Impact Pricing

Ryan Susanna is the VP of Sales at LogiSense, where he helps telecom, IoT, and SaaS companies operationalize complex usage-based and hybrid pricing models. With more than two decades in monetization, automation, and billing infrastructure, Ryan didn't come up through pricing theory—he came up through execution. His work sits at the intersection of pricing ideas and the systems required to make those ideas real at scale.
In this episode, Ryan breaks down why billing platforms quietly shape—and sometimes constrain—pricing innovation, what usage-based pricing actually looks like in practice, why many AI pricing models default to credits, and the single pricing habit he believes every company must adopt: testing pricing ideas in isolation before scaling them across the business.
 
Why You Have to Check Out This Episode:
Understand why pricing innovation fails after approval—and how billing and monetization systems quietly block execution.
Learn which modern pricing models die first in rigid systems (usage-based, high-watermark, hybrid, credits).
Discover how to test pricing ideas safely without risking your entire go-to-market motion.
 
"Find an isolated way to test your pricing hypothesis before you boil the ocean for your entire motion." 
— Ryan Susanna
 
Topics Covered:
02:00 – From Physics to Monetization (By Accident). How Ryan's background in physics, computer science, and sales led him into billing systems—and why monetization sits closer to pricing than most teams admit.
04:00 – "Why Should Pricing Care About Billing?" Mark challenges the assumption that billing is just collecting money. Ryan explains how billing systems determine which pricing models are even possible.
07:00 – High-Watermark Pricing Explained. Charging based on peak concurrent usage—not total usage—and why this better reflects customer value in many SaaS and telco models.
08:30 – Earned Discounts and Hybrid Usage Models. How companies combine multiple usage metrics to guide behavior while protecting margins.
14:00 – Meter Everything (Even If You Don't Charge for It). Ryan explains why future pricing decisions depend on historical usage data you may not even know you need yet.
19:00 – Credits vs. Value-Based Pricing. Mark reframes credits as a payment mechanism—not a pricing model—and explains why value correlation matters.
23:00 – The Pricing Test Most Companies Skip. Why executives roll out pricing changes globally—and how isolated testing could prevent costly mistakes.
25:00 – Final Advice for Pricing Leaders. Ryan's core message: pricing strategy without monetization readiness is just theory.
 
Key Takeaways:
"You could dream up any pricing scenario if you want, but if you can't operationalize it at scale, you are setting yourself up for failure." – Ryan Susanna
"Billing systems quietly decide which pricing models you're allowed to use." – Ryan Susanna
"If you pick a model and you have the same model forever, then it will not appear hard for you—because it's what you've always done. What's hard is change." – Ryan Susanna
 
People / Resources Mentioned:
LogiSense – Monetization and billing platform enabling complex usage-based pricing
OpenAI – Referenced in the context of AI credit-based pricing models
Databricks – Example of proprietary credit-based pricing (DBUs)
Slack – Example of active-user pricing metrics
 
Connect with Ryan Susanna:
Email: [email protected]
LinkedIn: https://www.linkedin.com/in/ryansusanna/
 
Connect with Mark Stiving:
LinkedIn: https://www.linkedin.com/in/stiving
Email: [email protected]

This is an Impact Pricing Blog published on November 10, 2025, turned into an audio podcast so you can listen on the go.
Read Full Article Here: https://impactpricing.com/blog/designing-hybrid-and-evolving-pricing-models-for-ai/
If you have any feedback, definitely send it. You can reach us at [email protected]. 
Now, go make an impact.
 
Connect with Mark Stiving:
Email: [email protected]
LinkedIn: https://www.linkedin.com/in/stiving/

Mike Wilkinson, founder of Axia Value Solutions, joins Mark Stiving to explore how AI is fundamentally changing buying behavior—and why this shift exposes weak value stories more than it threatens good sellers.
In this episode, Mike explains how AI has raised buyer expectations by enabling benchmarking, price testing, and faster comparisons—rewarding sellers who clearly communicate value and exposing those who don't. He and Mark show why AI creates mediocrity when used blindly, and why value clarity—not pricing tricks—determines who wins.
 
Why You Have to Check Out This Episode:
Understand how AI is changing buyer expectations—and why buyers now demand clearer value justification before accepting price.
Learn where AI helps sales—and where it hurts—including why copying AI outputs creates "AI mediocrity" instead of differentiation.
Discover how value clarity and value literacy become your competitive moat in an AI-saturated selling environment.
 
"Whatever price you're charging or thinking of charging, make sure that it's supported by the value that you are communicating that you can deliver." 
– Mike Wilkinson
 
Topics Covered:
02:17 – AI Is Changing How Buyers Buy. Buyers now show up informed with comparisons and benchmarks, shifting the focus from persuasion to value justification.
06:00 – How Buyers Use AI When Making Decisions. Why price-focused questions produce very different answers than value-focused ones.
09:08 – Using AI to Support Value Selling. Where AI helps sellers think through value—and where copying AI outputs makes everyone sound the same.
11:32 – The Real Problem: Most Salespeople Don't Understand Value. Why unclear definitions of value break value-based selling, with or without AI.
17:23 – AI as a Sales Assistant, Not a Replacement. How AI supports preparation and thinking, but can't replace real customer conversations.
19:25 – Practical Ways Salespeople Should Use AI. What actually helps sellers win—from research to prep—and what's just busywork.
22:55 – Researching Customers with AI Before the Call. How to use AI to understand the company, the market, and the buyer before the meeting.
27:17 – Pricing Advice: Value Has to Justify Price. Why prices fall apart when sellers can't clearly explain why they're worth it.
 
