Assessing algorithms for selecting countries to market new products to low-income consumers

Abstract

Title

Assessing algorithms for selecting countries to market new products to low-income consumers.

Subject area

A consulting team to an international food packaging company (SDYesBox) is attempting to decide which algorithm is the most useful for selecting two national markets in Central America and the Caribbean. SDYesBox wants to work closely with its immediate customers – manufacturers in the dairy and food industry and their customers (retailers) – to develop and market innovative products to low-income consumers in emerging markets; the “next big opportunity for the dairy industry” according to SDYesBox.

Study level/applicability

New product development and market selection in emerging markets in Latin America.

Case overview

Five algorithms are “on the table” for assessing 14 countries by 12 performance indicators: weighted-benchmarking each country by the country leader ' s indicator scores; tallying by ignoring indicator weights and selecting the countries having the greatest number of positive standardized scores; applying a conjunctive and lexicographic combination algorithm; and using a “fluency metric” of how quickly consumers can say each country aloud. At least one member of the consulting team is championing one of these five algorithms. Which algorithm do you recommend? Why?

Expected learning outcomes

Learners gain skills, insights, and experience in alternative decision tools for evaluating and selecting choices among emerging markets to enter with new products for low-income (bottom of the pyramid) products ands services.

Supplementary materials

Teaching notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes.

Citation

Metzger, M.D., Woodside, A.G. and Ickis, J.C. (2013), "Assessing algorithms for selecting countries to market new products to low-income consumers", Emerald Emerging Markets Case Studies, Vol. 3 No. 4. https://doi.org/10.1108/EEMCS-06-2013-0067

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