CC BY
85
ю
^ Natalya B. IZAKOVA
Sr. Lecturer of Marketing
and International Management Dept.
Ural State University of Economics 620144, RF, Yekaterinburg, 8 Marta/Narodnoy Voli St., 62/45 Phone: (343) 221-27-46 E-mail: [email protected]
► Larisa M. KAPUSTINA
Dr. Sc. (Econ.), Professor,
Head of Marketing and International
Management Dept.
Ural State University of Economics 620144, RF, Yekaterinburg, 8 Marta/Narodnoy Voli St., 62/45 Phone: (343) 221-27-46 E-mail: [email protected]
References
RELATIONSHIP MARKETING INDUSTRIAL MARKET MARKETING PRODUCTIVITY INDICATORS BALANCED SCORECARD RELATIONSHIP MARKETING PROGRAM CUSTOMER LIFETIME VALUE
JEL classification
M31, C12, C81
Measuring Relationship Marketing Productivity in the Industrial Market
Abstract
The paper systematizes theoretical and methodological approaches to the study of the influence of marketing activities involved in building relationships with partners on an organization's performance indicators. The article aims to design a system of indicators and a set of methods for measuring relationship marketing productivity in the industrial market. The methodological basis is the works of the leading Russian and foreign scientists on examining the content and productivity of relationship marketing in the industrial market, as well as on forming customer metrics and a marketing balanced scorecard. The methods for evaluating relationship marketing productivity in the industrial market combines methods of mathematical statistics (single-factor analysis of variance, construction of contingency tables, pairwise correlation analysis) and expert methods (in-depth interviews). The authors develop a balanced scorecard of relationship marketing of an industrial enterprise on the basis of Kaplan and Norton's business perspectives. We establish the stages of evaluating the productivity of relationship marketing in the industrial market and test scientific hypotheses about the factors determining the productivity of relationship marketing. The authors try out the proposed method at the Aramil Plant of Advanced Technologies and introduce a relationship marketing program. Due to implementation of the relationship marketing program in 2017, the plant's revenue increased by 1.4%. The results of calculations confirm the hypotheses that customers with a high level of satisfaction have the largest share in the company's sales volume and employees with a high level of satisfaction establish the longest relationships with the clients. We also prove the correlation between satisfaction of the target segment's customers and their lifetime value.
INTRODUCTION
The industrial market is a system of relationships between economic subjects resulting in acquisition of goods which are then used in production of other products and services. In the context of positive shifts happening in the Russian economy, the market environment for industrial enterprises maintains a high level of uncertainty, which is due to the unfavourable foreign economic situation. In this regard, industrial companies are forced to seek ways to enhance sales efficiency through the use of marketing and by improving interaction with corporate clients and end-users. Competent management in the field of relationship marketing at industrial enterprises allows optimizing marketing costs, maintaining a stable position in the market and improving competitiveness even in the face of a fall in products sales. The problem of measuring the results of relationship marketing is widely debated by both scientists and business practitioners, but an integrated methodological approach to its solution is still under development. The main difficulty is to establish the relationship between marketing activities and financial performance of a company.
The process of establishing and developing relationships with customers, which reflects the importance of retaining partners, has been the object of research for many decades. Finch et al. underline the interdisciplinary nature of relationship marketing concept that finds itself at the intersection of management, psychology and sociology [12. P. 171]. They arrive at the conclusion that the quality of relationships is an integral part of consumer behaviour when deciding to make a purchase [13. P. 15]. Sheth et al. emphasize the importance of a number of aspects in relationship marketing, such as cooperation, creation and appreciation of value for those involved in the relationships [21. P. 140].