Key Takeaways:
"The people who truly understand and communicate value are the people who will rise above that mediocrity." – Mike Wilkinson
"For me, the question in the customer's mind is: if you're more expensive than a competitor, why should I make that additional investment? What do I get back in return? And if the answer is, 'I haven't a clue,' prepare to discount. If you've got some great reasons why you're worth more than competing alternatives, then you're into the conversation." – Mike Wilkinson
 
People & Resources Mentioned:
Axia Value Solutions – Mike Wilkinson's consultancy focused on value-based selling and commercial excellence.
Value-Based Selling – A sales approach centered on discovering, quantifying, and communicating customer-specific value rather than competing on price.
AI in Sales Enablement – Used for research, preparation, and idea generation—not as a substitute for human judgment or relationship-building.
Mentioned LinkedIn article in the episode: https://www.linkedin.com/pulse/future-selling-ai-world-michael-wilkinson-5brme/ 
 
Connect with Mike Wilkinson:
Website: https://axiavalue.com/
LinkedIn: https://www.linkedin.com/in/mikewilkinson-thevalueexpert/
Email: [email protected]
 
Connect with Mark Stiving:
LinkedIn: https://www.linkedin.com/in/stiving
Email: [email protected]

This is an Impact Pricing Blog published on November 3, 2025, turned into an audio podcast so you can listen on the go.
Read Full Article Here: https://impactpricing.com/blog/pricing-ai-evaluating-pricing-metrics/
If you have any feedback, definitely send it. You can reach us at [email protected]. 
Now, go make an impact.
 
Connect with Mark Stiving:
Email: [email protected]
LinkedIn: https://www.linkedin.com/in/stiving/

Steven Forth, Managing Partner at Ibbaka and co-creator of Value IQ, joins Mark Stiving to tackle a topic most pricing teams are avoiding: pricing governance in an AI-driven world.
This episode explores who owns pricing decisions when AI is involved, how companies should govern data and models, and why pricing leaders must step into a broader leadership role or risk having governance imposed on them by others. 
If AI is touching your pricing process in any way, this conversation will change how you think about responsibility, risk, and trust.
 
Why You Have to Check Out This Episode:
Understand what pricing governance actually means and why poor governance shows up as finger-pointing between sales, pricing, and finance.
Learn the new governance questions AI introduces around data usage, bias, accountability, and mistakes.
Discover why pricing leaders must own AI governance or risk losing control of pricing decisions altogether.
 
"The big issue for me is how, as pricing people, do we develop the knowledge that we need to be accountable for AI pricing governance? It's not something any of us were taught."
– Steven Forth
 
Topics Covered:
01:51 - Pricing Governance and Accountability. What pricing governance really means and why accountability breaks down when roles are unclear.
05:04 - Pricing and Customer Value Alignment. Why pricing teams sit at the center of aligning sales, product, finance, and customer value.
08:01 - AI Challenges in Pricing Governance. How AI introduces new risks around data usage, ownership, and responsibility in pricing decisions.
12:45 - AI Pricing Governance Challenges. Who is accountable when AI makes mistakes and how strict rules can slow innovation.
16:35 - AI Governance in Pricing. Why pricing leaders must take ownership of AI governance or risk losing control to other functions.
22:13 - AI Transparency in Pricing. The importance of explainable pricing models and why transparency matters to both sellers and buyers.
26:49 - AI in the Buying Process. How buyers are using AI to evaluate vendors and why transparency will shape future pricing outcomes.
28:08 - Connecting on LinkedIn. How to continue the conversation and connect with Steven Forth directly.
 
Key Takeaways:
"Governance is an area of pricing that we don't spend enough time thinking about and talking about because it's not sexy and it does not immediately tie to results." – Steven Forth
"If pricing leaders don't take ownership of AI governance, someone else will." – Steven Forth
"It's the fact that the AIs are not deterministic that allows them to be, dare I say it, creative and to find new things." – Steven Forth
"AI generally does a better job of explaining how it got to its answers than most humans can." – Steven Forth
 
People & Resources Mentioned:
Tom Nagle – Referenced as Steven's mentor and a foundational thinker in pricing governance 
Michael Mansard – Mentioned for prior work and thinking on pricing governance
Tim Smith – Referenced for contributions to pricing governance discussions
Karen Chiang - Co-founder of Ibbaka
Stephan Liozu – Mentioned for advocating the Chief Value Officer role
Anthropic – Research on bias and AI self-evaluation
OpenAI – Data usage and model governance considerations
Deal Desks – Scaling pricing guidance with AI support
 
Connect with Steven Forth:
LinkedIn: https://www.linkedin.com/in/stevenforth/ 
Email: [email protected]
 
Connect with Mark Stiving:
LinkedIn: https://www.linkedin.com/in/stiving
Email: [email protected]