Global markets are facing prolonged periods of deflation, and many B2B company leaders are more closely considering the impact of that market dynamic on pricing and margins, especially as they are faced with increasing pressure from customers to lower prices.
This leads to some very difficult questions, such as: “When do I need to start lowering my prices? How far do I need to go?” “For which customers and products do I need to lower price?” Holding onto price while costs drop can lead to more profits, however, it can be taken too far, leading to losses of customers, revenue and profits.
Whether the cost change is a result of prolonged deflation, occasional spikes in cost increases or decreases, or regular cost swings, it’s critical to have a clear, data-informed strategy during these times rather than leaving decisions completely in the hands of sales and “letting the market tell you” what prices should be. In this three-part blog series, we will discuss how advanced data science can provide predictive insights to help answer these tough questions across broad customer and product portfolios.
When you think about your pricing strategy with respect to material cost volatility, from what is planned to what actually happens, as well as that's going, is there anything that gives you cause for concern?
Read the next post, Analyzing Cost Strategies, where Pete dives into how to analyze your existing pricing strategies and provide real data visualization examples.
About the Author
Pete brings 20 years of product strategy experience, helping Fortune 500 companies harness Big Data to improve business performance. As Senior Vice President of Products and Science, Pete is responsible for leading Zilliant’s R&D efforts and defining the product lifecycle and requirements. Prior to Zilliant, Pete served as Vice President of Product Marketing at Yclip. Prior to Yclip, Pete managed KD1’s highly scalable data mining and decision support applications used by Walgreens, Lowe’s Home Improvement and Pepsi/Frito Lay. He also worked at Kelly Information Systems where he oversaw product development and implementation of their multi-terabyte data warehouse analytics product line. In addition, Pete has worked in consulting and product development roles with Category Management, Inc. and Procter & Gamble. He earned his B.B.A. in Quantitative Analysis and Information Systems from the University of Cincinnati.Follow on Twitter More Content by Pete Eppele