Оценка результативности маркетинга взаимоотношений на промышленном рынке
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Аннотация
Статья посвящена систематизации теоретико-методологических подходов к исследованию влияния маркетинговой деятельности по выстраиванию отношений с партнерами на показатели эффективности организации. Исследование направлено на разработку системы показателей и методического инструментария оценки результативности маркетинга взаимоотношений на промышленном рынке. Методологическая база включает труды ведущих российских и зарубежных ученых, посвященные исследованию содержания и результативности маркетинга взаимоотношений в данном секторе рынка, формированию клиентских метрик и сбалансированной системы показателей маркетинга. Методический инструментарий объединяет методы математической статистики (однофакторного дисперсионного анализа, построения таблиц сопряженности, парного корреляционного анализа) и экспертные методы (глубинное интервью). Авторами предложена сбалансированная система показателей маркетинга взаимоотношений промышленного предприятия на основе бизнес-перспектив Р. Ка-плана и Д. Нортона. Определены этапы оценки результативности маркетинга взаимоотношений на промышленном рынке. Протестированы научные гипотезы о факторах, определяющих результативность маркетинга взаимоотношений. Методический подход апробирован на Ара-мильском заводе передовых технологий, внедрена программа маркетинга взаимоотношений. По итогам реализации программы в 2017 г. доход завода увеличился на 1,4%. Результаты расчетов подтвердили гипотезы о том, что клиенты с высоким уровнем удовлетворенности имеют наибольшую долю в объеме продаж компании, сотрудники с высоким уровнем удовлетворенности устанавливают наиболее продолжительные отношения с клиентом. Обоснована зависимость между удовлетворенностью потребителей целевого сегмента и их пожизненной ценностью.
Lagutaeva et al. conduct a research using machine learning methods and reach the conclusion that the application of a full range of marketing practices by companies produced less financial effect compared to the focused application of relationship marketing tools. Those enterprises developing relationship marketing proved to be more financially efficient, as they were more successful in integrating into market interactions and responded more flexibly to changes in market conditions [7. P. 7]. The results of the study confirm the relevance of the scientific problem of measuring the productivity of relationship marketing and determining the relationship between companies' programs for relationship marketing and financial results of their activities. For industrial enterprises, this issue is of special relevance since their performance efficiency is largely dependent on a competent approach to constructing relationships with a limited number of partners and main buyers of their products.
The purpose of the paper is to develop a system of indicators and stages of measuring the productivity of relationship marketing of an industrial enterprise in the B2B market. The study represents the next step in the authors' research in the field of methods for measuring relationship marketing productivity in the industrial market [4; 18]. To achieve the stated goal, we set and accomplished the following tasks:
1) to develop a marketing balanced scorecard that allows evaluating the productivity of relationship marketing of an industrial enterprise;
2) to establish and test the stages of measuring the productivity of relationship marketing.
ИЗАКОВА Наталья Борисовна
Старший преподаватель кафедры маркетинга и международного менеджмента
Уральский государственный экономический университет 620144, РФ, г. Екатеринбург, ул. 8 Марта/Народной Воли, 62/45 Тел.: (343) 221-27-46 E-mail: [email protected]
КАПУСТИНА Лариса Михайловна
Доктор экономических наук, профессор, заведующая кафедрой маркетинга и международного менеджмента
Уральский государственный экономический университет 620144, РФ, г. Екатеринбург, ул. 8 Марта/Народной Воли, 62/45 Тел.: (343) 221-27-46 E-mail: [email protected]
Ключевые слова
МАРКЕТИНГ ВЗАИМООТНОШЕНИЙ
ПРОМЫШЛЕННЫЙ РЫНОК
ПОКАЗАТЕЛИ РЕЗУЛЬТАТИВНОСТИ МАРКЕТИНГА
СИСТЕМА СБАЛАНСИРОВАННЫХ ПОКАЗАТЕЛЕЙ
ПРОГРАММА МАРКЕТИНГА ВЗАИМООТНОШЕНИЙ
ПОЖИЗНЕННАЯ ЦЕННОСТЬ КЛИЕНТА
JEL classification
M31, C12, C81
2 THEORETICAL AND METHODOLOGICAL APPROACHES ¿ TO MEASURING THE PRODUCTIVITY J OF RELATIONSHIP MARKETING
h Scientific research considers productivity evaluation as £ one of the main components of the process of relationship 5 marketing management, while emphasizing its special imS portance for making marketing decisions. We have analysed g a number of scholarly sources and singled out several approaches based on the principles of selecting key indicators of relationship marketing productivity (Fig. 1).
