Knowledge about a product’s willingness-to-pay on behalf of its (potential) customers plays a crucial role in many areas of marketing management like pricing decisions or new product development. Numerous approaches to measure willingness-to-pay with differential conceptual foundations and methodological implications have been presented in the relevant literature so far. This article provides the reader with a systematic overview of the relevant literature on these competing approaches and associated schools of thought, recognizes their respective merits and discusses obstacles and issues regarding their adoption to measuring willingness-to-pay. Because of its practical relevance, special focus will be put on indirect surveying techniques and, in particular, conjoint-based applications will be discussed in more detail. The strengths and limitations of the individual approaches are discussed and evaluated from a managerial point of view.

A review of methods for measuring willingness-to-pay

There are now available a number of new subscription services that comprise a dual pricing system of a monthly access fee rental and a per-minute usage charge. Examples include cellular phones, the Internet, and pay TV. The usage and retention of such services depend on the absolute and relative prices of this dual system. For instance, a moderate access fee but a low-usage charge might initially appeal to customers, but later a low-usage customer might find the monthly fee unjustified and thereby relinquish the service. Providers of such services, therefore, usually offer several pricing packages to cater to differing customer needs.

The purpose of this study is to derive a revenue-maximizing strategy for subscription services, that is, the combination of access and usage price that maximizes revenue over a specified time period. An additional objective is to determine access and usage price elasticities because they have historically played an important role in theoretical pricing models. The application area is the cellular phone market, but for a new rather than an existing product. To help gauge the likely usage rates and customer retention, a field experiment is conducted in which several alternative price combinations are used. Specifically, a sample of potential residential customers most of whom did not have an existing cell phone were divided into four treatment groups. The first group were not charged an access fee but did have to pay a small per-minute usage charge. The second group also paid a small usage charge but in addition had three access price increases over the duration of the trial. The third group paid no access fee but had usage charge increases, while the fourth group had both access fee and usage charge increases. Usage levels for each respondent are recorded, as is their month of dropout if they discontinue the service.

An initial examination of the data shows that higher access fees result in higher customer attrition, and higher usage cost results in lower usage. Furthermore, usage and retention are related in that declining usage levels over time often signal impending customer attrition. Hence, two phenomena need to be modeled: usage of the service and customer retention conditional on usage. Some seasonal effects are also observed and are allowed for in the model. Modeling customer attrition simultaneously with usage is important because ignoring customer attrition will likely result in an underestimate of price sensitivity. This results from a censoring effect, whereby respondents who remain in the trial tend to be wealthier, and hence, less price sensitive.

Given the known problems of ignoring customer attrition, we develop a theoretical model of usage, which explicitly incorporates attrition by extending a time-series model introduced by Hausman and Wise 1979. We make two extensions of the Hausman and Wise model. The first is to generalize it from two to many time periods and the second is to allow for respondent heterogeneity by incorporating latent classes. We fit the model by maximum likelihood and find that a two-segment model is best. In addition, we examine the predictive validity of our model and find it to be reasonably good.

In general, the results show that access and usage prices have different relative effects on demand and retention. There are five key results. First, access price has some effect on usage but a much stronger effect on retention. Second, usage price has a strong effect on usage and a moderate effect on retention, in that if usage price increases so much that usage declines, then lower usage levels results in higher attrition. Third, access price elasticity is about half that of usage price, with both elasticities generally being much smaller than 1, indicating relative inelasticity for this particular service. Fourth, customer attrition rate churn is much more sensitive to access than usage price and, last, if just observed usage is examined and customer attrition is ignored, then price sensitivity is very likely to be substantially underestimated on the order of 45% in our case.

Finally, when developing the revenue-maximizing price combination we allow for the cost of customer acquisition by using some typical advertising-to-sales ratios for the telecommunications industry. We find that the revenue maximizing price is $27.70 per month for the access fee and $0.81 per minute for the airtime charge. These values are in line with current access fees and usage costs in the given market.

/pdf/optimal-pricing-of-new-subscription-services-analysis-of-a-iunrggo3pd.pdf

Optimal Pricing of New Subscription Services: Analysis of a Market Experiment

In this paper, we describe the practical application of a flexibility-based management approach to new product development, highlighting advantages, and limitations of this methodology. The model is concerned with the resolution of uncertainty over the product development life cycle and deals with technical, market, and cost factors all together. To this end, we consider a real options model, which uses multidimensional decision trees, to assess the development process of a high-technology product, namely, the Adaptive Optics Scanning Laser Ophthalmoscope. Moreover, we show how this project could be managed by estimating its value and determining optimal managerial actions to be taken at each review stage of the new product development process. Finally, we draw conclusions about this model's general utility and particular challenges associated with its use as a product development tool, and emphasize the need to consider a multidimensional model, instead of a single dimensional one.

http://people.bu.edu/tgb/PDF_files/Santiago.pdf

Management of R&D projects under uncertainty: a multidimensional approach to managerial flexibility

Best Practices for New Product Pricing: Impact on Market Performance and Price Level under Different Conditions

Current complex dynamic markets are characterized by numerous brands, each with multiple products and price points, and differentiated on a variety of product attributes plus a large number of new product introductions. This study seeks to analyze dynamic pricing paths in a highly complex branded market, consisting of 663 products under 79 brand names of digital cameras. The authors develop a method to classify dynamic pricing strategies and analyze the choice and correlates of observed pricing paths in the introduction and early growth phase of this market. The authors find that, despite numerous recommendations in the literature for skimming or penetration pricing, market pricing dominates in practice. In particular, the authors find five patterns: skimming 20% frequency, penetration 20% frequency, and three variants of market-pricing patterns 60% frequency, where new products are launched at market prices. Skimming pricing launches the new product 16% above the market price and subsequently increases the price relative to the market price. Penetration pricing launches the new product 18% below the market price and subsequently lowers the price relative to the market price. Firms exhibit a mix of these pricing paths across their portfolios. The specific pricing paths correlate with market, firm, and brand characteristics such as competitive intensity, market pioneering, brand reputation, and experience effects. The authors discuss managerial implications.

Skimming or Penetration? Strategic Dynamic Pricing for New Products

Introduction The problem of establishing a price for a new product is typically related to one of a number of possible company pricing objectives. McCarthy and Shapiro, for example, divide possible pricing objectives into the categories “profit oriented”, “sales oriented” and “status quo”, and then further subdivide them according to the diagram in Figure 1. The status quo objective of “meeting competition” translates itself directly into a new product price, while that of “nonprice competition” implies that price is to be de‐emphasised—one is, nevertheless, left with a pricing decision. All the other pricing objectives require either an explicit or implicit knowledge of the relationship between the price of the product and the quantity of goods sold—i.e. the demand curve.

Clive Lawler‐Wilson

Papers

Pricing New Products