Blue Ridge Enhances Machine Learning Capabilities for Price Optimization
ATLANTA,, June 24, 2020 (GLOBE NEWSWIRE) -- Blue Ridge announced today enhancements to its suite of next-gen cloud-based Price Optimization solutions, which leverage machine learning to quickly identify opportunities and simulate pricing strategies for peak margin, profits, revenues and sales. The pricing suite supports end-to-end pricing transformations, a strategy proven to minimize disruption and drive significant earnings expansion for distributors and retailers.
Blue Ridge’s Price Optimization solution quickly identifies both overpriced and underpriced products while providing accurate recommendations for aligning prices across products, channels and price points including wholesale, list and customer segment. The solution provides daily alerts on competitive price changes to react quickly in price-transparent ecommerce channels, as well as make recommendations on reducing excess inventory to create significant value and profit margin improvement.
“Today’s enterprises and brands have seen the impact when supply chains and demand signals disrupt markets,” said Ray Wang, Principal Analyst & CEO, Constellation Research, Inc. “Those leaders who had the right price optimization tools were able to respond with agility, resiliency, and speed to account for new signal intelligence and ensure that customers were satisfied, margins were met, and supply chains were not disrupted.”
A report by McKinsey & Company illustrated the latent benefits of intelligent pricing, estimating that “A one-percent price increase would yield 22 percent increase in EBITDA margins, and a 25 percent uplift in stock price. Moreover, pricing has a disproportionate impact on a distributor’s enterprise value, with an increase of 20 percent for a one-percent increase in price.”
“The highly competitive and increasingly digital landscape of consumer buying today requires that distributors and retailers analyze things like minimum advertised price, psychological price points, willingnes-to-pay measurement, and even list and net pricing, as well as macroeconomic influences before setting prices,” said Cliff Isaacson, Blue Ridge Executive Vice President of Product Strategy. “Machine learning-based pricing tools allow our customers to make those decisions swiftly and confidently, so they can always operate at max-profit point.”
Blue Ridge Price Optimization uses machine learning capabilities to continually optimize pricing across all products (not just top-tier items), segment and perfect pricing for each customer, and give distributors the upper-hand in supplier negotiations:
Price Optimization joins Blue Ridge’s suite of Supply Chain Planning solutions, which help customers increase forecast accuracy, improve customer satisfaction, and assure product availability to customers without creating a costly inventory surplus.
“Price Optimization combined with Supply Chain Planning solutions creates a huge financial game changer for retailers, distributors and manufacturers in today’s volatile market,” said Jim Byrnes, Blue Ridge Chief Executive Officer. “It uniquely blends science and synchronization to solve our customers’ biggest problem – what they don’t know. With Price Optimization, our customers have the insight to pivot quickly and grab significant near-term savings; shape and align longer-range S&OP processes; and consistently deliver pricing that’s both competitive and profitable.”
To learn more about Blue Ridge Price Optimization solution, visit https://blueridgeglobal.com/blue-ridge-price-optimization-solution/. In addition, Price Optimization will be a topic at the company’s annual user conference, BLUEPRINT, to be held virtually on September 23-24, 2020. Follow Blue Ridge on LinkedIn for more information and updates about BLUEPRINT 2020 registration.
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