title: Ð¡ÑÐ°ÑÐ¸ÑÑÐ¸ÑÐµÑÐºÐ¾Ðµ Ð¾Ð±ÐµÑÐ¿ÐµÑÐµÐ½Ð¸Ðµ Ð°Ð´Ð°Ð¿ÑÐ°ÑÐ¸Ð¸ SMM ÑÐµÑÐµÐ½Ð¸Ð¹ ÑÑÐ°Ð½ÑÐ°Ð¹Ð·Ð¸Ð½Ð³Ð¾Ð²ÑÑ ÑÐµÑÐµÐ¹ Ð½Ð° ÑÐµÐ³Ð¸Ð¾Ð½Ð°Ð»ÑÐ½Ð¾Ð¼ ÑÑÐ¾Ð²Ð½Ðµ
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: Statistical support for the adaptation of SMM solutions of franchise networks at the regional level
Creators: name: ÐÐºÑÐµÐ½Ð¾Ð², ÐÐ°Ð²ÐµÐ»
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: 2024
Subjects: ÑÐµÐ³Ð¸Ð¾Ð½Ð°Ð»ÑÐ½ÑÐµ Ð¾ÑÐ¾Ð±ÐµÐ½Ð½Ð¾ÑÑÐ¸
ÑÐºÐ¾Ð½Ð¾Ð¼ÐµÑÑÐ¸ÐºÐ°
Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
ÑÑÐ°Ð½ÑÐ°Ð¹Ð·Ð¸Ð½Ð³
Ð¼Ð°ÑÐºÐµÑÐ¸Ð½Ð³ Ð² ÑÐ¾ÑÐ¸Ð°Ð»ÑÐ½ÑÑ ÑÐµÑÑÑ
regional features
econometrics
machine learning
franchising
social media marketing

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description: The purpose of the research is to develop a methodology for the specialization of marketing materials in social networks, considering regional specifics. Approbation of the offered method is carried out on the example of the Dodo Pizza franchise network. The work consists of 4 logically consecutive chapters. The first chapter fully examines the theoretical aspects of franchising activities. In conclusion, a list of typical franchising problems in the catering industry is provided. The problem of considering regional peculiarities in the development of a business format franchise is chosen as the investigated one. In the next chapter, an auxiliary econometric analysis is carried out, statistically proving the existence of a link between the reaction of consumers on the social network and the average revenue of establishments of the franchise in question by region. For the analysis, 23 socio-economic, cultural, and demographic factors were collected in 27 regions of Russia for the period from 2018 to 2023. To collect data from the domestic social network - Vkontakte, parsing tools using APIs automated by Python 3 programming language tools were used. In total, more than 130 thousand records were collected containing: the text of the post, the number of likes, comments, and views. The next stage, using standard procedures for processing and quantifying natural language, is developing a methodology that includes a cascade of machine learning models aimed at specializing marketing material on a social network by considering consumer reactions. In conclusion, the algorithm for using the developed methodology is given using specific examples.