Doug, your role as Senior Vice President at Pricefx reflects a journey of leadership and expertise in the pricing technology sector. Could you walk us through your journey that has led you to your current position?
Sure… in my early career, as an engineer, I solved problems using optimization technology. While the problem solving was interesting and fun, one big revelation to me was when I realized that by solving these problems I could extend the life of an asset for my customer, which would yield about $8M per month for extra life. While I moved my career to business, specifically supply chain and pricing, that feeling never left – that leveraging advanced science and math in my jobs can make my customers a ton of money. Pricing is the most natural lever for that, but supply chain is a close second
Also Read – MarTech Interview with Ivana Istochka, VP of Demand Gen at Amity
Your AI technology is described as the pricing industry’s first and only Multi-Agent Artificial Intelligence (MAAI) technology. Could you delve deeper into what MAAI entails and how it’s applied in the context of pricing optimization?
Sure. Again, it is not about the technology, but the flexibility and focus. That said, our MAAI technology uses several different kinds of machine learning algorithms to simulate business environments along with optimization technology to provide the recommended path forward. There are five main schools of thought in machine learning. Connectionists, Evolutionaries, Bayesians, Analogizers, and Symbolists. The agents in MAAI interact and evolve, leveraging both the connectionist and evolutionary approaches, and the optimization toolkit comes from the analogizers school. The agents interact in a market and help the optimizer understand what the response will be for particular price actions. The output is a recommended price point, price action, discount, promotion, etc. that drives a specific business outcome.
In dynamic markets, business strategies often need to evolve rapidly. How does your technology enable companies to continuously adapt their pricing strategies to stay ahead of market shifts?
Our algorithms continuously monitor the data coming into the app, reflecting the latest market conditions. The output is real-time into our other modules. For example, if you use a market-based pricing strategy and the market changes, the prices output from the model can be immediately implemented in the market, allowing our customers to be as close to the market as possible.
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MarTech Interview with Doug Fuehne, SVP at Pricefx
Published on February 12, 2024
Published by Mark10
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