Value-based pricing requires the estimation of the economic value of a good. For this, estimating differentiation value becomes important: to what extent does a product or service provide additional value to a consumer? Estimating differentiation value requires strategic approaches towards measuring monetary and psychological value that we will investigate in the following.
Differentiation Value as a component of Economic Value
Economic value consists of the two components reference value and differentiation value.
That means, the value that consumers attach to a product depends firstly on the available alternatives and their values (reference value). Secondly, the product at hand is differentiated from these alternatives and therefore captures differentiation value. We want to focus on the latter component.
Differentiation value refers to the net benefits that your product or service delivers to customers over and above those provided by the competitive reference product(s). Competing products in a category likely provide many sources of differentiation value.
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Monetary Value and Psychological Value
Differentiation value comes in two forms: monetary and psychological, both of which may be instrumental in shaping a customer’s choice but require very different approaches to estimate them.
Monetary value represents the total savings or income increases that a customer accrues as a result of purchasing the product. Psychological value refers to the ways that a product creates innate satisfaction for the customer.
Differentiation Value Estimation
Estimating differentiation value consists of measuring monetary value and psychological value. The distinct characteristics of monetary and psychological value drivers require different approaches to quantify. In the following, we will therefore dive into each of these two components in more detail.
Estimating Monetary Value
The crucial basis for estimating monetary differentiation value is to gain a detailed understanding of customer value drivers and translate that understanding into quantified estimates of monetary value.
Monetary value drivers are tied to the customer’s financial outcomes via tangible cost reductions or revenue increases. As monetary value drives are already quantitative, monetary value can be estimated using qualitative research techniques that allow for a profound understanding of the customer’s business model or personal finances.
The first step in estimating monetary value drivers is to understand how the product category affects the customer’s costs and revenues. In consumer markets, this is a relatively straightforward exercise. For instance, think of a car purchase: for most buyers, fuel and maintenance costs will be important monetary value drivers. The quantification of these is also fairly simple. Quantifying monetary value drivers in B2B markets is more challenging because of the complexity of most business operations and the need to fully understand how a product affects a customer’s profitability. Therefore, in B2B cases, you should begin with a detailed analysis of the customer’s business model. This must be done to understand how your product or service contributes to the customer’s ability to create value for its own customers.
Once the mechanisms for value creation are understood, the next step in estimating monetary value is to collect specific data in order to develop quantified estimates. For this, in-depth customer interviews are often used. In contrast to other methods such as surveys or focus group methods, in-depth interviews probe the underlying economics of the customer’s business model and your product’s potential role in it. These interviews should reveal how much additional value is provided by the product at hand: how much cost will it save? How much additional revenue may it generate? The overall goal of this step is to eventually develop value driver algorithms, thus formulas and calculations that help estimating differentiation value precisely. In-depth interviews provide a foundation for developing these value algorithms and help to collect some data points to turn these algorithms into quantified estimates of customers’ monetary value drivers.
Estimating Psychological Value
In contrast to monetary value drivers, the intangible nature of psychological value drivers such as satisfaction are not inherently quantifiable. Therefore, marketers need to rely on more sophisticated quantitative techniques in order to quantify the worth of the various elements of a product offering.
The most widely used of these techniques is conjoint analysis. Applied frequently in New Product Development, conjoint analysis helps to uncover the value customers place on different features of a product. The basic approach is to decompose a product into groups of features and then provide customers with a series of choices among various feature sets to understand which of these feature sets they prefer.
The use of conjoint analysis greatly assists in estimating differentiation value as it becomes possible to estimate psychological value in quantitative terms. This is realized by estimating the value of different feature sets in driving willingness-to-pay and, ultimately, the purchase decision. For instance, a TV can be described in terms of attributes such as size and screen resolution. In a conjoint study, each of these attributes is divided into levels that can be tested. For instance, screen size might be broken into 36 inches, 42 inches, and 52 inches as a means to estimate the relative value placed on greater screen size. Similarly, resolution might be broken into HD, Ultra HD and so forth. This enables us to understand how customers might value a 36-inch Ultra HD TV relative to a 42-inch HD-only model.
Regardless of the attributes tested, the value estimates derived from the conjoint study can then be used to quantify the psychological differentiation value of a good.
