Mailing Decisions in the Catalog Sales Industry
Gabriel R. Bitran, Susana Mondschein
Abstract
Gabriel R. Bitran, Susana Mondschein
Abstract
Catalog sales are among the fastest growing businesses in the U.S. The most important asset a company in this industry has is its list of customers, called the house list. Building a house list is expensive, since the response rate of names from rental lists is low. Cash management therefore plays a central role in this capital intensive business. This paper studies optimal mailing policies in the catalog sales industry when there is limited access to capital. We consider a stochastic environment given by the random responses of customers and a dynamic evolution of the house list. Given the size of real problems, it is impossible to compute the optimal solutions. We therefore develop a heuristic based on the optimal solutions of simplified versions of the problem. The performance of this heuristic is evaluated by comparing its outcome with an upper bound derived for the original problem. Computational experiments show that it behaves satisfactorily. The methodology presented permits the evaluation of potential catalog ventures thus proving useful to entrepreneurs in this industry.
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Catalog sales are among the fastest growing businesses in the U.S. The most important asset a company in this industry has is its list of customers, called the house list. Building a house list is expensive, since the response rate of names from rental lists is low. Cash management therefore plays a central role in this capital intensive business. This paper studies optimal mailing policies in the catalog sales industry when there is limited access to capital. We consider a stochastic environment given by the random responses of customers and a dynamic evolution of the house list. Given the size of real problems, it is impossible to compute the optimal solutions. We therefore develop a heuristic based on the optimal solutions of simplified versions of the problem. The performance of this heuristic is evaluated by comparing its outcome with an upper bound derived for the original problem. Computational experiments show that it behaves satisfactorily. The methodology presented permits the evaluation of potential catalog ventures thus proving useful to entrepreneurs in this industry.
Key concepts: Renting, Heuristic, Computer science, Outcome (game theory), Cash flow, Asset (computer security), Revenue, Operations research