing or just smarter-looking "fake data" that distances us from buyers. What unfolds is an unscripted stress test of the idea itself, and it ends with a surprisingly human conclusion you should definitely listen to.   What You'll Learn in This Episode: What synthetic data actually is—and how it differs from simply "making up numbers." Where synthetic data becomes dangerous, especially when assumptions about buyer behavior go untested. Why even the most advanced AI modeling cannot replace direct conversations with buyers.   "Go out and talk to buyers and understand their buying process." – Steven Forth   Topics Covered: 00:00 – Why synthetic data is suddenly a pricing topic. Steven introduces Value IQ and the idea behind AI-generated pricing intelligence. The setup: why synthetic data is gaining attention—and why Mark is skeptical from the start. 03:45 – What is synthetic data (without the buzzwords)? A plain-language definition of synthetic data and how it differs from CRM or ERP history. Why backward-looking data limits pricing strategy. 06:30 – The "fake data" objection. Mark challenges the idea head-on: Isn't this just inventing numbers? A sharp exchange on statistical misuse, p-values, and the danger of generating data that simply confirms what you want to see. 09:30 – Interpolation vs. extrapolation in pricing models. Why most pricing data isn't normally distributed. Discussion of fat tails, clustering, segmentation signals, and what synthetic data might distort—or reveal. 12:30 – The three types of synthetic data. Steven outlines three practical applications. (1) AI-generated buyer simulations. (2) Stress-testing value and pricing models. (3) Modeling competitive and economic scenarios. This is where the conversation moves from theory to use cases. 16:30 – Can AI predict buyer behavior? Mark pushes the core issue: pricing changes behavior. So how can synthetic data anticipate it? A discussion about assumptions, validation, and ground truth. 20:00 – A practical example: AI-driven Van Westendorp studies. A concrete scenario: simulate 100 real buyers, test pricing sensitivity, validate with actual survey data, and refine the model. A tangible way to experiment responsibly. 23:30 – The risk: Are we moving further from real buyers? The philosophical tension of the episode. Does synthetic data create insight—or another buffer between pricing teams and customers? 26:30 – The surprisingly human conclusion. After 25 minutes of AI debate, Steven's final advice is simple and grounded: talk to buyers and understand their buying process. 29:00 – Closing thoughts and where to connect. How to reach Steven and Mark—and a final reminder that AI is a tool, not a substitute for customer insight.   Key Takeaway: "Synthetic data is data that is generated for you by your AI." – Steven Forth "With synthetic data, you can explore scenarios that do not yet exist or parts of the market you do not yet touch." – Steven Forth   People and Resources Mentioned: Craig Zawada – Former McKinsey partner, co-creator of the pocket price waterfall; now Chief Strategy Officer at PROS  Benoit Mandelbrot – Referenced in the discussion about fat-tailed distributions and why pricing data is often not normally distributed. Pocket Price Waterfall – A pricing analytics framework originally developed at McKinsey. Van Westendorp Price Sensitivity Meter – Used as a practical example of how synthetic data could simulate buyer responses. Conjoint Analysis – Discussed as a potential future application for synthetic respondents. Bayesian Updating / Bayesian Statistics – Mentioned as a way to iteratively improve models by aligning synthetic data with real-world results. Interpolation vs. Extrapolation – Statistical concepts debated in the context of synthetic modeling. Normal vs. Fat-Tailed Distributions – Discussion on why pricing data often violates normal distribution assumptions.   Connect with Steven Forth: LinkedIn: https://www.linkedin.com/in/stevenforth/  Email: steven@valueiq.ai Subscribe to Steven's Substack: Synthetic data in pricing: https://pricinginnovation.substack.com/p/synthetic-data-in-pricing   Connect with Mark Stiving: LinkedIn: https://www.linkedin.com/in/stiving/ Email: mark@impactpricing.com  

