Private labels – customer profile and changes in trade during pandemic

• Autorzy: Slabá Marie

Identyfikatory

DOI

10.29119/1641-3466.2021.154.22

• Języki publikacji: EN

Abstrakty

EN

Purpose: This article focuses on private labels, which play a crucial role in the retail market. This article aims to examine the market of private labels in the Czech Republic and reveal the customer profile of private labels in the Czech market. Design/methodology/approach: This article incorporates the results of the author's research devoted to various aspects of private labels and trade. The author used an online questionnaire for the research. This questionnaire was divided into several parts and prepared based on the literature search of statistics, reports, papers, and scientific studies. Findings: Large retail chains can achieve more than 30% of sales from private labels. The nature of the private label market is changing significantly. Therefore, the customer profile is changing too. The author's research revealed that the most critical segment for private labels is women, specifically single women with an income of up to 20,000 CZK, aged under 27-36, who live in medium-sized cities with up to 100,000 inhabitants. Research limitations/implications: In the current Covid-19 pandemic, the results can contribute to more effective collaboration with customers. In the future, it is intended to develop research on other aspects that affect the operation of private labels. Practical implications: It is clear from the research results that large retail chains should focus on certain specific segments, especially women with the above profile. According to research, this segment is the most crucial segment for retail chains and should focus on it. Originality/value: The article focuses on the changes during the Covid-19 pandemic. At this time, there were changes in shopping behavior, which are listed in the article.

Słowa kluczowe

EN

private label; customer profile; retail; customer

PL

marka własna; profil klienta; sprzedaż detaliczna; klient

• Wydawca: Wydawnictwo Politechniki Śląskiej
• Czasopismo: Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska
• Rocznik: 2021
• Tom: z. 154
• Strony: 291--303
• Opis fizyczny: Bibliogr. 23 poz.

Twórcy

autor

Slabá Marie

• College of Polytechnics Jihlava, Czech Republic

• https://orcid.org/0000-0001-9607-1521

Bibliografia

• 1. Chao, P. et al. (2008). Identifying the Customer Profiles for 3c-product Retailers: A Data Mining Approach. International Journal of Electronic Business Management, 6(4), pp. 195-202.
• 2. Cordo, J. (2012). Align S&M Teams. Sales & Service Excellence Essentials, 12(10), pp. 4-14.
• 3. Cuneo, A. et al. (2015). The growth of private label brands: A worldwide phenomenon? Journal of International Marketing, 23(1), pp. 72-90.
• 4. Eurostat (2021a). EU, development of retail trade volume. January 2020 – March 2021. Retrieved from https://ec.europa.eu/eurostat/statistics-explained/index.php?title=File:EU, _development_of_retail_trade_volume,_January_2020_-_March_2021_.png.
• 5. Eurostat (2021b). EU, development of retail trade volume during the Covid-19 crisis May 2021. Retrieved from https://ec.europa.eu/eurostat/statistics-explained/images/a/a1/EU %2C_development_of_retail_trade_volume_during_the_Covid-19_crisis_May_2021.png.
• 6. Grosso, M., and Castaldo, S. (2015). Private Labels and National Brands: A Comparison Within Brand Extension. Advances in National Brand and Private Label Marketing Springer Proceedings in Business and Economics, pp. 95-102.
• 7. Hassan, M.M., Tabasum, M. (2018). Customer Profiling and Segmentation in Retail Banks Using Data Mining Techniques. International Journal of Advanced Research in Computer Science, 9(4), pp. 924-29.
• 8. Janssen, M., and Hamm, U. (2014). Governmental and private certification labels for organic food: Consumer attitudes and preferences in Germany. Food Policy, 49, pp. 437-448.
• 9. Julashokri, M. et al. (2011). Improving electronic customers' profile in recommender systems using data mining techniques. Management Science Letters, 1(2011), pp. 449-456.
• 10. Kadirov, D. (2020). Private labels ain't bonafide! Perceived authenticity and willingness to pay a price premium for national brands over private labels. Journal of Marketing Management, 31(17-18), pp. 1773-1798.
• 11. Lee, K.S., Yo, H., and Chung, S-Y. (2011). A Customer Profile Model for Collaborative Recommendation in e-Commerce. The Journal of the Korea Contents Association, 11(5), pp. 67-74.
• 12. Park, Y.J., Chang, K.N. (2009), Individual and group behavior-based customer profile model for personalized product recommendation. Expert Systems with Applications, 36(2), pp. 1932-1939.
• 13. Planiappan, S. et al. (2017). Customer Profiling using Classification Approach for Bank Telemarketing. International Journal on Informatics Visualization, 1(4-2), pp. 214-217.
• 14. Prasad, P., Malik, L.G. (2011). Generating Customer Profiles for Retail Stores Using Clustering Techniques. International Journal on Computer Science and Engineering (IJCSE), 3(6), pp. 2506-2510.
• 15. Risch, D., Schubert, P. (2005). Customer Profiles, Personalization and Privacy. Proceedings of the CollECTeR 2005 Conference, Furtwangen. Retrieved from https://www.researchgate.net/publication/242263870_Customer_Profiles_Personalization_and_Privacy.
• 16. Statista (2021a). world: retail sales 2018-2022. Available at https://www.statista.com/ statistics/443522/global-retail-sales/.
• 17. Statista (2021b). Private label share of supermarkets' sales volume in Europe 2020, by country. Retrieved from https://www.statista.com/statistics/1194649/private-label-share-of-total-supermarkets-sales-volume-europe/.
• 18. Syakur, M.A. et al. (2018). Integration K-Means Clustering Method and Elbow Method For Identification of The Best Customer Profile Cluster. IOP Conf. Series: Materials Science and Engineering, volume 336. The 2nd International Conference on Vocational Education and Electrical Engineering (ICVEE) 9 November 2017, Surabaya, Indonesia. Retrieved from https://iopscience.iop.org/article/10.1088/1757-899X/336/1/012017.
• 19. The Nielsen Company (2018). The rise and rise again of private label. Retrieved from https://www.nielsen.com/wp-content/uploads/sites/3/2019/04/global-private-label-report.pdf.
• 20. Upadhyay, T., Vidhani, A., Dadhich, V. (2016). Customer Profiling and Segmentation using Data Mining Techniques. IJCSC, 7(2), 65-67.
• 21. Vasilev, J. (2014). Creating a Customer Profile in a Credit Institution. International Journal of Advanced Research in Computer Science and Software Engineering, 4(1), pp. 1108-111.
• 22. Wehmeyer, K. (2005). Aligning IT and marketing The impact of database marketing and CRM. Journal of Database Marketing & Customer Strategy Management, 12(3), pp. 243-256.
• 23. Wu, J. et al. (2007). Research on Customer Profile Integration of Telecom Enterprises Based on Ontology. Conference: Research and Practical Issues of Enterprise Information Systems II, Volume 1. IFIP TC 8 WG 8.9 International Conference on Research and Practical Issues of Enterprise Information Systems (CONFENIS 2007), October 14-16, 2007, Beijing, China. Retrieved from https://www.researchgate.net/publication/221296752_ Research_on_Customer_Profile_Integration_of_Telecom_Enterprises_Based_on_ Ontology.