Die Bedeutung der Marktforschung in schnelllebigen Märkten mit rasch wechselnden Kundenerwartungen ist heute anerkannt: Gute Marktforschung signalisiert Ertragssteigerungspotenziale und ermöglicht somit ein frühzeitiges Agieren. Auch der technologische Fortschritt gibt der Marktforschung Auftrieb. Neben klassischen Erhebungsmethoden wie zum Beispiel der Kundenbefragung lassen sich wertvolle Markterkenntnisse aus der Verknüpfung von Scannerdaten mit Kundenkartendaten erschliessen. Es stehen heute den meisten Unternehmen weit mehr Marktinformationen als vor zehn Jahren zur Verfügung. Doch ist es damit auch gelungen, die Kundenzufriedenheit zu steigern?
Patterns of choice behavior have been examined in retailing for long with the intention to align marketing instruments to specific customer needs. Predominantly socioeconomic and demographic variables have been constituent in clustering customers in different homogenous target groups. Yet, the tendency of tradition losing its value limits the ability of socioeconomic and demographic aspects to discriminate among consumers (Flemming and Bak-Jensen 1972). New approaches for identification of consumption patterns have been distinctions due to reaction to innovation, lifestyles (e.g. Wells 1975), values (e.g. Mitchell 1978). The distinction of these typologies, however, often rests on uni-dimensional attributes which doubtfully reflects the complexity of the underlying dynamics.
Our studies propose a new approach to segment customers. As some comparable psychographic segmentation methods have already reflected (e.g. Kahle 1983), it can be assumed, that shared psychological profiles determine collective consumption patterns. Research in analysing the relationship between these two variables is far from complete (Fournier Antes and Beaumier 1992). The findings suggest a two step segmentation process whereas customers typologies are portrayed through actual consumption behaviors rather than abstracted constructs (e.g. lifestyles, values), which are believed to support certain in-store customer choice behavior.
As the conceptual foundation, we apply the theory of the Optimum Stimulation Level (OSL) which presumes, that people tend to prefer intermediate levels of stimulation (e.g. Berlyne 1960; Fiske and Maddi 1961). The need for stimulation is thereby operationalized through different personal characteristics such as personal traits, demographic variables and general exploratory tendencies (Raju 1980). These personality variables are crucial to cluster customers in a first step segmentation process. The literature suggests furthermore that the individual OSL affects the degree of exploratory tendencies across many situations. These OSL-specific in-store choice patterns can be revealed and compared to each other (identification of discriminate variables) through verbal-protocol coding schemes (e.g. Bettman 1971; Biehal and Chakravarti 1982). This method (second step segmentation process) subsequently leads to a synthesis between personal traits (OSL) and in-store customer choice behavior. Since these typologies are characterized through stable individual differences (McReynolds 1971; Steenkamp and Baumgartner 1992), the distinction on the basis of the OSL is promising for segmenting customers. Given that the OSL influences the extend of individual curiosity-motivation, variety seeking, risk taking and innovative behavior (e.g. Berlyne 1960), OSL-adapted marketing measures could be effective for augmenting the profile of retail businesses.
It can be emphasized that it is crucial to address the different OSL-categories properly. There is a general agreement, that if external stimuli (e.g. information overload or conflicting messages) disturb the individual's OSL, their behavior gets disrupted as well (Raju and Venkatesan 1980). Deviations from the optimum leads either to stimulus seeking or avoidance behavior - this in order to maintain the OSL. For the draft of retail strategy these findings imply, that sophisticated marketing measures tempt to confuse customers (especially the ones with low OSLs) whereas slight assortment variety tends to bore individuals (especially the ones with high OSLs) in the retail store. Confused or bored customers are inclined to abort the buying decision process or to switch brands/retail stores respectively. These kinds of reactions cause consumer buying tiredness and lead consequently to lower revenues for retailers.
To summarize our conceptual findings: Through segmenting consumers by their OSL it is possible to address customers in such a way, that the individual obtains exactly as much stimuli as he requires to maintain a pleasant level of stimuli (OSL). Due to this segmenting method, it is possible to retain customers by means of customer-oriented measures without confusing or boring them.
