title: ÐÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ðµ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð´Ð»Ñ ÑÐµÐ³Ð¼ÐµÐ½ÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ ÐºÐ»Ð¸ÐµÐ½ÑÑÐºÐ¾Ð¹ Ð±Ð°Ð·Ñ Ð² ÑÐ¸ÑÐµÐ¹Ð»Ðµ
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð±Ð°ÐºÐ°Ð»Ð°Ð²ÑÐ°
titleType: Subtitle
title: Application of machine learning methods to segment a customer database in retail
Creators: name: Ð¡ÐµÐ¼ÐµÐ½Ð¾Ð²Ð°, ÐÐ¾Ð»Ð¸Ð½Ð°
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: 2021
Subjects: Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
ÑÐµÐ³Ð¼ÐµÐ½ÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ
ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ñ
Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ Ñ ÑÑÐ¸ÑÐµÐ»ÐµÐ¼
uplift Ð¼Ð¾Ð´ÐµÐ»Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ
machine learning
segmentation
classification
supervised learning
uplift modeling

description: Ð¦ÐµÐ»Ñ ÑÐ°Ð±Ð¾ÑÑ â Ð°Ð½Ð°Ð»Ð¸Ð· Ð¸ Ð¾Ð±Ð¾ÑÐ½Ð¾Ð²Ð°Ð½Ð¸Ðµ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ñ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð´Ð»Ñ ÑÐµÐ³Ð¼ÐµÐ½ÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ ÐºÐ»Ð¸ÐµÐ½ÑÑÐºÐ¾Ð¹ Ð±Ð°Ð·Ñ Ð² ÑÐ¸ÑÐµÐ¹Ð»Ðµ. ÐÐ°Ð´Ð°ÑÐ¸ ÑÐ°Ð±Ð¾ÑÑ: - Ð°Ð½Ð°Ð»Ð¸Ð· Ð´ÐµÑÑÐµÐ»ÑÐ½Ð¾ÑÑÐ¸ ÑÐµÑÐ¸ Ð¿ÑÐ¾Ð´Ð¾Ð²Ð¾Ð»ÑÑÑÐ²ÐµÐ½Ð½ÑÑ ÑÑÐ¿ÐµÑÐ¼Ð°ÑÐºÐµÑÐ¾Ð²; - Ð¿Ð¾ÑÑÑÐ¾ÐµÐ½Ð¸Ðµ Ð±Ð¸Ð·Ð½ÐµÑ-Ð¿ÑÐ¾ÑÐµÑÑÐ° ÑÐ¾Ð·Ð´Ð°Ð½Ð¸Ñ ÑÐµÐºÐ¾Ð¼ÐµÐ½Ð´Ð°ÑÐ¸Ð¸ ÐºÐ»Ð¸ÐµÐ½ÑÐ°; - ÑÐ°ÑÑÐ¼Ð¾ÑÑÐµÐ½Ð¸Ðµ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð´Ð»Ñ ÑÐµÑÐµÐ½Ð¸Ñ Ð·Ð°Ð´Ð°ÑÐ¸ ÑÐµÐ³Ð¼ÐµÐ½ÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ; - ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° Ð¸ ÑÐµÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ñ Ð¿ÑÐµÐ´Ð»Ð¾Ð¶ÐµÐ½Ð¸Ñ Ð¿Ð¾ Ð²Ð½ÐµÐ´ÑÐµÐ½Ð¸Ñ Ð°Ð½Ð°Ð»Ð¸ÑÐ¸ÑÐµÑÐºÐ¾Ð³Ð¾ Ð¸Ð½ÑÑÑÑÐ¼ÐµÐ½ÑÐ°. Ð Ð°Ð±Ð¾ÑÐ° Ð²ÑÐ¿Ð¾Ð»Ð½ÐµÐ½Ð° Ð½Ð° Ð¼Ð°ÑÐµÑÐ¸Ð°Ð»Ð°Ñ Ð¾ Ð´ÐµÑÑÐµÐ»ÑÐ½Ð¾ÑÑÐ¸ ÑÐµÑÐ¸ Ð¿ÑÐ¾Ð´Ð¾Ð²Ð¾Ð»ÑÑÑÐ²ÐµÐ½Ð½ÑÑ ÑÑÐ¿ÐµÑÐ¼Ð°ÑÐºÐµÑÐ¾Ð² Â«ÐÐ·Ð±ÑÐºÐ° Ð²ÐºÑÑÐ°Â» ÐÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð½ÑÐµ Ð¼ÐµÑÐ¾Ð´Ñ: