Most companies have adopted procurement management strategies to help drive better profitability by reducing costs. Yet, only a small number are effectively addressing pricing strategies to drive revenue, which is the other half of the profitability equation. Pricing is perhaps the most powerful tool corporate executives can use to affect the profitability of their businesses. Despite the fact companies lose deals when they fail to generate a profitable, competitive quote—or win deals but dilute the company’s bottom-line with less than optimal pricing—they haven’t invested in the technology available to avoid these pitfalls.
Pricing steps to B2B market growth
Business to Business (B2B) companies spent $3.2 billion on procurement software last year, according to a study from management consulting firm McKinsey & Company. By contrast, businesses spent less than $200 million on pricing optimization software. This despite the fact that as little as a one percent improvement in price can yield up to an eight percent increase in profit or more, as incremental dollars come at no incremental cost.
Yes, pricing optimization can be complex—given the various data sources and methodologies that go into its use as a key business decision-making tool. But it’s clear that sound pricing optimization can lower an organization’s risk in setting prices; provide visibility on the impact of pricing decisions; and arm the customer-facing workforce with real-time intelligence on how competitors are pricing.
Tips & tricks
To get you started on your pricing analysis, below are some tips and best practices for implementing effective pricing optimization within B2B markets.
Focus segmentation on what matters most to customers—While many organizations segment their markets by customer size, geography or product families, none of these categories focus on actual purchasing behavior; and each of these categories are treated equally when predicting an optimum price. Without understanding which attributes drive pricing behavior, however, companies are left with an incomplete picture of how to price more accurately. For example, a high-volume customer may be considered more profitable in terms of sheer purchases, yet a lower-volume customer may be more valuable in the long run, since he may be more loyal to your products. Pricing optimization software helps companies determine a handful of key attributes that drive pricing behavior, such as products bought by a customer, the quantity of rush orders or a local competitive situation—and it can weigh and categorize segments by behavior patterns, types of transactions and product selection.
Move beyond basic administrative rules—Most pricing optimization software applies basic administrative rules that help generate better pricing. Pricing managers typically use rules of thumb that are well-known throughout the organization. But a lack of robust tools prevents them from being uniformly applied. Because these pricing software tools only automate existing manual processes, they don’t fully exploit the potential of pricing optimization, which goes beyond the automation of simple rules and provides granular, customer-specific price recommendations based on all available data.
Hindsight may be 20/20 but forecasting is key—The growth of business intelligence software gives front-office employees the power to analyze large volumes of historical data. But in highly dynamic markets with volatile costs, fluctuating demand and evolving competition, looking at historical data is not enough. Pricing optimization technology analyzes trends in pricing and demand data and forecasts where prices are heading, not just where they’ve been.
Avoid one-size-fits-all pricing—Giving all customers in the same segment the same price is less than optimal; it doesn’t take into consideration each individual customer’s willingness to pay by analyzing how differently they respond to services, marketing and sales people. For example, an analysis of prices from a medical-products distributor showed the company could consider lowering prices for a high-performing segment based on historical data. But by analyzing the willingness to pay of this segment and delivering unique recommendations by individual customer and product, the distributor and its sales people were able to use more targeted guidance to increase profitability.
Pricing optimization does not require loss data—Many professionals have been trained to believe that without access to customer loss data there can be no accurate determination of market pricing. By analyzing win data to determine win-rate elasticity—knowing at what price point a deal is won—the vast majority of businesses can optimize prices to maximize margins and profitability.
Consider price elasticity even in B2B markets—In the food services industry, it is unlikely a restaurant would increase its orders of hamburgers just because prices are reduced. The restaurant would only order the amount they think will be consumed. By the same token, if a supplier raises prices, for example, the restaurant would order the same quantity to meet its consumer demand. Given this scenario, it’s important to recognize what really drives volume. It’s probably not price but whether a company has won the customer’s business. If you have the business, you can get the volumes that are regularly ordered regardless of price. Science-based pricing optimization enables suppliers to discover the sweet spot that balances winning business at the maximum profit level.
Market dynamics analysis, a critical key to sound pricing optimization—Rules are an important part of pricing optimization technology and can help streamline processes, since they are designed to be “set and forgotten.” But they also assume that prices will be consistent in the future. The dynamics of market changes, however, are a constant challenge to the inflexibility of rules. New customers become legacy customers, new competitors emerge and product portfolios change over time. Rules that are limited to looking at price variance, price yield and manager-set approval escalations can reduce obvious out-of-bounds pricing—which often results in more profitable pricing. Dynamic market conditions require that rules be constantly monitored and updated. And a science-based approach to pricing optimization can determine which market attributes drive pricing and how these attributes change over time.
Gain buy-in on pricing optimization software from the sales team—The best technology in the world often can’t replace human interaction between a supplier and buyer. While some pricing software enables organizations to set prices according to historical analysis, it offers little guidance for making it operational in the field. Listen to the needs of your sales team—they require a solution that’s flexible enough to handle exceptions for specific customers and also allows overrides in the negotiation process. Technology doesn’t win valued customers; good supplier-buyer relationships do. By listening to the needs of your sales team, pricing optimization technology can help support their efforts and ensure profitability.
Pricing optimization consistently improves financial performance by boosting revenue up to five percent, increasing gross margins from five to 15 percent and enhancing cash flow. Effective utilization of pricing technology can accelerate time-to-quote by as much as 25 percent and increases the ability to respond to market changes. By strategically implementing pricing optimization processes, organizations of all sizes can leverage the collective wisdom contained throughout their companies and supply chain partners to achieve bottom-line results.
Patrick Schneidau is Vice President of Product Marketing for PROS, Houston, a global software and services provider in pricing and revenue management. He is responsible for development of the company’s go-to-market strategies and positioning for its portfolio of pricing and revenue management products. Neil Biehn, Ph.D., is Vice President of Science and Research for PROS. He leads science and research teams on multiple projects and pricing system implementations and heads the company’s market segmentation science team.