Blogcast: AI Can't Own Pricing

This is an Impact Pricing Blog published on December 8, 2025, turned into an audio podcast so you can listen on the go. Read Full Article Here: https://impactpricing.com/blog/ai-cant-own-pricing/ If you have any feedback, definitely send it. You can reach us at mark@impactpricing.com.  Now, go make an impact.   Connect with Mark Stiving: Email: mark@impactpricing.com LinkedIn: https://www.linkedin.com/in/stiving/  

From $500 to $20,000 a Month: What This Pricing Jump Reveals About Value with Alex Shartsis

Alex Shartsis is a pricing and go-to-market advisor who helps founders charge what their products are actually worth. He is the CEO of Silverwood and Skyp, working with early- and growth-stage companies on pricing discipline, packaging, and monetization. This episode explores why charging too little early is one of the most expensive mistakes founders make, including the story of raising a customer from $500 a month to $20,000. Mark and Alex discuss when to raise prices, how early sweetheart deals quietly damage businesses, and why price often signals quality in AI and SaaS markets.   Why You Have to Check Out This Episode: Understand why early underpricing creates long-term trauma in customer bases, teams, and investor conversations. Learn when to raise prices (and when not to) especially with early customers and pilots. See why price often acts as a signal of quality in markets where buyers can't easily judge value (AI, software, experimentation budgets).   "If you can charge for value early and be disciplined about it, you'll have a much better journey—you'll look better to investors, and you'll be running a more viable business much sooner." — Alex Shartsis   Topics Covered: 02:00 – From $500 to $20,000: A Pricing Wake-Up Cal. Alex shares the deal that pulled him into pricing—and why willingness to pay is often far higher than founders expect. 06:10 – Founder Discounts and Early Pricing Mistakes. How "sweetheart deals" happen, why they feel harmless early on, and how they quietly break pricing discipline. 10:45 – Should You Raise Prices on Early Customers?A nuanced discussion on fairness, trust, investor expectations, and when price increases actually make sense. 15:30 – Building NRR Into Pricing (Without Repricing Customers). Why limits, packaging, and expansion paths matter more than simply charging more later. 18:45 – AI Changes the Cost and Pricing Equation. Why the old "software has no marginal cost" mindset no longer holds in AI-driven businesses. 22:30 – Price as a Signal of Quality. When buyers use price to infer value—and why this shows up strongly in AI and experimental products. 26:15 – Credit-Based Pricing: Temporary Fix or Long-Term Problem?. A candid debate on credits, customer confusion, and what it signals about unresolved value models. 29:10 – Final Advice: Charge for Value Earlier. Alex's closing guidance for founders—and why pricing discipline creates better businesses, not just higher revenue.   Key Takeaways: "If you can charge for value early and be disciplined about it, you'll have a much better journey—you'll look better to investors and you'll be running a more viable business sooner." — Alex Shartsis "Most early-stage founders charge too little, and it quietly creates problems that don't show up until much later." — Alex Shartsis "Price often becomes a signal of quality when buyers can't easily judge value—especially in AI and software." — Alex Shartsis   People & Resources Mentioned: Carta – Carta's ERP for private capital combines software and services to deliver connected clarity and control across equity, fund, and portfolio management. Google Maps – Example of usage-based pricing evolution Tesla – Used as an example of starting high and expanding market access over time Porsche – is referenced as a real-world analogy for how premium pricing shapes belief, not because Porsche has radically different parts, but because the brand and price tell a story buyers trust.excellence. Kyle Poyar -  is referenced in the context of "reasonable use" pricing. Steven Forth - comes up during the discussion on credit-based pricing models, especially in AI-driven products.   Connect with Alex Shartsis: LinkedIn: https://www.linkedin.com/in/shartsis/ Skyp: https://skyp.ai Silverwood: https://silverwood.ai   Connect with Mark Stiving: LinkedIn: https://www.linkedin.com/in/stiving/ Email: mark@impactpricing.com