ÑÑÐ°Ð²Ð½Ð¸ÑÐµÐ»ÑÐ½ÑÐ¹ Ð°Ð½Ð°Ð»Ð¸Ð·, Ð¼Ð¾Ð´ÐµÐ»Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ Ð±Ð¸Ð·Ð½ÐµÑ-Ð¿ÑÐ¾ÑÐµÑÑÐ¾Ð², Ð°Ð½Ð°Ð»Ð¸Ð· Ð´Ð°Ð½Ð½ÑÑ, Ð¸Ð½ÑÑÑÑÐ¼ÐµÐ½ÑÑ Ð¸Ð½ÑÐ¾Ð³ÑÐ°ÑÐ¸ÐºÐ¸. Ð ÐµÐ·ÑÐ»ÑÑÐ°ÑÑ ÑÐ°Ð±Ð¾ÑÑ: - Ð¿Ð¾ÑÑÑÐ¾ÐµÐ½Ð¸ÐµÐ¼ Ð¼Ð¾Ð´ÐµÐ»Ð¸ AS-IS Ð½Ð°Ð¹Ð´ÐµÐ½Ð¾ ÑÐ»Ð°Ð±Ð¾Ðµ Ð¼ÐµÑÑÐ¾ Ð² Ð±Ð¸Ð·Ð½ÐµÑ- Ð¿ÑÐ¾ÑÐµÑÑÐµ ÑÐ¾Ð·Ð´Ð°Ð½Ð¸Ñ ÑÐµÐºÐ¾Ð¼ÐµÐ½Ð´Ð°ÑÐ¸Ð¸ Ð´Ð»Ñ ÐºÐ»Ð¸ÐµÐ½ÑÐ°, Ð¿ÑÐµÐ´Ð»Ð¾Ð¶ÐµÐ½Ð¾ ÑÐµÑÐµÐ½Ð¸Ðµ Ð¿Ð¾ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸Ñ Ð±Ð¾Ð»ÐµÐµ Ð¼Ð¾ÑÐ½Ð¾Ð³Ð¾ Ð°Ð½Ð°Ð»Ð¸ÑÐ¸ÑÐµÑÐºÐ¾Ð³Ð¾ Ð¸Ð½ÑÑÑÑÐ¼ÐµÐ½ÑÐ°; - ÑÐ°ÑÑÐ¼Ð¾ÑÑÐµÐ½Ñ Ð¼ÐµÑÐ¾Ð´Ñ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð´Ð»Ñ ÑÐµÐ³Ð¼ÐµÐ½ÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ ÐºÐ»Ð¸ÐµÐ½ÑÐ¾Ð², Ð¾Ð¿Ð¸ÑÐ°Ð½ ÐºÐ¾Ð½Ð²ÐµÐ¹ÐµÑ Ð¾Ð±ÑÐ°Ð±Ð¾ÑÐºÐ¸ Ð´Ð°Ð½Ð½ÑÑ, Ð²ÑÐ±ÑÐ°Ð½ Ð¿ÑÐ¸Ð¼ÐµÑ Ð¼Ð¾Ð´ÐµÐ»Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Ð¸ Ð¾Ð¿Ð¸ÑÐ°Ð½Ð° ÑÑÐµÐ¼Ð° ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð¾Ð´ÐµÐ»Ð¸; - ÑÐ°ÑÑÐ¼Ð¾ÑÑÐµÐ½ Ð¿ÑÐ¾ÑÐµÑÑ ÑÐ±Ð¾ÑÐ° Ð´Ð°Ð½Ð½ÑÑ, Ð¸Ñ Ð¿Ð¾Ð´Ð³Ð¾ÑÐ¾Ð²ÐºÐ¸ Ð¸ Ð¾Ð±ÑÐ°Ð±Ð¾ÑÐºÐ¸ Ð¿ÑÐ¸ Ð¿Ð¾Ð¼Ð¾ÑÐ¸ Ð¼Ð¾Ð´ÐµÐ»Ð¸ uplift; Ð¿ÑÐ¾Ð¸Ð·Ð²ÐµÐ´ÐµÐ½Ð¾ ÑÑÐ°Ð²Ð½ÐµÐ½Ð¸Ðµ ÑÑÐµÐ´ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ¸, Ð²ÑÐ±ÑÐ°Ð½Ð° ÑÑÐµÐ´Ð° Ð´Ð»Ñ Ð²Ð½ÐµÐ´ÑÐµÐ½Ð¸Ñ Ð¸ Ð´Ð¾Ð¿Ð¾Ð»Ð½Ð¸ÑÐµÐ»ÑÐ½Ð¾Ðµ Ð¾Ð±Ð¾ÑÑÐ´Ð¾Ð²Ð°Ð½Ð¸Ðµ; - Ð¾Ð±Ð¾ÑÐ½Ð¾Ð²Ð°Ð½Ð° ÑÑÑÐµÐºÑÐ¸Ð²Ð½Ð¾ÑÑÑ Ð²Ð½ÐµÐ´ÑÐµÐ½Ð¸Ñ, ÑÐ°ÑÑÐ¼Ð¾ÑÑÐµÐ½ Ð¿ÑÐ¾ÐµÐºÑ Ð¿Ð¾ Ð²Ð½ÐµÐ´ÑÐµÐ½Ð¸Ñ, Ð²ÐºÐ»ÑÑÐ°Ñ ÐºÐ¾Ð¼Ð°Ð½Ð´Ñ Ð¿ÑÐ¾ÐµÐºÑÐ°, ÑÑÐ¾ÐºÐ¸ Ð¿ÑÐ¾ÐµÐºÑÐ°, ÑÐ¸ÑÐºÐ¸. ÐÑÐ°ÐºÑÐ¸ÑÐµÑÐºÐ°Ñ Ð·Ð½Ð°ÑÐ¸Ð¼Ð¾ÑÑÑ ÑÐ°Ð±Ð¾ÑÑ Ð¾Ð±ÑÑÐ»Ð¾Ð²Ð»ÐµÐ½Ð° ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐ°Ð¼Ð¸ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸Ñ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð´Ð»Ñ ÐºÐ¾Ð¼Ð¿Ð°Ð½Ð¸Ð¸: Ð·Ð° ÑÑÐµÑ Ð¿ÐµÑÑÐ¾Ð½Ð°Ð»Ð¸Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð½Ð¾Ð³Ð¾ Ð²Ð·Ð°Ð¸Ð¼Ð¾Ð´ÐµÐ¹ÑÑÐ²Ð¸Ñ Ð¿Ð¾Ð²ÑÑÐ°ÐµÑÑÑ ÐºÐ¾Ð½Ð²ÐµÑÑÐ¸Ñ Ð¸ ÐºÐ¾Ð»Ð¸ÑÐµÑÑÐ²Ð¾ ÐºÐ»Ð¸ÐµÐ½ÑÐ¾Ð², Ð·Ð° ÑÑÐµÑ Ð±Ð¾Ð»ÐµÐµ Ð°ÐºÑÑÐ°Ð»ÑÐ½ÑÑ Ð¿ÑÐµÐ´Ð»Ð¾Ð¶ÐµÐ½Ð¸Ð¹ Ð¿Ð¾Ð²ÑÑÐ°ÐµÑÑÑ ÑÑÐµÐ´Ð½Ð¸Ð¹ ÑÐµÐº, Ð²ÑÐµ ÑÑÐ¾ Ð¿Ð¾Ð·Ð²Ð¾Ð»ÑÐµÑ ÑÐ²ÐµÐ»Ð¸ÑÐ¸ÑÑ Ð²ÑÑÑÑÐºÑ. ÐÑÐ²Ð¾Ð´Ñ. ÐÐ°Ð´Ð°ÑÐ¸ ÐÐÐ  ÑÐµÑÐµÐ½Ñ, ÑÐµÐ»Ñ Ð´Ð¾ÑÑÐ¸Ð³Ð½ÑÑÐ°, Ð¾Ð¿ÑÐµÐ´ÐµÐ»ÐµÐ½Ð° Ð¾Ð±Ð»Ð°ÑÑÑ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ñ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐ¾Ð².
description: The purpose of the work â analysis and justification of the application of machine learning methods to segment a customer database in retail. Tasks of work: - analysis of the activities of the chain of food supermarkets; - building a business process for creating a clientâs recommendation; - study of machine learning methods for solving the segmentation problem; - development and implementation of an analytical tool. Work is performed on the basis of chain store âAzbuka Vkusaâ activities. Methods used: comparative analysis, business process modeling, data analysis, infographic tools. Work results: - in the construction of the AS-IS model a weak spot in the business process of creating a recommendation for a client was found, a solution was proposed for using a more powerful analytical tool; - the methods of machine learning for segmenting customers are considered, the data processing pipeline is described; an example of modeling is chosen, and the scheme of the model is described; - the process of data collection, their preparation and processing using the uplift model is considered; a comparison of development environments was made, an environment for implementation and additional equipment were selected; - the efficiency of implementation was substantiated, the implementation project was considered, including the project team, project timing, risks. The practical significance of the work is due to the results of the use of machine learning methods for the company: due to personalized interaction, conversion and the number of customers increase, due to more relevant offers, the average check increases, all this allows to increase the company's revenue. Conclusions. The tasks of the thesis have been solved, the goal has been achieved, the scope of the results has been determined.