Identification of advanced data analysis in marketing: A systematic literature review

Aim/purpose – Marketing is an important area of activity for the vast majority of enterprises. Many of them try using marketing data analysis. Both the literature and the practice of many enterprises describe the use of advanced data analysis. However, interpretations of this concept differ. The aim of this paper is to identify the interpretation of advanced data analysis in marketing, in support of decision-making processes applied in the retail trading sector. Design/methodology/approach – The study was conducted using a systematic literature review, suggested by B. Kitchenham (2004), extended by C. Wohlin & R. Prikladniki (2013). This method was modified and expanded through the division of the whole study into two phases. Each phase is intended to facilitate obtaining answers to different important research questions. The first phase constitutes an exploratory study, whose results allow the detailed analysis of the literature in the second phase of the study. Findings – The results of this study of the relevant literature indicate that scholarly pub-lications do not use the phrase ‘advanced data analysis’, and its context is described with the term ‘data analysis’. Another term used broadly within the sphere of data analysis is ‘big data’. The concept of ‘data analysis’ in marketing is focused around the term ‘big data analytics’ and terms linked to the word ‘customer’, such as ‘customer-centric’, ‘customer engagement’, ‘customer experience’, ‘customer targeting service’, and ‘customers classification’. The study of the literature undertaken indicates that marketing employs data analysis in such areas as customer needs identification and market segmentation. Research implications/limitations – The study of the literature review was carried out using selected four databases containing publications, i.e. Web of Science, IEEE, Springer and ACM for the period 2008 to 2018. The research described in the article can be continued in two ways. First, by analysing the literature presented in this paper on advanced data analysis in marketing using the method called snowball sampling. Secondly, the results obtained from the first stage of the study can be used to conduct the study with other databases. Originality/value/contribution – The main contribution of this work is the proposal of modifying the systematic literature review method, which was expanded through the introduction of two phases. This division of two stages is important for conducting studies of literature when there are no clear, established definitions for the concepts being employed. The result of the study is also a set of ordered terms and their meanings that clearly define advanced data analysis in marketing

Klastrowanie i segmentacja klientów i produktów w sprzedaży wielokanałowej firm handlowych działających w e-commerce w segmencie B2B

Given the progressive growth of e-commerce sales and the increasing interest in large-channel sales of business-to-business (B2B) trading companies among researchers and practitioners, the aim of this article was to identify the needs related to clustering and segmentation in B2B trading companies, as well as the techniques currently in use. Issues related to clustering and customer and product segmentation were explored and the most promising research areas for the nearest future identified. The article outlines the main techniques for clustering and segmenting customers and products, and identifies potential areas for further research. From a managerial perspective, the article is useful for companies entering the domain of multi-channel sales to guide their future efforts on methods to increase the value of customer purchases.Ze względu na postępujący wzrost sprzedaży e-commerce oraz rosnące zainteresowanie sprzedażą wielkokanałową firm handlowych w segmencie business-to-business (B2B) wśród naukowców i praktyków celem niniejszego opracowania jest przedstawienie aktualnego przeglądu literatury na temat możliwości zawansowanej analityki (Big data). W szczególności zbadane zostały zagadnienia związane z klastrowaniem i segmentacją klientów i produktów, wskazano, jak temat ten był rozwijany w czasie, oraz zidentyfikowano najbardziej obiecujące obszary badawcze na najbliższą przyszłość. Artykuł oferuje wgląd w główne techniki klastrowania i segmentacji klientów i produktów, jak również wskazuje potencjalne obszary dalszych badań. Z perspektywy menedżerskiej artykuł jest przydatny dla firm wchodzących w sprzedaż wielkokanałową, aby ukierunkować ich przyszłe działania dotyczące metod zwiększania wartości zakupów klientów