The Revolution will be Digitized: The Growing Importance of Pricing in B2B eCommerce

Sean Cassidy

A recent Gartner Report: “Digital Transformation Will Require Pricing Transformation,” underscores the importance data science-driven pricing will play in the next few years; not only in finance and marketing, but also on the front lines of sales. With sales force automation (SFA) progressing beyond automation and efficiency improvements into the realm of predictive analytics, there are now a myriad of tools that can more effectively drive demand, initiate and optimize customer engagement, and even drive incentive compensation. But nowhere is analytics more vital than in pricing, the one part of the transactional sales process where true bottom-line improvements can be had. And how optimized pricing is delivered to the field can make all the difference in how enterprise-class businesses can grow margins and boost business and shareholder value.

According to the Gartner report “by 2018, 40% of B2B digital commerce sites will use price optimization algorithms and configure/price/quote tools to dynamically calculate and deliver product pricing.”

B2B E-Commerce Has Arrived The key takeaway in the quote above is the term “B2B digital commerce” or eCommerce. B2B eCommerce is becoming a hot topic as more and more traditional industries, such as manufacturing, food, and consumer goods, embark on digital transformation projects. As buyers of all shapes and sizes become savvier in the digital business age, even “old school” industries must adapt to meet buyer expectations. Creating a consistent buying experience across all channels, from direct sales to partner sales to parts business and even online self-service, is essential.

When deployed across all sales channels, SFA tools like CPQ (configure, price, quote) are extremely important in delivering a consistent buying experience for customers, especially for companies with complex product and service catalogs. What is often overlooked though, is how price optimization — and price consistency — can play an outsized role in customer satisfaction. By leveraging data science in pricing, companies can not only recapture lost revenue and achieve their financial goals, they can ensure that the pricing customers receive, whether direct or from partners, resellers, or parts dealers, is fair and consistent. At the recent PROS Outperform conference in Orlando, Iron Mountain’s Steve Haggett explained how pricing fairness is one of the key drivers in his company’s move to automated price optimization. With more than 100,000 subscription customers, Iron Mountain couldn’t ensure it was delivering fair and equitable pricing to all of its customers without an automated price optimization platform.

In the past, sales channels could often take adversarial roles when it came to pricing, leaving customers stuck in the middle in the fight to squeeze as much money out of them as possible. By using the wealth of previously underutilized data at their fingertips, companies that employ price optimization and guidance across all channels — especially when delivered via CPQ — have a much better shot of keeping all interested parties satisfied, from the C-Suite to partners to most importantly, customers.

Read the full Gartner report here.

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