TECHNOLOGY

Reality Check: Choosing and Deploying the Right Price-Optimization Solution

In my previous look at “How to Optimize Pricing to Drive Margins and Customer Experience”, I noted that price optimization capabilities are becoming more and more common across many industries. I also observed that the companies with price optimization capabilities are finding both significant financial returns as well as improved sales processes that result in an improved customer experience.

In this article, I will explore the types of optimization tools that are available for organizations, a few of the most common challenges they face when deploying them, and how they can overcome these challenges.

Price optimization software solutions have a reputation for being a pretty significant investment, yet they have almost unbelievable returns. The average payback is just 12 months

From Airlines to B2B

The theories and math behind most forms of price optimization have actually been around for quite some time, typically in textbooks on economics or marketing. Until modern computer systems made working with large amounts of data practical, however, these methods were limited to special projects conducted by consultants and data scientists, usually on a small set of products or situations.

In the 1980s and 1990s, airlines and some other travel companies began using a type of price optimization often referred to as Yield Management or Revenue Management. In the early 2000s, retail and consumer product companies began using commercial price optimization software solutions to find the optimal shelf price, promotional prices, and even markdown or clearance prices, using complex algorithms with multiple price-demand elasticity measurements.

In the mid-2000, a new batch of price optimization solutions designed for the various business-to-business industries became available.

In B2B industries, all of the leading price optimization software solutions first focus on identifying fine-grained “pricing segments” – segments of their business where willingness-to-pay tends to be similar. Then they utilize some sort of an algorithm to identify the ideal target price for any situation.

Because of the inherent differences in certain sectors, price optimization software vendors tend to concentrate on one main sector like retail/consumer, travel & hospitality, and B2B industries.

Benefits and Challenges

Price optimization software solutions have a reputation for being a pretty significant investment, yet they have almost unbelievable returns. Supply chain specialist AMR Research, which is now part of Gartner, looked at over 100 projects and found that the average payback is just 12 months.

A rough estimate of the investment required of a US$1 billion business unit would be software subscriptions of around US$500,000 to 700,000 per year, and one-time implementation costs of around US$500,000.

This may sound like a big investment, but when you consider the fact that Deloitte measured an average of 3.2% revenue lift from price optimization projects, that’s US$32 million in benefits – usually considered an annual gain – on a one-time investment of US$500,000 plus around US$600,000 in annual subscription.

But, as always, there are challenges. The three common ones are overreliance on price optimization software, getting carried away with the data science, and failure to get buy-in from key departments such as Sales.

Don’t Rely on Software Alone

One fundamental challenge or mistake that often occurs when deploying price optimization solutions is that the client naively believes that a software tool alone will fix the company’s pricing deficiencies.

As in other business disciplines such as marketing, sales, operations, or supply chain, pricing is a combined function of people, strategy, business processes, and, yes, tools. A great software solution that’s deployed with little thought about how to align that tool to a company’s pricing strategy or whether the organization can take advantage of its insights will not achieve its full potential for ROI.

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