Segmentation of multiple retailers’ clients on the basis of shopping occasions


Rapid development of a retailing sector and the emergence of multiple retailers (also called chain stores or chains of stores) significantly increased the power of retailers over other members of products distribution channels. Large retailers, and especially chain stores become more and more independent from manufacturers and suppliers, take over the functions of wholesalers, make orders for manufacturing private label (or store brand) products, take part in product manufacturing processes. The implementation of modern information technologies enables multiple retailers to manage information about customers, their habits and demands of various products. The usage of this information allows multiple retailers to make a purposeful impact on customers’ behaviour by using various marketing tools. The development of retail companies and chain stores also increases competition among retailers themselves. Therefore retailers pay more attention to the analysis of competitors and search of new competitive strategies. Positioning concept is being implemented in retailing for assuring differentiation and positive opinion of customers. Besides that, intensive competition among retailers forces them striving to address customers’ needs better. Therefore segmentation, targeting and evaluation of target segment(s) customers’ needs and requirements become very important. In case of multiple retailers, segmentation procedures are quite complicated because chain stores most often seek to serve the largest possible group of customers. Therefore traditional segmentation, based on demographic, geographic and psychographic criteria here is not fully suitable. For this reason more attention should be paid towards segmentation that is based on customer behaviour. This issue is not yet comprehensively analyzed and not many empirical surveys are performed yet. This article analyses the possibilities to segment markets on the basis of shopping occasions. The analysis concentrates on customers of chain stores that are operating in Lithuania. Data were collected during two surveys. The first one was qualitative, and it included a set of in-depth interviews with customers. The second was quantitative and it was performed as a part of National Omnibus survey. Both surveys took place in July – August, 2004. The research results allowed defining several typical shopping occasions. These shopping occasions can be characterized by the type of needed products, their quantity and shopping frequency. Depending on the specifics of the concrete needs at the moment, the same customers experience various needs and this triggers different shopping occasions. Then they relate specific shopping occasion with the types and brands of their known retail outlets. Customers were able to even name the chain stores, which in their opinion were the most suitable for a particular shopping occasion. The fact that the majority of customers occurs in several buying occasions and prefers different stores allows concluding that a ‘customer share’ concept can be very much applicable in retailing. Supporting the idea of differentiation, this concept could help understanding, evaluating and satisfying customers’ needs better. As a result, retailers can improve their overall competitive positions. The results allow claiming that segmentation of multiple retailers’ customers on the basis of shopping occasions is efficient and deserves more attention from managers of chain stores. It is important to further analyse the possibilities of segmentation according to shopping occasions in retailing, thus broadening traditional segmentation according to demographic, geographic and psychographic characteristics of retail customers. Possibly, the list of initially defined shopping occasions has to be expanded or changed. Finally, a similar survey of chain stores operating in the other retail sectors would help evaluate whether the concept is applicable under broader circumstances.

Article in Lithuanian.

Parduotuvių tinklų pirkėjų segmentavimas pagal pirkimo progas

Santrauka. Intensyvi konkurencija tarp mažmeninės prekybos įmonių skatina geriau tenkinti pirkėjų poreikius. Todėl labai aktualūs tampa pirkėjų segmentavimo klausimai, siekiant išskirti tikslinį segmentą ir nustatyti jo poreikius bei reikalavimus. Tradiciniai demografiniai, geografiniai ir psichografiniai segmentavimo kriterijai gerai tinka tik segmentuojant santykiškai nedidelės ar siauriau specializuotos mažmeninės prekybos įmonės pirkėjus. Didelės mažmeninės prekybos įmonės ir parduotuvių tinklai teikia paslaugas daugybei pirkėjų, kurie pasižymi įvairiomis socialinėmis, demografinėmis bei psichografinėmis charakteristikomis. Šiuo atveju vien tradicinių išorinių segmentavimo kriterijų nebepakanka. Todėl straipsnyje nagrinėjami segmentavimo pagal pirkėjų elgseną klausimai. Tyrimų objektu pasirinkus parduotuvių tinklų pirkėjų elgseną, buvo siekiama įvertinti tinklų pirkėjų segmentavimo pagal pirkimo progą (angl. buying occasion) galimybes. Tyrimų rezultatai atskleidė, kad gali būti išskirtos tam tikros pirkimo progos, kurias galima apibūdinti įsigyjamų prekių pobūdžiu, kiekiu ir apsipirkimo dažnumu, atspindinčios skirtingus pirkėjų poreikius. Paprastai pirkėjai kiekvienai pirkimo progai renkasi geriausiai jas atitinkančias parduotuves, kurios gali skirtis savo tipu ir dydžiu. Tokios išvados leidžia kalbėti apie pirkėjo dalies (arba pirkėjo išlaidų dalies) koncepcijos taikymą parduotuvių tinklų pirkėjų elgsenai nagrinėti. Taigi parduotuvių tinklų pirkėjų segmentavimą pagal pirkimo progas galima laikyti veiksmingu, nors jis kol kas nėra naudojamas tinklų veikloje.

Pagrindiniai žodžiai: mažmeninė prekyba, parduotuvių tinklas, segmentavimas, diferenciacija, pirkimo proga, pirkėjo išlaidų dalis.

Keyword : retailing, multiple retailer, segmentation, differentiation, shopping occasion, customer share

How to Cite
Urbonavičius, S., & Ivanauskas, R. (2006). Segmentation of multiple retailers’ clients on the basis of shopping occasions. Business: Theory and Practice, 7(1), 37-44.
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Mar 27, 2006
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