Perakende Sektöründe Kayıp Müşteri Yönetimi: Bir Vaka Çalışması
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Date
2022
Authors
Gülmüş Börühan
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GOLD
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Abstract
Perakende sektörü küresel olarak gelişmekte olan endüstriler arasında yer almakta uygulayıcılar ve akademisyenler tarafından artan bir ilgi görmektedir. Perakende çevresi hızla değişmekte ve hem yerli hem de yabancı şirketlerden gelen büyük rekabet ile karakterize edilmektedir. Firmaların çoğu özdeş mallar üretmekte ve bunları rekabetçi fiyatlarla satmaya çalışmaktadır. Bu bağlamda yeni müşteriler bulmak ve onları sadık kılmak perakende sektörünün en zor işlerinden biridir. Firmalar için yeni müşteri bulmak eski müşteriyi elde tutmaktan beş kat daha pahalıya mal olmaktadır. Bu nedenle müşteriyi elde tutma kavramı akademik literatürde yeni bir terim olan “Kayıp Müşteri Yönetimi” nin ortaya çıkmasına neden olmuştur. Bu çalışmanın amacı Perakendeci X'in İzmir'in farklı bölgelerinde bulunan düşük ve yüksek verimli mağazalarını veri zarflama analizi yaparak analiz etmek ve ardından bu mağazalardaki müşteri kaybının nedenlerini hem müşteriler hem de mağaza yöneticileri açısından incelemektir. Düşük ve yüksek verimli mağazaları bulmak için veri zarflama analizi yapmak üzere Perakendeci X'ten veriler toplanmıştır. Bir sonraki aşamada her iki tarafın algılarını karşılaştırabilmek için hem mağaza yöneticileri hem de müşterilerle yarı yapılandırılmış görüşmeler yapılmıştır. Bu görüşmeler sonucunda müşteri kaybı nedenleri ürün ve stok düzeyi fiyat promosyonlar fiziksel mağaza atmosferi satış personelinin etkileşimi satış sonrası hizmetler ve rakipler olmak üzere 7 grupta sınıflandırılmıştır.
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ORCID
Keywords
İşletme, kayıp müşteri, retail management, Churn Customer;Churn Customer Management;Retail Management;Data Envelopment Analysis;Semi Structured Interview, churn customer management, veri zarflama analizi, churn customer, semi structured interview, yarı yapılandırılmış görüşme, Economics as a science, İşletme, Kayıp Müşteri;Kayıp Müşteri Yönetimi;Perakende Yönetimi;Veri Zarflama Analizi;Yarı Yapılandırılmış Görüşme, perakende yönetimi, data envelopment analysis, HB71-74, kayıp müşteri yönetimi, Business Administration
Fields of Science
05 social sciences, 02 engineering and technology, 0502 economics and business, 0202 electrical engineering, electronic engineering, information engineering
Citation
Amin A. Anwar S. Adnan A . Nawaz M. Alawfi K. Hussain A. & Huang K. (2017). Customer churn prediction in the telecommunication sector using a rough set approach. Neurocomputing 237 242-254.Arslan İ. K. & Ersun N. (2011). Moda sektöründe faaliyet gösteren mağazalarda müşterilerin mağaza tercihinde mağaza tasarımının önemi ve tasarım kriterleri Istanbul Ticaret Üniversitesi Sosyal Bilimler Dergisi. 10(19) 221-245.Bagul N. Surana P. Berad P. & Khachane C. (2021).Retail Customer Churn Analysis using RFM Model and K-Means Clustering International Journal of Engineering Research & Technology (IJERT) 10(3).Barros C. P. & Alves C. A. (2003). Hypermarket retail store efficiency in Portugal. International Journal of Retail & Distribution Management 31 549–560.Berman B. and Evans J.R. (2004). Retail Management: A Strategic Perspective Pearson Prentice Hall Upper Saddle River NJ.Bharti A. (2017). Customer churn management. ACADEMICIA: An International Multidisciplinary Research Journal 7(5) 96-102.Bi W. Cai M. Liu M. & Li G. (2016). A big data clustering algorithm for mitigating the risk of customer churn. IEEE Transactions on Industrial Informatics 12(3) 1270-1281.Buttle F. (2004). Customer relationship management. Routledge.Chan K. & Li Q. (2022). Attributes of young adults’ favorite retail shops: a qualitative study. Young Consumers (ahead-of-print).Dabholkar P. A. Thorpe D. I. & Rentz J. O. (1996). A measure of service quality for retail stores: scale development and validation. Journal of the Academy of Marketing Science 24(1) 3.Deekshitha M. A. Udaya Kumar & M. D. Pradeep (2017). A