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B2B Customers Buying Behavior

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EN
Purpose – The presented paper aims to characterize the main differences and similarities between B2B as well as the commercial customers buying behaviors. Design/Methodology/Approach – The authors’ approach is based on the literature and research review, concerning the B2B customers buying behaviors. The authors assess buying behavior of professional clients. Findings – Based on the analysis, we can find out that the use of electronic means of cooperation between the companies continues to grow in strength and dynamics. It seems that the distribution model, where the supplier runs his own B2B shop, maintains its position only in case of strong market players. Small and weak players will use the universal marketplaces. We observe growing “self-service with everything”; providers will pass on to buyers and systems, most actions which they can perform by themselves. Practical implications – The outcome of the analysis can teach managers to act on the B2B electronic markets, how to organise the multi-channel sale systems and how these systems can be used by both, commercial and business customers. Original value – The original value of the paper is that we have presented the general analysis of possible future expectations of B2B business customers, as well as those customers buying behaviors which regard to the use of the omnichannel sale. Article type – Research and literature general review.
EN
The paper presents the problem of identifying groups of customers for marketing purposes based on their purchasing activity. We discuss the problem of highlighting key customers and the expectations of the customer life cycle using the RFM method (Recency, Frequency, Money). Classification results were compared with each other based on Customer Profitability (CP) calculated by cost sharing using the ABC method. The experience of companies is that in the early stages of cooperation, customers show a quite considerable unprofitability. The study involved the purchasing activity of more than 1000 customers of trading companies. It included behavioral parameters: the period since the last purchase (Recency), purchase frequency (Frequency) and the level of spending (Money) and the overall rate of RFM analyzed for each customer. Then, clients were assigned to specific groups and compared with the profitability of the group and the average profitability of clients in the group. Segmentation was supplemented by an analysis of the number of transactions and sales in established classes of customers. Presented analyses were performed using actual transaction data of the 12-month period, obtained by a distribution channel website. The authors formulated a way of interpreting the data and recommendations for marketing activities with a focus on groups that emerged from the customers.
PL
W publikacji przedstawiono zagadnienie identyfikacji grup klientów do celów marketingowych na podstawie ich aktywności zakupowej. Podjęto problem wyróżniania klientów kluczowych oraz przewidywań co do cyklu życia klienta z wykorzystaniem metody RFM (Recency, Frequency, Money). Wyniki klasyfikacji porównano rentownością klientów (Customer Profitability – CP) obliczoną podziałem kosztów metodą ABC. Z doświadczeń przedsiębiorców wynika, że we wczesnych fazach współpracy klienci wykazują dosyć znaczną nierentowność. Badaniu poddano aktywność zakupową ponad 1000 klientów przedsiębiorstwa handlowego. Określono w nim behawioralne parametry: okres od dokonania ostatniego zakupu (Recency), częstotliwość zakupów (Frequency) i poziom wydatków (Money) oraz całościowy wskaźnik RFM dla każdego analizowanego klienta. Następnie przypisano klientów do określonych grup, porównano z rentownością grupy oraz średnią rentownością klientów w grupie. Segmentacja ta została uzupełniona o analizę liczby transakcji i wartość sprzedaży w utworzonych klasach klientów. Prezentowane analizy wykonano z wykorzystaniem rzeczywistych danych transakcyjnych firmy z okresu 12 miesięcy, uzyskiwanych przez kanał dystrybucji internetowej. Autorzy sformułowali sposób interpretacji danych, a także zalecenia dotyczące działań marketingowych z ukierunkowaniem na wyłonione grupy klientów.
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