Enhancing Marketing with Engineering : Optimal Product Line Design for Heterogeneous Markets

Successful product line design and development often requires balancing technical and market trade-offs. Quantitative methods for optimizing product attribute levels using preference elicitation (e.g., conjoint) data are useful for many product types. However, products with substantial engineering content involve critical trade-offs in the ability to achieve those desired attribute levels. Technical trade-offs in a product’s design must be made with an eye toward market consequences, particularly when heterogeneous market preferences make differentiation and strategic positioning critical to capturing a range of market segments and avoiding cannibalization. We present a unified methodology for product line optimization that coordinates positioning and design models to achieve realizable firm-level optima. The approach overcomes several shortcomings of prior product line optimization models by incorporating a general Bayesian account of consumer preference heterogeneity, managing attributes over a continuous domain to alleviate issues of combinatorial complexity, and avoiding solutions that are impossible to realize. The method is demonstrated for a line of dial-readout scales, using physical models and conjoint-based consumer choice data. Results show that the optimal number of products in the line is not necessarily equal to the number of market segments; that an optimal single product for a heterogeneous market differs from that for a homogeneous one; and that the representational form for consumer heterogeneity has a substantial impact on the design and profitability of the resulting optimal product line – even for the design of a single product. The method is managerially valuable, as it yields product line solutions efficiently, accounting for marketing-based preference heterogeneity as well as engineering-based constraints on which product attributes can be realized