eThesis - School of Business electronic theses

Objectives of the Study The objectives of the study are both managerial and methodological. On the one hand, the aim is to apply a novel research approach, fuzzy set qualitative comparative analysis or fsQCA (see f. ex. Ragin, 2000; Rihoux & Ragin, 2009), to sales response modeling and thus, create a response model for the case company to identify complex, configurational causalities affecting the company's sales volumes within the chosen product category. On the other hand, to goal is to illustrate the benefits of the configurational analysis and fsQCA in sales response modeling. In other words, the broader aim of the study is to arouse interest in configurational analysis both among the marketing managers and academics.

Academic background, methodology and research data The theoretical background of the study builds upon marketing productivity and marketing performance theories as well as sales response modeling practices. A novel research method, fsQCA, is applied to sales response modeling to link marketing activities to sales outcomes and to examine complex interrelationships between the marketing activities in a certain fast moving consumer goods product category. The data used in the empirical example consists of weekly-level media expenditure and price promotions data ranging from the beginning of the year 2009 to the week 34 of 2010. Media expenditure data covered seven media categories and the data was documented by a media research company, whereas price promotion figures were reported by the case company's sales personnel for both the case company and its competitors.

Findings and conclusions Two separate solutions are presented as the results from the fuzzy set analysis to illustrate causal asymmetry; the first one represents a solution for the outcome and the second a solution for the negation of the outcome. These solutions are provided mainly as examples of what kind of information can be achieved from configurational analysis and how this information differs from the knowledge gained from the traditional response models. From managerial point of view, the solutions show how the different marketing mix elements combine to result in high/low sales volumes and what kind of alternative configurations can be found to lead to the outcome and its negation in the case context. From academic point of view, the key contribution of the paper is to apply a rather new method, fsQCA, to sales response modeling, provide an example of the empirical execution and analyze how future, further-developed fsQCA applications could potentially complement the present range of marketing productivity analysis tools.