دانلود مقاله انگلیسی رایگان:پیش بینی حفظ مشتری - یک رویکرد یادگیری ماشین - 2020
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  • Forecasting client retention — A machine-learning approach Forecasting client retention — A machine-learning approach
    Forecasting client retention — A machine-learning approach

    سال انتشار:

    2020


    عنوان انگلیسی مقاله:

    Forecasting client retention — A machine-learning approach


    ترجمه فارسی عنوان مقاله:

    پیش بینی حفظ مشتری - یک رویکرد یادگیری ماشین


    منبع:

    Sciencedirect - Elsevier - Journal of Retailing and Consumer Services, 52 (2020) 101918: doi:10:1016/j:jretconser:2019:101918


    نویسنده:

    Satu Elisa Schaeffer⁎, Sara Veronica Rodriguez Sanchez


    چکیده انگلیسی:

    In the age of big data, companies store practically all data on any client transaction. Making use of this data is commonly done with machine-learning techniques so as to turn it into information that can be used to drive business decisions. Our interest lies in using data on prepaid unitary services in a business-to-business setting to forecast client retention: whether a particular client is at risk of being lost before they cease being clients. The purpose of such a forecast is to provide the company with an opportunity to reach out to such clients as an effort to ensure their retention. We work with monthly records of client transactions: each client is represented as a series of purchases and consumptions. We vary (1) the length of the time period used to make the forecast, (2) the length of a period of inactivity after which a client is assumed to be lost, and (3) how far in advance the forecast is made. Our experimental work finds that current machine-learning techniques able to adequately predict, well in advance, which clients will be lost. This knowledge permits a company to focus marketing efforts on such clients as early as three months in advance.
    Keywords: Client retention | Sales forecasting | Machine learning | Prepaid unitary services


    سطح: متوسط
    تعداد صفحات فایل pdf انگلیسی: 9
    حجم فایل: 1577 کیلوبایت

    قیمت: رایگان


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