Application of machine learning technologies in sales management of car dealership companies

This paper examines the use of machine learning (ML) technologies in sales management of automobile dealership companies. It provides an overview of current approaches to car sales management in Russia and globally, including the use of traditional CRM systems, business intelligence (BI) tools, sales scripts, and chatbots. A comparison of these technologies is presented, highlighting their advantages and disadvantages in the dealership context. The problems of existing solutions are noted, and the need for implementing artificial intelligence and machine learning methods to improve sales effectiveness is substantiated. The principles of ML-based technologies in sales (e.g., predictive analytics, personalized recommendations, intelligent assistants) are described, and their application is analyzed through examples of Russian practices and international experience (USA, Europe, China) of AI adoption in car dealerships. The existing 1C:Enterprise “Alfa-Auto” system used by major Russian dealers (e.g., the TransTechService group) is mentioned, and prospects for integrating AI into such platforms to enhance sales management are discussed. The article is written in an academic style and is intended for professionals in strategic management and IT in sales, as well as educators and graduate students.