1. Company - Customer retention - Profitability. Gronroos's model - one of the first models of relationship feedback -is based on the concept of customer relationship life cycle or a profit chain in which a company's profitability is a result of
relationship marketing, and the core factor in profitability is customer satisfaction that is the key to its retention [14. P. 8]. Most researchers question this model and suggest extending it with employee satisfaction and retention, good quality, which results in customer satisfaction, their retention and an increase in profitability (see, for example, [15. P. 184]). Developing this approach, Storbacka et al. propose a model demonstrating the influence that a large number of factors exert on the profitability of relationships. According to the authors, these factors embrace service quality, customer perception of value, customer's perceived sacrifice, customer commitment to the company, customer satisfaction, customers' dependence on the company, the availability of alternatives for interaction and the longevity of the relationships [22. P. 23].
1. Company -Customer retention -Profitability
Gronroos, 1994
Simple model of relationship
feedback.
Indicators: Satisfaction, customer retention, the company's profitability
Gummerson, 1999
Extended model of relationship
feedback.
Indicators: Satisfaction and retention of employees and customers, the company's profitability
Storbacka et al., 1994 Integrated model of relationship feedback.
Indicators: Service quality, value, commitment, customer satisfaction, power of the supplier and the customer, stable and lasting relationships, patronage, relationship costs, revenue and profit from the relationships
Hougaard & Bjerre, 2002, et al. Indicators: Supplier and consumer interaction costs, profit from consumer interaction
Classification of methodological approaches to measuring relationship marketing productivity (by the criteria of the diversity of the company's partners and the outcome of relationships)
3. Company -Creating value jointly with the customer
Rust et al., 2004
Indicators: Awareness, level of satisfaction, uniqueness and sustainability of privileges, brand loyalty, customer experience
Gupta et al., 2007
Indicators: Customer lifetime value, customer referral value, customer influencer value, customer knowledge value
Kushch & Smirnova, 2010 Indicators: Total number of customers, volume of consumer purchases, total customer costs, retention coefficient, marginal revenue per consumer
Dvoryashina, 2015, et al. Indicators: Relational, behavioural, financial customer metrics
5. Company - Integration of marketing into a company's general management system
Oyner, 2GG8
Indicators: Balanced scorecard
Sheth, Parvatiyar & Sinha, 2013, et al.
Indicators: Kaplan and Norton's balanced scorecard, loyalty index, customer satisfaction level, the degree of the company's satisfaction with relationships with its partners, etc.
4. Company -Network interaction efficiency
Tretyak, 2013
Conceptual model of relationship marketing management. Indicators: The system of indicators that allows evaluating the results of the network members' interaction
Bagiev, 2014
Conceptual-methodological model of analysing the effectiveness of interaction between subjects of the market network. Indicators: Criteria reflecting the possibility of comparing the results of marketing activities of the network's business entities
Yuldasheva, 2014 Indicators: Indicators of strategic, economic and psychological efficiency of network interaction between partners
Popova, 2014, et al. Indicators: Strategic, economic and social aspects of the effectiveness of relationships and the functioning of the network environment
Fig. 1. Methodological approaches to measuring relationship marketing productivity
Most of the listed factors cannot be represented in the form of quantitative values and evaluate their dynamics, therefore, these models are of a theoretical nature and not applicable in practice.
2. Supplier - Company - Customer. Comparing the results of marketing and purchasing activities of a company, Hou-gaard and Bjerre evaluate the productivity of relationships with the supplier, the amount of consumer costs and profit from interacting with consumers. These estimates are the arguments in favour of choosing one of the three strategies: 1) a competitive strategy which suggests terminating the relationships; 2) a cooperative strategy aimed at maintaining long-term relationships and 3) a command strategy implemented in case if the producer dominates the customer which allows the company to reduce costs incurred when interacting with clients [17].
3. Company - Creating value jointly with the customer. A number of Russian and foreign researchers propose to measure the outcome of relationships using a set of customer metrics [2]. Rust et al. form a set of indicators which includes the following: the level of the client's awareness of the company and its products; uniqueness and stability of the privileges received by the client, the level of customer satisfaction; brand loyalty; client experience [20. P. 80].
Gupta et al. regard customer lifetime value (CLV) as a cash flow generated by a client during the life cycle and believe it to be the major indicator of productivity of customer relationships [16. P. 150]. In order to determine customer value, Kumar et al. suggest applying the indicator of customer engagement value (CEV) which takes into account the level of emotional arousal and thinking activity that are typical of customers' behaviour when making a purchase. They evaluate the client's engagement as an aggregation of the four indicators: customer lifetime value, customer referral value, customer influencer value and customer knowledge value [19. P. 300].