Study on Changing Consumer Behaviour towards Fast Moving Consumable Goods in India. International Journal of Multidisciplinary Research and Modern Education (IJMRME) 3(1) 392-398.Donthu N. & Yoo B. (1998). Retail productivity assessment using data envelopment analysis. Journal of Retailing 74(1) 89-105.Filimonau V. Zhang H. and Wang L. (2020). Food waste management in Shanghai full-service restaurants: a senior managers’ perspective. Journal of Cleaner Production Vol. 258 pp. 1-13.Gagliano K. B. & Hathcote J. (1994). Customer expectations and perceptions of service quality in retail apparel specialty stores. Journal of Services Marketing 8(1) 60-69.Gülpinar V. (2013). Yapay Sinir Ağlari Ve Sosyal Ağ Analizi Yardimi İle Türk Telekomünikasyon Piyasasinda Müşteri Kaybi Analizi. Marmara Üniversitesi İktisadi ve İdari Bilimler Dergisi 34(1) 331-350.Hadden J. Tiwari A. Roy R. & Ruta D. (2007). Computer assisted customer churn management: State-of-the-art and future trends. Computers & Operations Research 34(10) 2902-2917.Huang Y. Zhu F. Yuan M. Deng K. Li Y. Ni B. Dai W. Yang Q. & Zeng J. (2015) Telco Churn Prediction with Big Data. SIGMOD Conference 2015.Hung S. Y. Yen D. C. & Wang H. Y. (2006). Applying data mining to telecom churn Management. Expert Systems with Applications 31(3) 515-524.Idris A. Rizwan M. and Khan A. (2012) Churn Prediction in Telecom Using Random Forest and PSO Based Data Balancing in Combination with Various Feature Selection Strategies. Computers & Electrical Engineering 38 1808- 1819.Johny C. P. & Mathai P. P. (2017). Customer churn prediction: A survey. International Journal of Advanced Research in Computer Science 8(5) 2178-2181.Karakaya F. & Ganim Barnes N. (2010). Impact of online reviews of customer care experience on brand or company selection. Journal of Consumer Marketing 27(5) 447-457.Kaya S. Williams B. (2005). Effective churn management for business. Journal of Corporate Real Estate 7(2) 154-163.Keramati A. Ghaneei H. & Mirmohammadi S. M. (2016). Developing a prediction model for customer churn from electronic banking services using data mining. Financial Innovation 2(1) 1-13.Keramati A. Jafari-Marandi R. Aliannejadi M. et al. (2014).Improved Churn Prediction in Telecommunication Industry Using Data Mining Techniques. Applied Soft Computing 24 994-1012.Kim S.Y. Staelin R. (1999). Manufacturer allowances and retailer pass-through rates in a competitive environment. Marketing Science 18 (1) 59–76.Khan A.A, Jamwal S. & Sepehri M.M. (2010). Applying Data Mining to Customer Churn Prediction in an Internet Service Provider. International Journal of Computer Applications 9(7) 8-14.Ko K. Chang M. Bae E. S. & Kim D. (2017). Efficiency analysis of retail chain stores in Korea. Sustainability 9(9) 1-14.Koca Y. Söğüt B. E. ve Mardikyan S. (2019). Sadakat Programında Müşteri Kayıp Tahmini: Bir Vaka Çalışması. Journal of Information Systems and Management Research 1(1) 59-66.Lau K. H. (2012). Distribution network rationalisation through benchmarking with DEA. Benchmarking: An International Journal 19(6) 668-689.Lejeune M. A. (2001). Measuring the impact of data mining on churn management. Internet Research" 11(5) 375-387.Leroi-Werelds S. (2021). Conceptualising Customer Value in Physical Retail: A Marketing Perspective. In The Value of Design in Retail and Branding. Emerald Publishing Limited.Lindlof T.R. & Taylor B. C. (2002). Qualitative Communication Research Methods. (2nd Ed.) California: Sage Publication.Liu Y. Cheng S. Liu X. Cao X. Xue L. and Liu G. (2016). Plate waste in school lunch programs in Beijing China Sustainability 8(12) 1288-1300.Magaldi D. and Berler M. (2020).Semi-structured Interviews. In: Zeigler-Hill V. Shackelford T.K. (eds) Encyclopedia of Personality and Individual Differences Springer.McDonald L. M. & Rundle Thiele S. (2008). Corporate social responsibility and bank customer satisfaction: a research agenda. International Journal of Bank Marketing 26(3) pp. 170-182.Miguéis V. L. Camanho A. & e Cunha J. F. (2013). Customer attrition in retailing: an application of multivariate adaptive regression splines. Expert Systems with