Optimization of customer loyalty evaluation algorithm for retail company : доклад, тезисы доклада | Научно-инновационный портал СФУ

Optimization of customer loyalty evaluation algorithm for retail company : доклад, тезисы доклада

Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций

Конференция: International conference "Economy in the modern world" (ICEMW 2018); Kazan; Kazan

Год издания: 2018

Ключевые слова: Bayes formula, customer loyalty, "Behavioral" loyalty, "Perceived" loyalty, evaluation of loyalty

Аннотация: The problem of quantitative estimation of "behavioral" and "perceived" loyalty of clients is considered. The theme of the paper is to study the algorithm for filling segments, based on the Bayes formula. The methods of probability theory, mathematical statistics, cognitive modeling, regression analysis are used. The article proposes the concept of determining the quantitative evaluation of loyalty, combining "behavioral" and "perceived". The findings and results of the study are aimed at the use in retail companies, regardless of their size, specialization and the volume of the client base. In addition, the developed methods can be modified and used for analysis in other areas of business.

Ссылки на полный текст

Издание

Журнал: ADVANCES IN ECONOMICS, BUSINESS AND MANAGEMENT RESEARCH (AEBMR)

Выпуск журнала: 61

Номера страниц: 177-182

Издатель: Atlantis Press

Персоны

  • Tynchenko V.S. (Reshetnev Siberian State University of Science and Technology)
  • Boyko A.A. (Reshetnev Siberian State University of Science and Technology)
  • Kukartsev V.V. (Reshetnev Siberian State University of Science and Technology)
  • Danilchenko Yu.V. (Reshetnev Siberian State University of Science and Technology)
  • Fedorova N.V. (Reshetnev Siberian State University of Science and Technology)

Вхождение в базы данных

Информация о публикациях загружается с сайта службы поддержки публикационной активности СФУ. Сообщите, если заметили неточности.

Вы можете отметить интересные фрагменты текста, которые будут доступны по уникальной ссылке в адресной строке браузера.