title: Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° Ð°Ð½Ð°Ð»Ð¸ÑÐ¸ÑÐµÑÐºÐ¾Ð³Ð¾ Ð²ÐµÐ±-ÑÐµÑÐ²Ð¸ÑÐ° Ð¿ÑÐ¾Ð³Ð½Ð¾Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Ð¾ÑÐ¼ÐµÐ½Ñ Ð·Ð°ÐºÐ°Ð·Ð° Ð´Ð»Ñ Ð¸Ð½ÑÐµÑÐ½ÐµÑ-Ð¼Ð°Ð³Ð°Ð·Ð¸Ð½Ð°
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: Development of an analytical service of order cancellation forecasting for an online store
Creators: name: ÐÐ° Ð¦Ð·ÑÑÐ¸Ð½
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: 2023
Subjects: Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
Ð¿ÑÐµÐ´ÑÐºÐ°Ð·Ð°ÑÐµÐ»ÑÐ½ÑÐµ Ð¼Ð¾Ð´ÐµÐ»Ð¸
ÑÐ»ÐµÐºÑÑÐ¾Ð½Ð½ÑÐ¹ Ð±Ð¸Ð·Ð½ÐµÑ
Ð¾Ð¿ÑÐ¸Ð¼Ð¸Ð·Ð°ÑÐ¸Ñ Ð±Ð¸Ð·Ð½ÐµÑ-Ð¿ÑÐ¾ÑÐµÑÑÐ¾Ð²
machine learning
predictive models
e-business
business process optimization

description: Ð¦ÐµÐ»ÑÑ ÑÐ°Ð±Ð¾ÑÑ ÑÐ²Ð»ÑÐµÑÑÑ Ð²Ð°Ð¶Ð½Ð¾ÑÑÑ ÑÐµÑÐµÐ½Ð¸Ñ Ð¿ÑÐ¾Ð±Ð»ÐµÐ¼Ñ Ð¾ÑÐ¼ÐµÐ½ÐµÐ½Ð½ÑÑ Ð·Ð°ÐºÐ°Ð·Ð¾Ð². ÐÑÐ»Ð¸ ÑÐµÑÐµÐ½Ñ ÑÐ»ÐµÐ´ÑÑÑÐ¸Ðµ Ð·Ð°Ð´Ð°ÑÐ¸: âÐÐ·ÑÑÐ¸ÑÑ ÑÐ¾Ð²ÑÐµÐ¼ÐµÐ½Ð½ÑÐµ Ð¿Ð¾Ð´ÑÐ¾Ð´Ñ Ðº Ð°Ð½Ð°Ð»Ð¸Ð·Ñ ÐºÐ»Ð¸ÐµÐ½ÑÑÐºÐ¸Ñ Ð±Ð°Ð· Ð´Ð°Ð½Ð½ÑÑ. âÐÐ¿Ð¸ÑÐ°ÑÑ Ð¾Ð±ÑÐµÐºÑ Ð°Ð½Ð°Ð»Ð¸Ð·Ð° (Ð¸Ð½ÑÐµÑÐ½ÐµÑ-Ð³Ð¸Ð¿ÐµÑÐ¼Ð°ÑÐºÐµÑ Â«Ð£ÑÐºÐ¾Ð½Ð¾ÑÂ») Ð¸ ÑÑÐ¾ÑÐ¼Ð¸ÑÐ¾Ð²Ð°ÑÑ Ð¿ÑÐ¾ÑÐµÑÑÑ AS-IS Ð¸ TO-BE Ð¿Ð¾ Ð´Ð¾ÑÑÐ°Ð²ÐºÐµ ÑÐ¾Ð²Ð°ÑÐ¾Ð². âÐÑÐ¾Ð²ÐµÑÑÐ¸ Ð°Ð½Ð°Ð»Ð¸Ð· ÑÑÐ½ÐºÐ° Ð°Ð½Ð°Ð»Ð¸ÑÐ¸ÑÐµÑÐºÐ¸Ñ Ð¸Ð½ÑÑÑÑÐ¼ÐµÐ½ÑÐ¾Ð² Ð´Ð»Ñ Ð²ÑÐ±Ð¾ÑÐ° Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½Ð¾Ð³Ð¾ Ð¸Ð½ÑÑÑÑÐ¼ÐµÐ½ÑÐ° Ð´Ð»Ñ Ð²ÑÐ¿Ð¾Ð»Ð½ÐµÐ½Ð¸Ñ ÑÐ°Ð±Ð¾ÑÑ. âÐ ÐµÑÐ¸ÑÑ Ð¿ÑÐ¾Ð±Ð»ÐµÐ¼Ñ Ð¾ÑÐ¼ÐµÐ½ÐµÐ½Ð½ÑÑ Ð·Ð°ÐºÐ°Ð·Ð¾Ð² Ð¿ÑÐ¸ Ð¿Ð¾Ð¼Ð¾ÑÐ¸ Ð¿Ð¾ÑÑÑÐ¾ÐµÐ½Ð¸Ñ Ð¿ÑÐµÐ´ÑÐºÐ°Ð·Ð°ÑÐµÐ»ÑÐ½Ð¾Ð¹ Ð¼Ð¾Ð´ÐµÐ»Ð¸ Ð¾ÑÐµÐ½ÐºÐ¸ Ð²ÐµÑÐ¾ÑÑÐ½Ð¾ÑÑÐ¸ Ð¸ Ð¾Ð¿Ð¸ÑÐ°Ð½Ð¸Ñ Ð¿ÑÐ¾ÑÐµÑÑÐ° TO-BE. âÐÐ¿Ð¸ÑÐ°ÑÑ Ð¼Ð¾Ð´ÐµÐ»Ñ ÐºÐ°Ðº Ð°Ð½Ð°Ð»Ð¸ÑÐ¸ÑÐµÑÐºÐ¸Ð¹ Ð²ÐµÐ±-ÑÐµÑÐ²Ð¸Ñ. ÐÐºÑÑÐ°Ð»ÑÐ½Ð¾ÑÑÑ ÑÐµÐ¼Ñ Ð¾Ð±ÑÑÐ»Ð¾Ð²Ð»ÐµÐ½Ð° ÑÐµÐ¼, ÑÑÐ¾ Ð½ÐµÐ¾Ð±ÑÐ¾Ð´Ð¸Ð¼Ð° Ð¾Ð¿ÑÐ¸Ð¼Ð¸Ð·Ð°ÑÐ¸Ñ Ð±Ð¸Ð·Ð½ÐµÑ-Ð¿ÑÐ¾ÑÐµÑÑÐ¾Ð² Ð¸Ð½ÑÐµÑÐ½ÐµÑ-Ð¼Ð°Ð³Ð°Ð·Ð¸Ð½Ð¾Ð², Ð·Ð°Ð½Ð¸Ð¼Ð°ÑÑÐ¸ÑÑÑ Ð´Ð¾ÑÑÐ°Ð²ÐºÐ¾Ð¹ Ð¿ÑÐ¾Ð´ÑÐºÑÐ¾Ð² Ð¿Ð¸ÑÐ°Ð½Ð¸Ñ, Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð¼Ð¾Ð´ÐµÐ»ÐµÐ¹ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ, Ð´Ð»Ñ ÑÐ½Ð¸Ð¶ÐµÐ½Ð¸Ñ ÑÐ±ÑÑÐºÐ¾Ð², ÑÐ²ÑÐ·Ð°Ð½Ð½ÑÑ Ñ Ð¾ÑÐ¼ÐµÐ½Ð°Ð¼Ð¸ ÐºÐ»Ð¸Ð½ÑÑÑÐºÐ¸Ñ Ð·Ð°ÐºÐ°Ð·Ð¾Ð². ÐÑÑÐ¾ÑÐ½Ð¸ÐºÐ° Ð¸Ð½ÑÐ¾ÑÐ¼Ð°ÑÐ¸Ð¸ Ð²ÑÑÑÑÐ¿Ð¸Ð»Ð¸ ÑÐ²Ð»ÑÑÑÑÑ Ð¸ÑÑÐ¾ÑÐ½Ð¸ÐºÐ¸ ÑÑÐµÐ±Ð½Ð¾Ð¹, Ð¼Ð¾Ð½Ð¾Ð³ÑÐ°ÑÐ¸ÑÐµÑÐºÐ¾Ð¹ Ð¸ Ð¿ÐµÑÐ¸Ð¾Ð´Ð¸ÑÐµÑÐºÐ¾Ð¹ Ð»Ð¸ÑÐµÑÐ°ÑÑÑÑ Ð¿Ð¾ Ð²ÑÐ±ÑÐ°Ð½Ð½Ð¾Ð¹ ÑÐµÐ¼Ðµ, Ð° ÑÐ°ÐºÐ¶Ðµ Ð¸ÑÑÐ¾ÑÐ½Ð¸ÐºÐ¸ Ð½Ð° Ð²ÐµÐ±-ÑÐ°Ð¹ÑÐ°Ñ. ÐÐ±ÑÐµÐºÑÐ¾Ð¼ ÑÐ²Ð»ÑÑÑÑÑ Ð·Ð°ÐºÐ°Ð·Ñ ÐºÐ»Ð¸ÐµÐ½ÑÐ¾Ð² Ð¸Ð½ÑÐµÑÐ½ÐµÑ-Ð¼Ð°Ð³Ð°Ð·Ð¸Ð½Ð° Â«Ð£ÑÐºÐ¾Ð½Ð¾ÑÂ» Ð·Ð° Ð¿ÐµÑÐ¸Ð¾Ð´ Ð² Ð½ÐµÑÐºÐ¾Ð»ÑÐºÐ¾ Ð¼ÐµÑÑÑÐµÐ² (9 Ð¼Ð»Ð½. ÑÑÐ°Ð½Ð·Ð°ÐºÑÐ¸Ð¹). ÐÐ°Ð½Ð½ÑÐµ Ð²Ð·ÑÑÑ Ð¸Ð· Ð¾ÑÐºÑÑÑÐ¾Ð³Ð¾ ÐºÐ¾Ð½ÐºÑÑÑÐ° Ð¿Ð¾ Ð°Ð½Ð°Ð»Ð¸Ð·Ñ Ð´Ð°Ð½Ð½ÑÑ SAS Data Hack Platypus, Ð¿ÑÐ¾Ð²Ð¾Ð´Ð¸Ð¼Ð¾Ð³Ð¾ ÐºÐ¾Ð¼Ð¿Ð°Ð½Ð¸ÐµÐ¹ SAS Ð¸ Â«Ð£ÑÐºÐ¾Ð½Ð¾ÑÂ» Ð¾ÑÐµÐ½ÑÑ 2019 Ð³Ð¾Ð´Ð° (https://sascompetitions.ru). Ð ÑÐ°Ð±Ð¾ÑÐµ Ð¿ÑÐ¾Ð¸Ð·Ð²ÐµÐ´ÐµÐ½ ÑÑÐ°Ð²Ð½Ð¸ÑÐµÐ»ÑÐ½ÑÐ¹ Ð°Ð½Ð°Ð»Ð¸Ð· Ð¿Ð¾Ð´ÑÐ¾Ð´Ð¾Ð², Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¸ Ð¸Ð½ÑÑÑÑÐ¼ÐµÐ½ÑÐ°Ð»ÑÐ½ÑÑ ÑÑÐµÐ´ÑÑÐ² Ð°Ð½Ð°Ð»Ð¸Ð·Ð° Ð´Ð°Ð½Ð½ÑÑ. ÐÐ±Ð¾ÑÐ½Ð¾Ð²ÑÐ²Ð°ÐµÑÑÑ Ð²Ð¾Ð·Ð¼Ð¾Ð¶Ð½Ð¾ÑÑÑ Ð¸ ÑÑÑÐµÐºÑÐ¸Ð²Ð½Ð¾ÑÑÑ ÑÐµÑÐµÐ½Ð¸Ñ Ð·Ð°Ð´Ð°ÑÐ¸ Ð°Ð½Ð°Ð»Ð¸Ð·Ð° Ð´Ð°Ð½Ð½ÑÑ Ð½Ð° Ð¿Ð»Ð°ÑÑÐ¾ÑÐ¼Ðµ Loginom. ÐÐ¿Ð¸ÑÑÐ²Ð°ÑÑÑÑ Ð±Ð¸Ð·Ð½ÐµÑ-Ð¿ÑÐ¾ÑÐµÑÑÑ AS-IS Ð¸ TO-BEÂ  Ð² Ð½Ð¾ÑÐ°ÑÐ¸Ð¸ BPMN. Ð¡ÑÑÐ¾ÑÑÑÑ Ð½ÐµÑÐºÐ¾Ð»ÑÐºÐ¾ Ð¼Ð¾Ð´ÐµÐ»ÐµÐ¹ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð¸ Ð²ÑÐ±Ð¸ÑÐ°ÐµÑÑÑ Ð»ÑÑÑÐ°Ñ. ÐÐ¾Ð´ÐµÐ»Ñ Ð¾ÑÐ¾ÑÐ¼Ð»ÐµÐ½Ð° Ð² ÐºÐ°ÑÐµÑÑÐ²Ðµ Ð°Ð½Ð°Ð»Ð¸ÑÐ¸ÑÐµÑÐºÐ¾Ð³Ð¾ Ð²ÐµÐ±-ÑÐµÑÐ²Ð¸ÑÐ°. ÐÑÐ¾Ð¸Ð·Ð²ÐµÐ´ÐµÐ½ ÑÐ°ÑÑÐµÑ ÑÐºÐ¾Ð½Ð¾Ð¼Ð¸ÑÐµÑÐºÐ¾Ð¹ ÑÑÑÐµÐºÑÐ¸Ð²Ð½Ð¾ÑÑÐ¸ Ð¾Ñ Ð²Ð½ÐµÐ´ÑÐµÐ½Ð¸Ñ Ð¼Ð¾Ð´ÐµÐ»Ð¸ Ð¿ÑÐ¸ ÑÑÐ»Ð¾Ð²Ð¸Ð¸ ÑÐ½Ð¸Ð¶ÐµÐ½Ð¸Ñ Ð¿Ð¾Ð·Ð´Ð½Ð¸Ñ Ð¾ÑÐ¼ÐµÐ½ Ð·Ð°ÐºÐ°Ð·Ð¾Ð² Ð² Ð´Ð²Ð° ÑÐ°Ð·Ð°.
description: The purpose of the research isÂ  the importance of solving the problem of cancelled orders. The subject of the thesis: âTo study modern approaches to the analysis of customer databases. âDescribe the object of analysis (online hypermarket "Utkonos") and form AS-IS and TO-BE processes for goods delivery. âTo analyze the market of analytical tools to select a software tool to do the job. âSolve the problems of cancelled orders by building a predictive probability estimation model and describing the TO-BE process. âDescribe the model as an analytical web service. The relevance of the topic stems from the fact that it is necessary to optimize the business processes of online stores involved in food delivery, based on machine learning models, to reduce losses associated with the cancellation of customer orders. The sources of information are the sources of educational, monographic and periodical literature on the chosen topic, as well as sources on websites. The object is the customer orders of the Utkonos online store for a period of several months (9 million transactions). The data are taken from SAS Data Hack Platypus, an open data analysis competition conducted by SAS and Utkonos in fall 2019 (https://sascompetitions.ru). The paper makes a comparative analysis of approaches, methods and tools for data analysis. It substantiates the possibility and effectiveness of solving the data analysis problem on the Loginom platform. AS-IS and TO-BE business processes are described in BPMN notation. Several machine learning models are built and the best one is selected. The model is designed as an analytical web service. Calculated the cost-effectiveness of the implementation of the model on the condition of reducing late order cancellations by half.