The Margin

MGI Research
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The Margin is a podcast from MGI Research that explores the evolving world of business monetization. Hosted by MGI Managing Directors Andrew Dailey and Igor Stenmark, the show features candid conversations with founders, CEOs, product leaders, and industry experts at the forefront of pricing, billing, and revenue operations. Each episode dives deep into the strategies, technologies, and trends shaping how companies generate, capture, and grow revenue—from subscription and usage-based models to AI-driven monetization. Whether you're in finance, product, or IT, The Margin offers practical insights to help you navigate complexity and drive growth in the digital economy.

  1. May 12

    Trust but Verify: Todd McElhatton on AI, Finance, and Systems of Record

    In this episode of The Margin, Andrew Dailey speaks with Todd McElhatton, Chief Financial and Operating Officer at Zuora, about how AI is reshaping software business models, finance operations, and the economics of SaaS. Todd explains why AI-driven usage models are putting pressure on traditional seat-based pricing, why “systems of record” require precision rather than probabilistic outcomes, and how companies are navigating the growing tension between AI innovation and profitability. Drawing on his experience at Zuora, SAP, Oracle, and VMware, Todd also shares candid insights into Zuora’s transition from public to private ownership, the operational realities of AI inside finance teams, and why speed may become the ultimate competitive advantage in enterprise software. What You’ll Learn in This Episode: Why AI and usage-based pricing are pressuring traditional SaaS business modelsHow finance teams are using AI while managing risk, accuracy, and auditabilityWhy systems of record still require deterministic outcomes instead of probabilistic AIWhat Zuora learned from transitioning from public to private ownershipHow AI-driven speed and operational efficiency could reshape software competition

    32 min

  2. Apr 28

    Pricing in Motion: Mark Walker on AI and Revenue Reinvention

    In this episode of The Margin, Andrew Dailey speaks with Mark Walker, CEO of Nue, about how AI is reshaping revenue infrastructure, pricing strategy, and the future of SaaS. Mark explains why traditional software moats are eroding, why distribution and data are becoming the new sources of defensibility, and how AI-native companies are forcing every business to operate at a faster clock speed. He shares why static seat-based pricing models are under pressure, how companies are navigating hybrid monetization models, and why flexibility in CPQ, billing, and revenue systems has become mission-critical. They also discuss the Salesforce CPQ migration opportunity, what legacy vendors are getting wrong, and why the next wave of winners will help customers adapt and grow, not just process transactions. What You’ll Learn in this Episode: Why traditional SaaS moats are weakening in the AI eraHow distribution and data are becoming the new advantagesWhy pricing is shifting beyond seat-based subscriptionsThe rise of hybrid monetization models across SaaSWhat 6,000+ Salesforce CPQ customers must decide next

    37 min

  3. Apr 14

    Speed Wins: Noel Goggin on AI and the SaaS Reset

    Episode Overview In this episode of The Margin, MGI Research Managing Director Andrew Dailey speaks with Noel Goggin, former CEO of Conga and board member at Anaplan and Auctane, to examine how artificial intelligence is fundamentally reshaping enterprise software companies. While much of the market conversation has focused on whether AI will disrupt the SaaS business model, Goggin argues that the more important challenge is organizational speed. As AI dramatically compresses product development cycles and lowers the cost of experimentation, software vendors must rethink pricing, product development, customer retention, and internal operations simultaneously. Drawing on decades of executive leadership through major technology transitions, Goggin explains why incumbent software companies possess valuable advantages, including customer relationships, domain expertise, and mission-critical data, but must overcome organizational inertia to capitalize on them. The discussion explores the growing pressure on traditional seat-based pricing, the emergence of AI-first product strategies, the importance of creating organizational capacity through internal AI adoption, and why "clock speed" may become the defining competitive advantage of the next generation of enterprise software companies. The conversation concludes with Goggin's perspective on software valuations, M&A activity, enterprise architecture, and where AI-driven transformation is likely to create the greatest long-term value. Key Analytical Takeaways The Pressure on Traditional SaaS Economics: Why seat-based licensing models are increasingly vulnerable as AI changes software utilization patterns, forcing vendors to rethink pricing, renewal strategies, and monetization before customers demand it.Clock Speed as Competitive Advantage: How AI compresses product development cycles and market experimentation, making organizational agility and cross-functional execution more important than the underlying SaaS business model itself.Creating Capacity Through Internal AI: Why successful software companies will use AI first to simplify operations, accelerate software development, improve internal workflows, and free resources that can be reinvested into innovation and growth.Balancing Innovation with Customer Retention: How established vendors must simultaneously protect renewal rates for existing products while building AI-first offerings capable of driving competitive wins and incremental revenue.The Next Phase of Enterprise Software: Why mission-critical enterprise applications remain well positioned despite AI disruption, as organizations increasingly combine packaged software with internally developed AI agents, faster development cycles, and new application architectures built around proprietary enterprise data.Featured Experts Andrew Dailey | Managing Director, MGI Research Andrew Dailey is a co-founder and managing partner of MGI Research. Andrew brings his 25+ years of diversified technology and financial services experience working in the enterprise software market and Fortune 500 firms to his clients. Noel Goggin | Former CEO, Conga Noel Goggin is an enterprise software executive and board member with decades of experience leading high-growth technology companies through periods of strategic transformation. As former CEO of Conga, he led the company's operational turnaround, product transformation, and acquisition strategy while achieving Rule of 40 performance. He currently serves on multiple technology company boards and advises organizations on AI strategy, enterprise software innovation, and executive leadership.

