Required Reading: Pricing Science Has Changed a Lot in Nine Years

Jim Vaughn, global head of pricing advisory services at Zilliant, has updated his book, Stop Racing in a Blindfold!: Big Data + Pricing Science Drive Bigger Profits, to address the changes in the business landscape and technology in the past nine years. CRM editor Leonard Klie discussed these changes with him.

CRM: What prompted you to update the book now?

Vaughn: While basic pricing ideas have not changed, sellers’ and customers’ mindsets and general market expectations have.

Companies have learned a lot since 2015. Business leaders are more experienced with volatile markets and have accepted that prices can be changed as market conditions change over shorter periods of time.

Beyond that, there has been a strong need to match price to the value customers perceive from the products they buy. Companies are sharpening their understanding of this perceived value, enabling sellers to finely tune the price guidance they give.

A key part of market expectations is pricing transparency. Many corporate buyers regularly push hard for price synchronization across platforms where they interact with sellers. The ability to meet this expectation drives greater sophistication in price management.

You say new technology is completely revamping the pricing process. Can you give examples?

The pandemic brought many business challenges; the most substantial was cost volatility. It impacted pricing through supply and demand; when you have no supply or demand, price does not matter. The velocity of change was driven by technology improvements not seen since the dot-com era. Companies had more automated data feeds and more integrated/less siloed data to mine, and they could turn that into market pricing intelligence.

We also saw companies change what and how they priced. We saw a greater embrace of subscriptions to give customers an alternative to capital expenditures.

You seem to blame inflation for much of the pricing changes. How can companies respond without overburdening consumers?

Pricing changes have much more to do with market-facing effects of input volatility. Costs went up rapidly, and costs went down rapidly, but the day-to-day volatility was the most challenging part for business.

The trick is to not introduce pricing noise into the process. Recognizing that most customers place a premium on price predictability, this should inform how often businesses adjust prices. And while they will always prefer smaller increases over larger ones, they really don’t like the death-by-a-thousand-cuts price increase approach. Understanding what customers value beyond product fit is key to a well-aligned relationship.

You say businesses are rethinking their value to customers and moving to service-based pricing and subscription models. What benefits do these approaches offer businesses and consumers?

The subscription model brings greater predictability to suppliers and customers, but it also means thinking about pricing in new ways. Ultimately, it helps align product prices (value) with customers and reinforces customer lifetime value. The ability to match price to the benefit the buyer will receive allows businesses to tap new customer markets, and when bundled with services that remove or reduce overhead costs, makes those customers very sticky.

The growing popularity of the subscription pricing model hinges on technological interconnectedness gains, like remote connectivity and IoT capabilities that did not exist 10 years ago.

You propose a new framework for connecting business concepts to the equivalent capabilities in a pricing science approach. What is this framework, and how can businesses apply it?

The framework is a comprehensive assessment. While there are 30 distinct components, it boils down to two main questions: 1. How can businesses assess industry, channel, market, and customer price sensitivities? 2. How can businesses assess the sales organization’s designed/structured capability and performance capability? With this in mind, users can connect tactical pricing data derived from analytics to strategic/operational business intent/objectives.

What is the key message you want readers to take away from this book?

Clearly communicate to stakeholders that there is a clear path to improve agility and profitability. We moved from early adopters to rapid expansion five to eight years ago, and if your business is not already heavily involved, it’s likely your competitors are.

Pricing directly leverages advances in artificial intelligence and data science. Pricing science has a 40-year track record of producing 100 to 500 basis point margin gains. If AI and data science is driving conversation in your business, then better pricing capabilities are a way to apply that with little risk.