Price management and optimization is not a new discipline, but until now, it has been restricted to particular industries — such as discrete manufacturing and chemicals — where there are potentially hundreds if not thousands of stock-keeping units covering many interdependent products.
To ensure that pricing optimizes either revenue or margin, a variety of vendors have created specialist tools and applications used to provide preliminary data-gathering and analysis, pricing model development and optimization, and operational deployment thorough processes like configure, price and quote. These applications support the many selling channels available in both consumer and business-to-business models, such as cost plus, or if in a market with a dominant leader, priced at a discount of the organization’s list price. But these pricing methods potentially leave revenue on the table, as classic pricing theory says that the price — in a perfect market — is the price that balances supply with demand and allows the item to be “cleared” in the sense of finding a willing buyer. Another complication is that discounting from list is often a standard approach as part of negotiating a deal, but if the list price is not set correctly, are you negotiating against yourself?
So, what is preventing organizations from availing themselves of pricing optimization software? I believe there are several reasons, such as:
- Pricing optimization is viewed as difficult and dependent on extensive data gathering and analysis.
- Leadership does not view pricing optimization as an appropriate lever to drive revenue growth and profitability.
- Pricing analytics are not seen as relevant in many industries.
With the growth in data and the ability to micro target different regions, customers and buyers, it’s time to reevaluate the relevancy of price optimization. Now that many organizations are developing multiple selling motions over and above the traditional direct-sales model — including partner ecosystems and digital selling channels — differing costs of sales and customer acquisition will further complicate the calculation of an optimum pricing mix. Crude pricing models and reflexive discounting does not have to be the norm. Many vendors in this space are utilizing newer technologies to collect, process and analyze price and sales data. With the shift to more self-service selling, pricing can be dynamic and more effectively linked to the customer, region and perceived value. Even for organizations using a subscription business model, there are opportunities to try A/B testing or see the effect of demand on past price changes in relation to the original price and competitive prices. I believe that, informed by these vendor initiatives, one in 10 organizations will deploy a dedicated pricing optimization application to analyze, create and operationalize optimized pricing to reduce leakage and maximize revenues by 2024.
Many vendors in the market are now offering services and technology that reduce both the effort and time needed to see a positive impact as well as building best practices into offerings so that in-house expertise is not required to optimize pricing for growth, margin or both. As my colleague Robert Kugel discusses in Profitability Management: A CFO Priority to Gain Competitive Advantage, for many chief financial officers and organizations, margin and profitability optimization is no longer an option.
You may have looked at price optimization before and decided the investment did not justify the return. But with new technologies and approaches, price optimization should no longer be the preserve of the few. You may be surprised how much necessary data you already have, and how quickly vendors can turn that data to your advantage.