    50 min
  4. Monetization at Scale: John Stame on Product-Led Growth and Direct Sales

    Feb 4

    Monetization at Scale: John Stame on Product-Led Growth and Direct Sales

    In this episode of The Margin, MGI Research Managing Director Andrew Dailey speaks with John Stame, enterprise architect and former business systems leader at Atlassian, to examine the architectural realities of scaling product-led growth (PLG) businesses. While PLG promises frictionless customer acquisition and self-service monetization, many successful software companies eventually confront a new challenge: introducing direct sales, channel partners, or enterprise selling without disrupting the systems that fueled their initial growth. Drawing on more than three decades of experience designing enterprise business systems at Atlassian, Microsoft, and Chevron, Stame explains why supporting multiple sales motions requires more than adding new applications. It demands disciplined governance, careful architectural decisions, and a unified approach to quote-to-cash that balances innovation with operational consistency. The discussion explores the tradeoffs between best-of-breed and suite architectures, the growing complexity introduced by usage-based pricing, and why enterprise architecture remains a strategic capability rather than an academic exercise. Key Analytical Takeaways The PLG Expansion Challenge: Why product-led growth companies often reach an inflection point where enterprise sales, channel relationships, and high-touch customer engagement require fundamentally different business systems and commercial processes.One Business, Multiple Sales Motions: Why maintaining a single quote-to-cash architecture becomes increasingly difficult as organizations introduce CRM, CPQ, contract lifecycle management, and enterprise pricing capabilities alongside frictionless self-service commerce.Governance Without Sacrificing Innovation: How high-growth organizations can establish architectural governance around critical assets, including product catalogs, pricing, contracts, and master data, while preserving the speed and agility that define product-led businesses.Enterprise Architecture as a Strategic Discipline: Why successful organizations continuously monitor the health, scalability, and operational limits of their monetization infrastructure instead of treating enterprise systems as static implementations.The Next Evolution of Quote-to-Cash: How AI assistants, usage-based monetization, and increasingly integrated commercial platforms are likely to improve enterprise selling workflows, while leaving the underlying architectural complexity of quote-to-cash largely intact.Featured Experts Andrew Dailey | Managing Director, MGI Research Andrew Dailey is a co-founder and managing partner of MGI Research. Andrew brings his 25+ years of diversified technology and financial services experience working in the enterprise software market and Fortune 500 firms to his clients. John Stame | Enterprise Architect and Consultant John Stame is an enterprise architect and business systems advisor with more than 35 years of experience designing and scaling enterprise applications at companies including Atlassian, Microsoft, and Chevron. His expertise spans product-led growth, enterprise architecture, quote-to-cash systems, governance, and the operational design of high-growth software organizations.

    22 min
  5. Pricing in Motion: Michael Wu on AI, Data, and Demand

    Jan 26

    Pricing in Motion: Michael Wu on AI, Data, and Demand

    In this episode of The Margin, Andrew Dailey, Managing Director at MGI Research, speaks with Dr. Michael Wu, Chief AI Strategist at PROS, about what other industries can learn from decades of airline experience in dynamic pricing and revenue optimization. Dr. Wu shares insights on building trust in AI, leveraging data to drive price precision, and accelerating quote times in complex B2B environments. They also explore the shift from black-box to glass-box AI, the power of 1% pricing changes, and how CFOs can start preparing now for AI-powered pricing transformation. What you’ll learn in this episode: Why the airline industry became the blueprint for real-time pricing, yield management, and demand sensingHow AI-powered pricing enables businesses to operate dynamically in volatile markets at scaleWhy data readiness and automation are prerequisites for effective AI-driven pricing decisionsHow trust, visibility into pricing decisions, and change management determine whether AI pricing actually delivers valueWhy pricing is the fastest and most powerful lever CFOs can pull to drive margin, revenue, and competitive advantage

