AI & Machine Learning in the Pricing World

In today’s fast-paced world, rapidly evolving data and software driven strategies are imperative to creating sustained commercial pricing success. Good processes and experienced personnel alone are no longer enough. It is nearly impossible to rely on spreadsheets, custom software tools, and empirical observation to properly manage the complexity of becoming a “data-driven” pricing organization. That’s why it’s more important than ever to not only understand what Artificial Intelligence (AI) and machine learning are but also to learn how to use them for tangible value in data-driven pricing.

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How Well Does Your Pricing Organization Learn From the Field?

Unlock latent potential with price experimentation

With every price quote or posted price, there is an opportunity to learn about the market, and in turn, improve pricing. Yet, a tremendous amount of the information is not captured, systemized or utilized, neither by people in pricing nor the algorithms they employ. The potential in learning from the untapped sources of field information can be tremendous.

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Tariffs: Fighter Pilot Strategies Businesses Can’t Afford to Ignore

Pricing teams that rely on Excel models and manual processes can be overwhelmed with the challenge of optimizing price as tariffs whipsaw cost. An Excel-based response can feel like “bringing a knife to a gun-fight.” Many companies have finite opportunities to change their price in any given year placing even greater weight on the right “weapon” in their pricing arsenal. Therefore, the biggest questions for pricing teams and senior leadership in B2B companies right now are how can we create an effective response swiftly, how can we ensure that the response is consistent with our broader pricing strategy, and how do we safeguard limited opportunities to change prices?

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Sales Organizations Benefit the Most from Pricing Software, Just Ask a Soccer Fan

“It’s in the game.”

The traditional core objective of pricing technology was centered on the identification of the margin leakage. The pricing team operated the software and provided sales with insights to mitigate the margin erosion. Put another way, the software served as a business intelligence support system with considerable human intervention. From the sales person’s vantage point, the pricing software was on the sideline.

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