title: ÐÑÐ¾Ð³Ð½Ð¾Ð·Ð½Ð°Ñ Ð°Ð½Ð°Ð»Ð¸ÑÐ¸ÐºÐ° Ð¼Ð°ÑÐºÐµÑÐ¸Ð½Ð³Ð¾Ð²ÑÑ Ð´Ð°Ð½Ð½ÑÑ Ð¾ÑÐ³Ð°Ð½Ð¸Ð·Ð°ÑÐ¸Ð¸
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: Predictive analytics of organization marketing data
Creators: name: ÐÐ°Ð¶ÐµÐ½Ð¾Ð²Ð°, ÐÐ°ÑÐ¸Ñ
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2022
Subjects: Ð±Ð¸Ð·Ð½ÐµÑ-Ð°Ð½Ð°Ð»Ð¸ÑÐ¸ÐºÐ°
Ð¼Ð°ÑÐºÐµÑÐ¸Ð½Ð³Ð¾Ð²Ð°Ñ Ð°Ð½Ð°Ð»Ð¸ÑÐ¸ÐºÐ°
Ð¿ÑÐ¾Ð³Ð½Ð¾Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ
ÑÐ²Ð¾Ð»ÑÑÐ¸Ð¾Ð½Ð½ÑÐµ ÑÐºÐ¾Ð½Ð¾Ð¼Ð¸ÑÐµÑÐºÐ¸Ðµ Ð¿ÑÐ¾ÑÐµÑÑÑ
Ð°Ð´Ð°Ð¿ÑÐ¸Ð²Ð½ÑÐµ Ð¼ÐµÑÐ¾Ð´Ñ
ÑÑÐ¾Ñ Ð°ÑÑÐ¸ÑÐµÑÐºÐ°Ñ Ð°Ð¿Ð¿ÑÐ¾ÐºÑÐ¸Ð¼Ð°ÑÐ¸Ñ
business analytics
marketing analytics
forecasting
evolutionary economic processes
adaptive methods
stochastic approximation

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description: Theme of the master's thesis: Â«Predictive analytics of organization marketing dataÂ». The purpose of the research is the developing a model for forecasting marketing data to improve the quality of the forecast. Research methods: data analysis, search and systematization of information, mathematical modeling and forecasting, comparative analysis. The main results of the study:Â The theoretical foundations of business analytics have been studied;Â The purpose of the application and the essence of marketing analytics are described;Â A study of the methods of predictive analytics, their application in various fields;Â The problems of forecasting evolutionary economic processes are described;Â Adaptive forecasting methods have been studied;Â The influence of various coefficient values on the quality of forecasts in the method of uneven smoothing has been studied;Â A combined forecasting model has been developed;Â A script has been developed for partial automation of calculations. Scope of results the application of the results of the work to predict evolutionary socio-economic processes. The scientific novelty of research is the development of a combined adaptive predictive model and investigation of the influence of various values of the filter border parameter on the quality of the forecast. Conclusions. The goal of the work has been achieved â a combined model for forecasting marketing data has been developed, all the tasks have been solved. The scope of application of the work results and the scientific novelty of the obtained results are defined.