How to Capture More Value With Price Segmentation

If a company has only one price for a given market or region, it is pricing too high for some customers and too low for others.
Alex HoffJuly 6, 2017
How to Capture More Value With Price Segmentation

One of the most basic concepts to understand about pricing is that price generally reflects (or should reflect) value. But it’s important to remember that value is not defined from the seller or supplier’s perspective; it’s defined by the customer or buyer. A good is only worth what a buyer is willing to pay for it. And their willingness to pay is based largely on how they perceive the value of the seller’s product, service, or solution.

A simplistic approach for a marketing and sales team is to understand what customers typically value in an offering and then set prices based on what the estimated willingness to pay is for that product.

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However, in reality, different customers perceive value differently. So, therefore, their willingness to pay is also different (and their pricing could be different too). This strategy is valid in consumer products markets, but it’s fairly challenging to leverage because retailers often can’t discriminate on price from one consumer to another. But in business-to-business industries, it’s almost always possible and acceptable to differentiate price between customers. That’s because in many cases, prices are negotiated or established based on certain “fences” or boundaries (e.g., educational institutions get a different price than commercial businesses).

A manufacturer of truck tires once explained to me that some of his customers have a different willingness to pay based on their industry. For instance, a fleet manager for a waste management business is typically very price sensitive so he’s not as interested in quality. If one of his trucks was disabled because of a blown tire, there would be no significant impact on his revenue.

However, an oilfield services business that uses similar tires for their mobile drilling rigs could lose a lot of revenue if one of their rigs (which they rent out by the hour or day) was out of commission due to mechanical or tire problems. Those two customers would likely have different price sensitivities and willingness to pay for an identical or very similar product.

A manufacturer of plastic pellets once told me that even with her products, which are considered somewhat of a commodity by many, the end-use application drives measurable differentiation in willingness to pay.

For instance, when the company sells plastic pellets for use in manufacturing pipe, the plastic is a relatively large percentage of the total cost of goods for the pipe. This pipe manufacturer is likely to have relatively high price sensitivity. However, when the company sells the same or a similar plastic to a company manufacturing a sophisticated and expensive medical device, that plastic is a relatively small portion of the cost of goods. So that customer tends to have a lower level of price sensitivity. This principle is not new; it’s been in marketing and economic textbooks for decades. But this and other principles that explain differentiation in price are less commonly used in practice than you’d think.

In B2B, a company’s best salespeople typically understand these dynamics intuitively and use them to maximize their commissions. But many times — especially in larger organizations — the bulk of the sales team ends up using a combination of recent experience (which may not be very relevant) and “gut feel.” And, typically, they’re trying to optimize their chance of winning opportunities, not trying to optimize revenue or margins.

So it’s helpful to explain pricing segmentation to sales leaders as simply putting structure and logic in place that mimics how their best salespeople already do things today. Indeed, at my employer, our projects always need to include the perspectives of the best salespeople because they often provide some of the key context that either supports or clarifies the findings from data and analytics.

Why Price Segmentation?

Why would a company bother to differentiate prices based on customer willingness to pay? The answer is it stands to gain a lot of value. If the company has one price for a given market or region, it will be pricing too high for some customers and leaving money on the table from other customers. By pricing according to different customers’ willingness-to-pay levels, the organization can capture the maximum amount of revenue (which of course drives operating profit) for each deal or transaction. (See figure below.)


In most cases these additional sources of value (revenue) come with little or no additional incremental costs, so there’s a direct — and large — link from that revenue to operating profit. Moving to differentiated pricing, based on pricing segments, has been shown to generate anywhere from 1% to 6% of revenue lift (with virtually no incremental costs). That’s typically a 10% to 60% increase in operating profit.

How Do Companies Use Price Segmentation?

The concept behind price segmentation is pretty clear, and well documented in academic textbooks. But how do you go about discerning and then leveraging these pricing segments in the first place?

Experience has shown that the best formula is a combination of data science, and business judgement and context. There are well-establish statistical methods for taking a company’s sales history and identifying pricing segments based on the attributes of each sale. These attributes tend to fall into three categories:

  • Product / Service — attributes about what is being sold (e.g., product lifecycle)
  • Customer — attributes related to whom the product is being sold (e.g., customer industry, customer size, new or existing customer, end-use application)
  • Transaction — attributes related to the historical transaction itself (e.g., spot quote or contract-related transaction, order size, competitor)

Once the company leverages the attributes it already has in its sales history, it then needs to factor in logical rules or strategies that may or may not be empirically present in the data. A classic example is that a company doesn’t want to group transactions sold directly with those sold through a distribution channel. Other insights are more nuanced and come from human interaction with the data — often the best sales people. This approach not only results in a more accurate segmentation, it also has benefits with regard to change management and adoption.

Finding the right level of segmentation is a bit of a “goldilocks” process: too much granularity and science in a segmentation and the firm will have way too many segments and they will be difficult to explain or understand in practice. If the firm has too little granularity and is just defining a managerial segmentation model (segments by rule), then it is most likely sub-optimizing value by pricing too broadly.

Now What?

Once an organization has agreed on a pricing segmentation model for its go-to-market approach, it then needs to find a way to operationalize it. Merely defining it and articulating it to the right employees is not enough.

Management needs to provide segment-specific context and guidance to sales or price approvers in their day-to-day business process or context. This usually means delivering the segment-specific guidance directly into their customer relationship management or customer price quote environment where they are working on opportunities, quotes, and contracts. Software vendors in this space are beginning to merge their capabilities and in some cases acquisitions are accelerating this process. Segmentation is becoming more and more of a standard approach and reality for organizations seeking to capitalize on the rich benefits available from more fine-grained pricing approaches.

Once management has set the segmentation and trained appropriate teams on how to implement it, it’s time to sit back and reap the benefits.

Alex Hoff is vice president of business consulting at Vendavo. He and his team work with organizations from a wide variety of B2B industries to help them identify and capture opportunities that drive revenue and margin improvements. 

Featured image: Thinkstock

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