How should product leaders rethink pricing in an AI-driven world where value, speed, and automation are constantly shifting? In this podcast hosted by EY Platform Operations Lead Justin Leibow, Decision Alpha CEO Etinosa Agbonlahor speaks on behavioral economics and the future of pricing in the AI era. She explores how companies can move beyond cost-plus models, design pricing as a strategic feature, and adapt monetization strategies as AI reshapes outcomes, efficiency, and customer expectations.
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Show Notes
- Pricing should be treated as a product feature, continuously refined, not as a one-time financial decision.
- Cost is only step zero in pricing; anchoring too heavily to build cost leads to fragile pricing strategies.
- Customers typically perceive more value than founders assume, which creates room for confident pricing.
- Willingness-to-pay research is critical to understanding what customers truly value and what they would pay for specific features.
- Competitor pricing should inform awareness, not dictate strategy—others may have mispriced their own value.
- Macroeconomic shifts expose weaknesses in cost-plus pricing models.
- Pricing conversations should happen at least quarterly to align with newly delivered value.
- Tracking delivered value over time makes renewals and price increase discussions far easier.
- Super users rarely stay solely because of price; they stay because of differentiated value.
- Customers are often less price-aware than companies fear, reducing the risk of thoughtful price adjustments.
- Founder fear frequently suppresses pricing potential more than market resistance does.
- Running pricing simulations helps leadership see margin impact beyond emotional assumptions.
- Value growth does not require exponential price growth; segmentation and product evolution create balance.
- As products mature, companies should consider graduating users into differentiated tiers or models.
- AI is pressuring traditional pricing structures, especially hourly billing in professional services.
- Outcome-based, hybrid, or subscription pricing models may better align with AI-driven efficiencies.
- AI can expand market access by lowering delivery costs and enabling new pricing flexibility.
- Reference points matter—positioning AI relative to what it replaces (e.g., a full-time analyst) shapes perceived value.
- Cultural differences influence pricing psychology: fairness in Australia, authority in the UK, speed in the US, and guarantees in emerging markets.
- The future of pricing may standardize around new reference models—AI “employees,” usage credits, or token-based systems—but value perception will remain central.
About the speaker
Etinosa Agbonlahor is a behavioral economist and CEO of Decision Alpha, a behavioral pricing firm that helps businesses improve pricing for growth, traction, and stronger perceived value. Passionate about helping people live healthier financial lives, she brings over a decade of experience working across the U.S., Australia, Africa, and the U.K.—shaping pricing, engagement, and customer behavior strategy for global financial institutions and venture-backed startups. Her work has been featured in MarketWatch, Morningstar, and other leading platforms, highlighting her focus on how behavior drives financial outcomes. Etinosa is the author of How to Talk to Your Parents About Money, a guide to navigating complex financial conversations.
About the host
Certified Digital Product Manager (CDPM), Certified Project Manager Professional (PMP) and ScrumMaster (CSP) Specialties: Product Development, Product Management, Insurance, Banking, Financial Transformation, Process Improvement, Business Risk