    26 min
  6. The Contract Intelligence Gap: Praful Saklani on Unlocking Revenue Hidden in Contracts

    Jan 8

    The Contract Intelligence Gap: Praful Saklani on Unlocking Revenue Hidden in Contracts

    Episode Overview In this episode of The Margin, MGI Research Managing Director Andrew Dailey speaks with Praful Saklani, CEO and Co-founder of Pramata, to examine why contracts remain one of the largest untapped sources of enterprise intelligence. Despite years of investment in contract lifecycle management (CLM), e-signature platforms, and digital repositories, many organizations still struggle to answer basic operational questions about customer commitments, pricing agreements, renewal opportunities, and contractual obligations because the underlying information remains fragmented across documents and disconnected systems. Drawing on decades of experience building contract intelligence platforms, Saklani explains why contracts should be viewed not as legal documents, but as strategic business assets that influence revenue growth, profitability, customer relationships, and operational execution. The discussion explores why traditional CLM implementations often fail to deliver enterprise-wide value, how generative AI is transforming the extraction and interpretation of unstructured contract data, and why successful AI adoption depends on transparency, governance, and domain expertise rather than simply deploying large language models. The conversation concludes with Saklani's perspective on AI-first enterprises, implementation transformation, and the future of contract-driven business intelligence. Key Analytical Takeaways Contracts as Enterprise Intelligence: Why customer and supplier agreements contain critical operational, financial, and commercial information that extends far beyond legal compliance and should be treated as a strategic enterprise data asset.Why Traditional CLM Falls Short: How contract lifecycle management systems often succeed at document storage and workflow automation but struggle to capture the negotiated complexity, historical context, and interconnected relationships that drive business decisions.Generative AI Beyond Document Search: Why AI delivers the greatest value when it organizes, validates, and contextualizes contract data rather than functioning as a conversational interface over isolated documents.Trust Through Transparency: How enterprise AI applications require explainability, auditability, and validation mechanisms that allow users to trace conclusions back to their contractual source material instead of relying on opaque AI-generated answers.The Next Evolution of Enterprise Applications: Why AI has the potential to dramatically reduce implementation complexity, accelerate business configuration, and enable natural language interactions with enterprise systems, provided organizations redesign application architectures rather than simply layering AI onto existing software.Featured Experts Andrew Dailey | Managing Director, MGI Research Andrew Dailey is a co-founder and managing partner of MGI Research. Andrew brings his 25+ years of diversified technology and financial services experience working in the enterprise software market and Fortune 500 firms to his clients. Praful Saklani | CEO and Co-founder, Pramata Praful Saklani is the CEO and Co-founder of Pramata, a provider of enterprise contract intelligence solutions that help organizations unlock operational and commercial value from complex customer and supplier agreements. His expertise spans contract lifecycle management, enterprise AI, legal technology, contract analytics, and the application of generative AI to unstructured enterprise data.

    27 min

  7. 12/11/2025

    The Future Is Metered: Puneet Gupta on How to Succeed with Usage-Based Models

    Episode OverviewIn this episode of The Margin, MGI Research Managing Director Andrew Dailey speaks with Puneet Gupta, Founder and CEO of Amberflo and former engineering leader at Amazon Web Services and Oracle, to examine why usage-based monetization has become a foundational capability for modern software companies. While consumption pricing is often viewed as a billing model, Gupta argues that its true value lies in enabling faster product innovation, richer customer insights, and more agile commercial strategies. Drawing on his experience building metering and billing infrastructure at AWS during its formative years, Gupta explains why successful consumption businesses begin with instrumentation rather than pricing. The discussion explores the cultural and organizational shifts required to adopt usage-based monetization, the architectural importance of metering as a system of record, and why organizations that treat monetization as strategic infrastructure, not simply a finance project, are better positioned to capitalize on AI-driven products and evolving customer expectations. The conversation concludes with Gupta's perspective on the expanding role of CIOs in building the data foundations required for the next generation of enterprise software. Key Analytical Takeaways Usage-Based Monetization as an Innovation Strategy: Why consumption pricing should be viewed as an enabler of faster product innovation, experimentation, and customer value rather than simply an alternative pricing model.Metering as the New System of Record: How modern monetization architectures depend on accurate, real-time usage instrumentation that serves as the foundation for pricing, billing, forecasting, and product analytics.Beyond Pay-As-You-Go: Why successful usage-based businesses increasingly adopt hybrid commercial models, including prepaid consumption commitments and flexible pricing structures, that combine financial predictability with operational flexibility.Monetization Requires Organizational Alignment: How product, finance, engineering, sales, and customer success must align around shared usage data and customer outcomes for consumption models to deliver their full strategic value.Building the Infrastructure for AI-Era Software: Why CIOs have an opportunity to establish enterprise-wide monetization platforms that support AI-powered products, continuous innovation, and future business models built around usage intelligence rather than static subscriptions.Featured Experts Andrew Dailey | Managing Director, MGI Research Andrew Dailey is a co-founder and managing partner of MGI Research. Andrew brings his 25+ years of diversified technology and financial services experience working in the enterprise software market and Fortune 500 firms to his clients. Puneet Gupta | Founder and CEO, Amberflo Puneet Gupta is the founder and CEO of Amberflo and a pioneer in usage-based monetization infrastructure. Prior to founding Amberflo, he helped build large-scale metering and billing systems at Amazon Web Services and Oracle, where he gained firsthand experience scaling some of the world's largest consumption-based cloud platforms. His expertise spans usage-based pricing, metering architecture, cloud infrastructure, product strategy, and enterprise monetization.

