Social-Data Driven Sales Processes in Local Clothing Retail Stores
Local clothing retailers compete with online retailers but have difficulties to increase cross-selling revenues. Therefore, a data-driven sales process is conceptualized that uses data from social software in order to increase revenue. It identifies and t
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Hochschule München, Lothstr. 64, 80335 Munich, Germany [email protected] 2 Hochschule Aalen, Beethovenstr. 1, 73430 Aalen, Germany {Barbara.Keller,Michael.Moehring, Ralf.Haerting}@hs-aalen.de Reutlingen University, Alteburgstr. 150, 72762 Reutlingen, Germany [email protected]
Abstract. Local clothing retailers compete with online retailers but have difficulties to increase cross-selling revenues. Therefore, a data-driven sales process is conceptualized that uses data from social software in order to increase revenue. It identifies and tracks the customer using RFIDs in customer loyalty cards. By these means, social data can be used in all phases of the purchase and both for major and minor purchases. Individual product suggestions and offerings can be tailored. Local retailers are able to catch up with online retailers in their cross- and upselling revenues. In consequence, local retailers are able to stay competitive. Keywords: Social BPM Retail Data driven Local retailers software Social data Sales processes Clothing retail store
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1 Introduction The clothing retail sector is an important part of the German economy with revenues of 59 billion euro [Hand13] and grows continuously. In particular buyers of higher priced clothes, appreciate competent advice in a specialist shop and therefore usually avoid online retailers [Derh00, KeHa06]. Furthermore, consumer spending for clothing is constantly increasing, which affects positively the clothing industry as a whole [Dest13]. Local retailers compete more and more with online retailers like Amazon, Zappos or Rakuten. On the one hand, local retailers have not to cope with expensive product returns [WMKS14] as online retailers. On the other hand, retailers with classic branches have difficulties to increase cross-selling revenues unlike established online retailers such as Amazon.de, Zalando or the Otto Group. This is associated with shrinking revenues and decreasing customer contacts. The reason is that consumers and their interests often cannot be analyzed (in contrast to online shops with purchases and search history). This phenomenon is similar for local retailers outside Germany. Local retailers should implement more customer-oriented sales processes and focus on their individual core competencies like product guidance and mentoring as well as (after sales) service. © Springer International Publishing Switzerland 2016 M. Reichert and H.A. Reijers (Eds.): BPM Workshops 2015, LNBIP 256, pp. 305–315, 2016. DOI: 10.1007/978-3-319-42887-1_25
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Therefore, this paper addresses the research question: how local retailers can improve sales business processes using social BPM. The paper is structured as follows. First, the basic paradigms of social BPM are discussed. Then the effects of Big Data and RFID are analyzed. We then introduce a data-driven sales architecture for local retailers. Based on it, we show how social BPM is leveraged for improving sales processes. Finally, we discuss related work and give an
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