In part three of our Real-Time Pricing Engine blog series, we look at how intelligent automated negotiation powered by a real-time pricing engine can optimize and simplify the complex B2B negotiation process to better serve customers. Read part one here and part two here.
Meet the Expectations of the Digital Age
In this blog series, we’ve defined what a real-time pricing engine is, and why the pressures of today’s digital landscape increased the need for a pricing engine with more dynamic capabilities. Additionally, we’ve discussed why it’s so complicated to achieve omnichannel price consistency, especially if you have a large volume of pricing calls that are being made in real-time. In this blog, we’ll examine how, once you’ve laid this groundwork, you can leverage advanced pricing capabilities that meet the expectations of the digital age and enable intelligent, automated price negotiations in digital channels.
B2B Price Negotiations Are Often Costly and Complicated
Mergers, acquisitions, or natural organic growth are all factors that can lead a B2B business to grow into a larger, enterprise-level company. It’s not uncommon for larger companies to process between 10,000 to 15,000 or more order lines daily. While these transactions are numerous, they are, unfortunately, also complicated. Various sales channels such as in-person sales reps, eCommerce, online self-service portals, and deal desks each factor into how quickly a new order can be routed, reviewed, approved, and ultimately finalized. Then, within those channels, many types of orders occur such as project bids, distributor orders, partner reseller orders or bids, new orders, re-orders, and more.
As daily order lines increase dramatically, the pricing negotiation process itself (aside from channel and order type) becomes cumbersome and complicated. When it comes to the challenge of price negotiations, there are three factors that pricing teams need to account for: speed of quoting, accuracy of offer, and completeness of offer. Often when customers request price exceptions, reps must route those to a manager or pricing team for approval. If pricing is broadly misaligned to the market, which is highly common in B2B, the pricing exception queue is all but guaranteed to bog down internal teams and slow down quote turnaround times, which usually results in frustrated customers.
Sometimes companies will add more people to internal teams to improve quote turnaround times. However, the pricing approval and order process is already overly complicated, and there is a lack of reliable pricing guidance, making an already-cumbersome process prone to human error in judgement and calculation. This creates a large administrative overhead cost from a process perspective and generates pricing that fails to meet the P&L targets of the business. Making matters worse, customers are often unsatisfied with prices that are consistently misaligned to their expectations.
Fortunately, the current inefficient and costly price negotiation process can be remedied by taking an approach that blends leading data science and technology. With science integrated into the negotiation process, companies stand to significantly reduce bulky processes and reserve high-skilled negotiators for the most critical deals.
What is Intelligent Automated Negotiation?
Instead of complicated processes that are susceptible to human error, many leading B2B companies are blending the art of negotiation with the science of data-driven decision making and leading technology. The result is intelligent automated negotiation, which is an innovative solution that optimizes the negotiation process, saving time, resources, and profit margin. Intelligent automated negotiation allows for setting pre-defined rules on what prices can be auto approved without human intervention. This gives sales reps, partner resellers and customers the flexibility to negotiate within a range of prices that still maintains necessary margin levels and escalates customer counter-negotiations quickly and efficiently when needed.
Replicating the online buying experience is so much more complex in the B2B world because there is so much negotiation involved. As B2B customers demand more self-service due to their experience as eCommerce consumers, it’s essential to leverage the power of a dedicated real-time pricing engine to consistently execute automated negotiation at the scale and speed users require. The pricing engine performs lookups and complex calculations automatically, which is necessary to power that Amazon-like purchasing experience and market-aligned online pricing customers seek.
Intelligent Automated Negotiation and Real-Time Pricing Engine Resources
B2B companies that leverage real-time pricing engine-enabled intelligent automated negotiation quickly see its benefits. Here are two resources that dive into how intelligent automated negotiation works, and how Zilliant’s Real-Time Pricing Engine™ calculates and delivers prices in real-time to any commercial system:
This case study discusses how intelligent automated negotiation turned a manual and time-intensive quote response process on its head by delivering sub-second quote responses while keeping pricing consistent for an electrical products manufacturer facing an increasingly complex business environment.
Learn more about how Zilliant’s Real-Time Pricing Engine allows B2B companies to rethink how to power intelligent commerce and be more dynamic. Meet the robust REST-based API providing a real-time connection between Zilliant’s pricing solutions and your commercial systems.
By integrating the science of data-driven decision making and leading technology into the art of negotiation, B2B companies can make significant operational and margin gains. Intelligent automated negotiation powered by a dynamic real-time pricing engine can optimize the usually complex B2B negotiation process, better serve customers, and help keep pace with competition in today’s high pressure digital landscape.
Contact Zilliant today to learn more about how our Real-Time Pricing Engine™ can optimize your negotiation process.