Управленец2218-50032686-792310.29141/2218-5003-2023-14-2-7YXXDEVhttps://upravlenets.usue.ru/ru/-2023/1236https://upravlenets.usue.ru/ru/-2023/1236Сегментация потребителей промышленного оборудования на основе MRFM-анализаMRFM-analysis for customer segmentation in the industrial equipment marketЦойМарина ЕвгеньевнаЦойМарина ЕвгеньевнаTsoyMarina E.tsoy@copr.nstu.ruЩеколдинВладислав ЮрьевичЩеколдинВладислав ЮрьевичShchekoldinVladislav Yu.schekoldin@corp.nstu.ruNovosibirsk State Technical University (Novosibirsk, Russia)Новосибирский государственный технический университет (г. Новосибирск, РФ)0505202314290992601202310032023CC BY-NC 4.0

В процессе экономической деятельности предприятиям важно выявлять и приоритизировать группы клиентов со схожими запросами для выработки индивидуального подхода к каждой из этих групп. Исследование направлено на осуществление сегментации потребителей сектора B2B на основе анализа истории их покупательского поведения. Методологической базой работы послужила теория поведенческого маркетинга. Методика исследования построена на применении МRFM-анализа (Modified Recency-Frequency-Monetary Analysis), который позволяет выявлять однородные группы клиентов, изучать эволюцию их поведения и разрабатывать адресные стратегии взаимодействия с представителями каждой группы. Показаны преимущества комплекса машинного обучения и интеллектуального анализа данных Orange Data Mining: возможность статистически корректно выделять кластеры клиентов и удобство визуализации результатов анализа. Информационную базу работы составили уникальные данные кейса о продажах промышленного оборудования крупного российского производителя систем безопасности за период 2015–2022 гг. На основании проведенного исследования обнаружена взаимосвязь построенной сегментации с классификацией Рейнарца – Кумара, применяемой для выбора стратегии формирования лояльности клиентов. По результатам сегментации выделено шесть групп потребителей и установлено, какие из них обеспечивают компании наибольшую прибыль, а какие на нее практически не влияют. Наиболее приоритетной оказалась группа торговых домов (около 20 % всех клиентов), которые характеризуются долгосрочностью отношений с производителем и высокой клиентской надежностью. Именно для них целесообразно разрабатывать адресные предложения, стимулирующие увеличение их спроса. В отношении других групп потребителей следует использовать стандартные стратегии маркетинга.

It is of high importance for enterprises to identify, group and prioritize customers with similar needs in order to develop an individual approach to each of these groups. The article aims to segment B2B consumers based on the analysis of their purchasing behaviour. The theoretical framework of the study is the postulates of behavioural marketing. The research method involves МRFM-analysis (Modified Recency-Frequency-Monetary Analysis) that allows determining homogeneous groups of clients, examining the evolution of their behaviour, and formulating targeted interaction strategies for each group. The paper demonstrates the benefits of the Orange Data Mining machine learning and data mining complex, these are the capability to statistically correctly identify client clusters and the visual clarity of results analysis. The empirical evidence is industrial equipment sales data provided by a large Russian security systems manufacturer for the period of 2015–2022. A relationship is found between the segmentation performed in the study and the Reinartz–Kumar approach applied to decide on a strategy for forming customer loyalty. The authors distinguish between six groups of customers and establish those generating the greatest profit for the company and those having the minimum effects on its turnover. The group of trading firms (about 20% of all the clients) turned out to be the priority one, which, due to the specificity of their activities, have long-term relationships with the manufacturer and high client reliability. It is the client group for which devising targeted strategies stimulating an increase in their demand is most reasonable. For the rest of the consumer groups, it is expedient to use standard marketing strategies.

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