Applications 40(16) 6225-6232.Miles M. B. & Huberman A. M. (1994). Qualitative data analysis: An expanded sourcebook. Sage.Mutanen T. (2006). Customer churn analysis–a case study. Journal of Product and Brand Management 14(1) 4-13.Oghojafor B. Mesike G. Bakarea R. Omoera C. & Adeleke I. (2012). Discriminant analysis of factors affecting telecoms customer churn. International Journal of Business Administration 3(2) 59-67.Okumus B. (2020).How do hotels manage food waste? Evidence from hotels in Orlando Florida Journal of Hospitality Marketing and Management 29(3) 291-309.Orac R. (2019). Churn prediction: Learn how to train a decision tree model for churn prediction https://towardsdatascience.com/churn-prediction-770d6cb582a5Patil A. P. Deepshika M. P. Mittal S. Shetty S. Hiremath S. S. & Patil Y. E. (2017 August). Customer churn prediction for retail business. In 2017 International Conference on Energy Communication Data Analytics and Soft Computing (ICECDS) (pp. 845-851). IEEE.Perdikaki O. Kesavan S. & Swaminathan J. M. (2012). Effect of traffic on sales and conversion rates of retail stores. Manufacturing & Service Operations Management 14(1) 145-162.Perrigot R. & Barros C. P. (2008). Technical efficiency of French retailers. Journal of Retailing and Consumer Services 15(4) 296-305.Petermans A. & Kent T. (2017). Retail design: Theoretical perspectives. Oxon: Routledge.Rao S. Goldsby T. J. & Iyengar D. (2009). The marketing and logistics efficacy of online sales channels. International Journal of Physical Distribution & Logistics Management 39(2) 106-130.Ridge M. Johnston K.A & O'Donovan B. (2015). The use of big data analytics in the retail industries in South Africa 9(19) 688-703.Saricam C. (2022). Analysing Service Quality and Its Relation to Customer Satisfaction and Loyalty in Sportswear Retail Market. Autex Research Journal 22(2) 184-193.Seker S. E. (2016). Müşteri Kayıp Analizi (Customer Churn Analysis). YBS Ansiklopedi 3(1) 26-29.Sellers Rubio R. & MasRuiz F. (2006). Economic efficiency in supermarkets: evidences in Spain. International Journal of Retail & Distribution Management 34 155–171.Shapiro C.(1982). Consumer information product quality and seller reputation. 13(1) 20-35.Sherman H. D. Zhu J.(2006). Service Productivity Management, Improving Service Performance using Data Envelopment Analysis (DEA). 49-89.Subramanya K.B. (2016). Enhanced feature mining and classifier models to predict customer churn for an e-retailer\".Graduate Theses and Dissertations. Iowa State University 16023.Thomas R. R. Barr R. S. Cron W. L. & Slocum Jr J. W. (1998). A process for evaluating retail store efficiency: a restricted DEA approach. International Journal of Research in Marketing 15(5) 487-503.Tsai C-F Chen M-Y (2010). Variable selection by association rules for customer churn prediction of multimedia on demand. Expert Syst Appl 37:2006–2015Uyar A. Bayyurt N. Dilber M. & Karaca V. (2013). Evaluating operational efficiency of a bookshop chain in Turkey and identifying efficiency drivers. International Journal of Retail & Distribution Management 41 331–347.Veningston K. Rao P. V. Selvan C. & Ronalda M. (2022). Investigation on Customer Churn Prediction Using Machine Learning Techniques. In Proceedings of International Conference on Data Science and Applications (pp. 109-119). Springer Singapore.Yu W. & Ramanathan R. (2008). An assessment of operational efficiencies in the UK retail sector. International Journal of Retail & Distribution Management.Zhang T. Feng X. & Wang N. (2021). Manufacturer encroachment and product assortment under vertical differentiation. European Journal of Operational Research 293(1) 120-132.Zhang T. Moro S. & Ramos R. F. (2022). A Data-Driven Approach to Improve Customer Churn Prediction Based on Telecom Customer Segmentation. Future Internet 2022 14 94.Zhu J. (2008). Quantitative Models for Performance Evaluation and Benchmarking: Data Envelopment Analysis with Spreadsheets. Springer.
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İzmir İktisat Dergisi
Volume
37
Issue
4
Start Page
1094
End Page
1118
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