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Purpose – International brands are expanding their business into emerging markets seeking new consumers for their products. Multiple research studies suggest that there are two key differentiators between developed and emerging markets that managers must take into account. These are that consumers differentiate between local and international brands, and that consumer segments differ between emerging and developed markets. This paper refutes these myths. The paper aims to discuss these issues. Design/methodology/approach – The authors examine large-scale data of purchase behaviour across seven countries and six product categories through telephone or online data collection. Surveys conducted in conjunction with research consulting projects form the basis of data collection, with samples skewing towards middle-income population from urban areas within the emerging markets. The different survey methods used support the empirical generalisability of the findings. Findings – The authors find that brand user profiles in emerging markets rarely differ between local and international brands across age, income and gender. Differences in segmentation are related to geography – which is likely a factor of infrastructure differences. When brand users are compared, their attitudes towards the brands are also very similar between local and international brands across several attitudinal measures: “high quality”, “value for money”, “meet/understand my needs”, “affordability” and “trustworthiness”. Originality/value – The research highlights that consumers in emerging markets need not be segmented based on their brand purchasing behaviour when it comes to local and international brands. This is in line with a growing body of literature in consumer segmentation and in contrast to a considerable amount of traditional literature on emerging markets.

This paper applies the D Duplication Coefficient from the Duplication of Purchase Law as a benchmark to help investigate patterns in simultaneous product category purchases. Shopper transaction data enable a deep analysis of what goes into shoppers' baskets; however, robust benchmarks are critical to see patterns in such rich data. We demonstrate the application of D Duplication Coefficient data to 30,000-plus UK and US supermarket transactions. The cross-category benchmarks allow meaningful deviations to be identified, isolating categories that are more or less intensely co-purchased than expected, which can then be used to guide decisions regarding store layout, prioritise in-store activations and plan product category promotions.

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