From Bruno Slosse
It is almost universally recognized across the business world that artificial intelligence (AI) will change things. A PWC survey confirmed this. 85 percent of CEOs believe that AI will change the way they do business “significantly” over the next five years.
In B2B pricing, there are two challenges that AI can face for the CEO: First, it is about reducing missed opportunities simply because the wrong price was quoted and the customer moved their business to another location. More responsiveness – with the right information – means more revenue.
The second challenge is more insidious – and while it’s very easy to understand the problems, it’s much more difficult to measure. Too often, the C-Suite gets dragged into an ad hoc review and approval process that consumes valuable executive bandwidth as each negotiated deal becomes “strategic”. Most organizations find that they actually have multiple, very similar, and relatively moderate impacts that have been addressed recently, but all in a crisis or emergency mode. Think of the benefits to your trading team as a consistent tactical application of your agreed-upon strategy that saves time otherwise spent on those fire drills to focus on improving organizational performance.
A change that is already in motion
Like so many near-seismic changes that take place within organizations and markets, the occurrence of change is less of a sudden jolt and more of a tectonic shift, gradual but unstoppable. This move to artificial intelligence is already well underway, especially with commercial pricing.
Solutions with AI for dynamic pricing, intelligent negotiation and product configuration, cloud-based CPQ (configuration, price and offer) and more are being accepted by more companies. Especially for those who are global and compete on the front lines with increasingly complex and challenging markets.
This increasing complexity, coupled with the constant pressure to find ways to be more efficient and maximize positive results, makes adopting AI a mandate. How else can large corporations strive for commercial excellence in the face of changing market dynamics, incessant competitive attacks, and increasing B2B customer expectations for B2C speed, precision, and convenience during the buying process?
AI helps you build your process around the buyer
When Gartner reported that 77 percent of B2B buyers said their final purchase was complex or difficult, all sellers should have understood they needed to make the process more user-friendly. This can be the key benefit of using AI in pricing in the years to come.
What some may not have recognized yet? These “complex or difficult” ones are rated relatively by buyers. What was “acceptable” or “convenient” for another generation of buyers five, ten or twenty years ago does not fly with modern B2B customers. They have been driven by advances in personalization – not just in consumer apps but in B2B marketing as well – to expect the same from a vendor’s pricing process. However, it is virtually impossible to achieve such responsiveness and personalization using manual and outdated pricing approaches.
Therefore, in B2B pricing over time, AI will be an essential tool to significantly improve the user experience for a potential buyer. Let’s compare two hypothetical sellers to illustrate the point:
Provider A. has a sometimes complex B2B product offering or a variety of offers; his competitor, Provider B.has an almost identical product mix. The benefits of both are almost the same.
Provider A.however, relies on “traditional” pricing methods and is therefore unable to quickly evaluate complex configurations and identify them to potential customers. This also hinders them in customer segmentation as they have limited business information during negotiations and cannot develop real-time pricing information. The result? A process that is slow, tedious and imprecise for both the seller and the potential buyer. Offers are not awarded, especially since there is a competitor – Vendor B – who offers a superior user experience during the pricing process.
Provider B. implemented AI in pricing. In this way, they can quickly deliver accelerated negotiations and highly accurate prices to the buyer even with complex configurations by using several data points: intelligent segmentation, machine learning using data from previous contacts with this buyer, competitive information, context data and more. The result? There is less money on the table as this seller is now winning more deals while optimizing margins.
The real transformation of B2B pricing that AI will deliver as it becomes more widely used is to provide pricing processes that work in near real time and offer higher end value for both sides.
An unlimited benefit?
It’s a confirmed fact: Companies that apply AI and machine learning to pricing and sales processes are already seeing significant improvements in supply accuracy, revenue growth and margins at this relatively early stage in the development of these systems.
However, as these solutions and platforms evolve and companies make greater use of them, it is difficult to predict exactly how the long-term improvements will play out. To date, the immediate iterative benefits of using AI-powered pricing have opened the eyes of many users who did not realize how burdened they were by last generation approaches and processes.
For today’s users, the benefits of AI-based pricing have continued or steadily expanded year after year, reliably and predictably. Since these systems are fine-tuned and tailored to business needs, can leverage larger amounts of data to improve smarter actionable insights, or apply to more products and services, is this the ultimate cap on results, growth, and profitability for these adopters? It can be practically unlimited.
About the author
Bruno Slosse is the President and Chief Executive Officer of Vendavo. Bruno brings more than 25 years of technology experience to Vendavo, including a strong track record in growing companies, expanding their global reach and expanding their product offerings. He is fluent in Dutch, French, German and English. Bruno graduated from the University of Ghent in Belgium with a bachelor’s degree in economics.