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Product concepts in megacity marketing
Purpose. This article addresses the question of how to identify product concepts of megacities as complex products that are simultaneously consumed and created by user groups with different preferences and behavioural patterns.
Methodology. We use empirical research to systematize heterogeneous descriptive data about the attributes of city districts and the everyday activities of their residents to further identify the key uses of the places in which they live. Classifiers are used as a tool to systematize city product technologies and uses. This tool was built deductively on the principle of morphological analysis (Zwicky 1969).
Findings. Ten distinctive product concepts of 12 Moscow districts and the city outside them were formulated as distinctive sets of benefits or district uses (needs satisfied and activities encouraged) offered to residents. The concepts yielded represent combinations of seven abstract types.
Originality. The paper proposes a new method for city product analysis which combines the advantages of the standardized (Kotler et. al, 1999) and narrative (Warnaby and Medway, 2013) approaches to place product and brand building. On one hand, this study expresses each of the city product concepts in terms of typical constructions, and, on the other hand, in contrast to previous studies, it fully reflects the distinctive features and specificities of the big city and its districts.
In narrative terms, much uncertainty still exists about the motivational and behavioural distinctions between city users as well as crucial differences in product concepts they share and the distinctive marketing strategies that satisfy them. The present study’s results demonstrate how consistent and inconsistent city use patterns can be identified.
Practical implications. We believe that the analytical procedure that we have developed is a much-needed supplement to the existing techniques that are used when shaping the product strategies of megacities. Identifying contradictory uses helps make product decisions that are appropriate to support all these uses concurrently.