Pricing strategy in B2B is often driven by reactive discounting, arbitrary price increases, and sales negotiation pressure rather than value-based pricing. Pascal Yammine, CEO of Zilliant and former GM of Salesforce Revenue Cloud, joins Cory Cotten-Potter to reveal how you can transition from fear-driven negotiation to a data-backed B2B pricing model that secures margins.
Learn how sales alignment affects pricing outcomes, how AI-driven optimization helps organizations make smarter decisions across markets, and why pricing optimization requires total alignment between sales, finance, and marketing to drive long-term revenue growth.
Most B2B organizations don’t actually have a pricing strategy. What they have is a collection of habits: annual price increases, end-of-quarter discounts, and sales-led negotiation tactics that evolve over time. These behaviors are rarely coordinated across departments, and the result is inconsistent margins, confused buyers, and reactive decision-making.
According to Pascal Yammine, pricing problems are usually alignment problems. Pricing touches sales, finance, marketing, product, and operations. When each function has a different objective, the pricing model becomes fragmented. Sales teams discount out of fear of losing deals. Finance pushes for margin targets. Marketing protects brand positioning. Without a unified strategy, pricing becomes reactive rather than strategic.
One of the most common examples of this behavior is the annual 9–10% price increase. Many companies treat this number as standard practice, but buyers recognize it as arbitrary and negotiable. Instead of reinforcing value, it signals that pricing is flexible and driven by internal pressures rather than customer outcomes.
Strategic pricing works differently. It starts with segmentation. Instead of applying the same logic across all markets and customers, organizations decide where to prioritize growth and where to protect margin. A company may accept lower margins in a strategic market to gain share while maximizing margins in mature segments.
Value-based pricing becomes the anchor of this strategy. Rather than applying percentage increases across the board, companies ask a more important question: are we still creating enough value for this customer? When value is clear and understood, arbitrary increases become irrelevant.
Data and AI now play a central role in enabling this shift. Modern pricing systems combine transactional data, market conditions, competitive intelligence, and supply-chain variables to generate recommendations. However, technology alone does not solve pricing problems. The real challenge is building trust across teams and aligning on commercial goals.
Organizations that succeed with pricing transformation typically start small. Instead of rolling out a new pricing model across the entire company, they begin with one region, one business unit, or one product line. Once leaders see measurable improvements in margin or growth, adoption spreads organically. Other teams ask for the capability rather than resisting it.
Over the next five years, pricing will likely move from AI-assisted insights to automated pricing actions. As organizations build trust in AI recommendations, pricing decisions will increasingly shift from manual analysis to real-time, automated adjustments based on market signals.
Learn more about Pascal Yammine:
Key Quotes:
- "Pricing is used in a reactive way as opposed to a proactive and a strategic way."
- "If I'm trying to solve a problem with technology, the problem has to be solved through technology, through process changes, workflow changes and to human behavior."
- “You will never create a model that is right. You will create a model that hopefully is okay, and then you'll get feedback, and then you'll make it better."
- "What's different today is that technology has gotten to the point where you can prepare yourself for it. You can do something about it as opposed to always looking reactively to it."