RECYCLING PROJECT WITH RFM ANALYSIS IN INDUSTRIAL MATERIAL SECTOR

With the advancement of technology and the widespread use of the Internet, the concept of big data, which we are often beginning to hear its name, has emerged. Big data can be briefly defined as an unstructured data stack. It aims to transform the data collected from different sources into a meaningful and processable format. One of these methods is RFM analysis. RFM analysis is an effective and practical marketing model that combines the initials of Recency Frequency and Monetary and performs behavioral customer segmentation. In this study, the importance of RFM analysis was emphasized. How to use RFM analysis in estimation models is explained in detail.The applicability of RFM analysis to the recycling project has been demonstrated. The operation of the model and the application of RFM to recycling projects are shown in the original retail data of a company operating in the metal industry. Therefore, they were encouraged to participate in recycling. According to the contribution rate of recycling, it is aimed to establish a profitable relationship between the customer and the company by applying discounts to the customers.

___

  • Katie Fisher, (March 19th, 2020), UK Statistics on Waste, UK.
  • Brian D. James & Jennie M. Moton & Whitney G. Colella, (May 14th, 2013). U.S. Department of Energy's (DOE's) Annual Merit Review and Peer Evaluation Meeting (AMR) for the Hydrogen and Fuel Cell Technologies (FCT) Program, Arlington, Virginia.
  • Anthony Kasozi, (2016). A Recycle Analysis for Converting Used Oil into Diesel to Support the Power System During the Drilling Process, SPE Nigeria Annual International Conference and Exhibition, 2-4 August, Lagos, Nigeria, ISBN: 978-1-61399-487-0, United States of America.
  • Internet: Recycle Mania 2009 Hits Otterbein Campus, (2009).https://www.thisweeknews.com/content/ stories/⦁ westerville⦁ /news/2009/01/21/0122wvrecyclemania_ln.html
  • Internet: Olipot in Barcelona Cooking Oil is Recycled!, (2016).https://www.livingcircular.veolia.com/en/eco-citizen/olipot-barcelona-cooking-oil-recycled
  • Internet: Recycling Reverse Vending Machine(2014).https://reversevending.wordpress.com/2013/09/16/ the-history-of-reverse-vending-1920-to-2013/
  • Internet: How Companies Learn Your Secrets(2012).https://www.nytimes.com/2012/02/19/magazine/ shopping-habits.html
  • Bult. J. R. & Wansbeek. T.. “Optimal selection for direct mail”. Marketing Science. Vol. 14. No. 4. (1995) 378-394. ISSN: 0732-2399.
  • Hosseini, S.M.; Maleki, A. Gholamian, M.R. (2010). Cluster analysis using data mining approach to develop CRM methodology to assess the customer loyalty, Expert Systems with Applications, Vol. 37, No. 7, (July 2010) 5259-5264, ISSN:0957-4174.
  • Chuang, H. & Shen, C. (2008). A study on the applications of data mining techniques to enhance customer lifetime value – based on the department store industry, Proceedings of the 7th International Conference on Machine Learning and Cybernetics, pp. 168-173, ISBN:978-1424420964, Kunming, China, July 2008, IEEE.
  • Ha, S.H. (2007). Applying knowledge engineering techniques to Customer analysis in the service industry, Advenced Engineering Informatics, Vol. 21, No.3, (July 2007) 293-301, ISSN:1474-0346.
  • Derya Birant (2011). Data Mining Using RFM Analysis, Knowledge-Oriented Applications in Data Mining, Prof. Kimito Funatsu (Ed.), ISBN: 978-953-307-154-1, InTech.
  • Internet: Yenilik analizi, Sıklık analizi ve Parasal (RFM) analiz ayarlama, (2017). https://docs.microsoft.com/tr-tr/dynamics365/unified-operations/retail/set-up-rfm-analysis
  • Internet: IBM Watson Studio ile yapay zekanın gücünden istediğiniz ölçekte yararlanın.https://www.ibm.com/tr-tr/marketplace/watson-studio.