    20 min

  8. 11/24/2025

    Transforming Professional Services: Dan Brown on Pragmatic AI

    Episode Overview In this episode of The Margin, MGI Research Managing Directors Andrew Dailey and Igor Stenmark sit down with Dan Brown, Chief Product Officer at Celonis, to examine one of the most consequential questions facing professional services: Will generative AI fundamentally replace knowledge workers, or will it become another enterprise technology that augments rather than disrupts human expertise? Drawing on leadership roles at Microsoft, Certinia, and Celonis, Brown separates the operational realities of AI adoption from the surrounding hype. While generative AI is proving highly effective at automating repetitive knowledge work, summarizing complex information, and accelerating project execution, it continues to struggle with judgment, counterfactual reasoning, opinion-based analysis, and the trust required for high-value advisory engagements. The discussion also explores the practical challenges organizations face as they attempt to operationalize AI amid mounting executive pressure, fragmented technology environments, rising customer expectations, and uncertain economic conditions. Rather than treating AI as a standalone strategy, Brown advocates a "Pragmatic AI" approach centered on measurable business impact, rapid deployment, and continuous feedback loops that integrate AI directly into day-to-day operational workflows. Key Analytical Takeaways The Accelerant vs. Replacement Debate: Why generative AI is unlikely to eliminate professional services but will fundamentally reshape how knowledge workers spend their time by automating routine project execution while increasing demand for higher-value advisory work.The Human Advantage in Judgment: Where AI continues to fall short, including opinion-based consulting, scenario planning, counterfactual reasoning, negotiation, and trust-driven client relationships, and why these capabilities remain difficult to automate.Pragmatic AI Over AI Theater: How organizations can avoid expensive experimentation by prioritizing AI initiatives that deliver measurable impact, are easy to deploy, and create closed-loop operational feedback rather than disconnected productivity gains.The Enterprise Adoption Challenge: Why organizational enablement, change management, and employee education may prove more difficult than implementing the underlying AI technology itself.Professional Services as AI Enablers: How consulting and services firms may become larger, not smaller, as enterprises struggle to integrate hundreds of existing applications alongside rapidly evolving AI capabilities. Featured Experts Andrew Dailey | Managing Director, MGI Research Andrew Dailey is a co-founder and managing partner of MGI Research. Andrew brings his 25+ years of diversified technology and financial services experience working in the enterprise software market and Fortune 500 firms to his clients. Dan Brown | Chief Product Officer, Celonis Dan Brown is Chief Product Officer at Celonis and has held senior product and strategy leadership roles at Microsoft and Certinia. His work focuses on enterprise software, process intelligence, professional services automation, and the practical application of AI to improve operational performance while maintaining trust and business outcomes.

    41 min
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About

The Margin is a podcast from MGI Research that explores the evolving world of business monetization. Hosted by MGI Managing Directors Andrew Dailey and Igor Stenmark, the show features candid conversations with founders, CEOs, product leaders, and industry experts at the forefront of pricing, billing, and revenue operations. Each episode dives deep into the strategies, technologies, and trends shaping how companies generate, capture, and grow revenue—from subscription and usage-based models to AI-driven monetization. Whether you're in finance, product, or IT, The Margin offers practical insights to help you navigate complexity and drive growth in the digital economy.

Information

  • Creator
    MGI Research
  • Years Active
    2025 - 2026
  • Episodes
    16
  • Rating
    Clean
  • Copyright
    © 2025 MGI Research LLC
  • Show Website
    The Margin