According to Kushch and Smirnova, customer metrics are indicators that allow establishing customer value for a company in an industrial market [6. P. 248]. Dvoryashina et al. argue that a set of customer metrics includes relational, behavioural and financial indicators. The relational metrics comprise those related to satisfaction, such as satisfaction with the relationships with the company, the supplier and the product, readiness to give recommendations to the supplier company, etc. The behavioural indicators embrace customer-company metrics (loyalty, customer behaviour when coming to a decision to make a purchase, the supplier's preferences, price premium, share of wallet) and client-client network metrics (partnership efficiency, social interaction, SMM-metrics). The financial metrics encompass the indicators of customer lifetime value, costs incurred in attracting a customer, the level of customer engagement, client capital [3. P. 103].
4. Company - Network interaction efficiency. In the industrial market, all the participants of the value creation chain, which affect customer satisfaction, play a significant part in the productivity of relationship marketing management.
A number of authors, therefore, believe that it is necessary R to allow for the results of interaction with all partners when g measuring the productivity of relationship marketing man- £ agement. Pursuing the demand-chain management (DCM) / approach, Tretyak has developed a conceptual model of rela- ¡Ü tionship marketing management [22] which features all the | creators of commodity flow as participants in the interaction: £ suppliers, manufacturers, intermediaries, customers that 22 take part in creation of added value during the process of 8 production, distribution and consumption of the goods pro- l duced. According to Tretyak, this approach implies searching N for new tools that would allow measuring the productiv- 5 ity of relationships between all participants of the network [10. P. 53]. Bagiev proposes a verbal model for evaluating economic performance of marketing initiatives which embraces indicators that characterize the level of marketing activity of all business subjects within the network [1. P. 11].
The system of metrics developed by Yuldasheva to perform the integrated assessment of implementation of strategies for improving customer satisfaction is also premised on the principles of expanding the concept of supply chain management and transforming it into relationship network management. If employed, this approach suggests using the indicators of strategic, economic and psychological efficiency and integrated indicators that make it possible to establish the level of satisfaction of the network's stakeholders [11. P. 73]. Popova proposes to assess strategic, economic and social aspects of relationship productivity and the functioning of the network environment within the framework of value chain [9. P. 139].
5. Company - Integration of marketing into a company's general management system. Oyner measures marketing efficiency from the standpoint of the entire system of business management and adopts an integrated approach founded on a balanced scorecard which reflects links between management levels in an organization, the congruence between strategic and operational goals and actions, monetary and non-monetary indicators [8. P. 42]. Sheth et al. also recommend applying a balanced scorecard that reflects the goals and objectives of specific relationship marketing programs. The specificity of the implemented marketing programs predetermines the choice of performance metrics which may include Kaplan and Norton's balanced scorecard construct, Reichheld's Net Promoter Score (NPS), the evaluation of customer satisfaction and the company's satisfaction with the relationships with partners, and other indicators [21. P. 119].
Having analyzed the theoretical and methodological approaches to measuring relationship marketing productivity, we managed to ascertain the following facts:
1) all the authors recognize the relevance of building strong relationships with customers and business partners, as well as the importance of assessment of return on investment in the company's relationships for achieving better financial performance;
2) there is a need for regular information updating about the market and the its participants, organization of informa-
g tion exchange which is required for calculating and analys-® ing relationship marketing productivity; £ 3) there is a lack of single approach to developing a sys-g tem of customer metrics and relationship marketing produc-=r tivity indicators; there is a wide range of indicators of effective 5 interaction with customers and other partners of a company. I We arrive at the conclusion that it is still urgent and prac-S tically important to resolve the scientific problem of devising a system of indicators characterizing relationship marketing productivity that would combine customer metrics and indicators focused on the importance of relationship management in the development of all business prospects of a company which are most correlated with a balanced scorecard. Such an approach stimulates integration of marketing in the management system of all business processes of a company and creation of extra value due to interaction with customers.
DEVELOPMENT OF A RELATIONSHIP MARKETING BALANCED SCORECARD
The specificity of the industrial market which resides in a combination of relationships among a wide range of partners determines the need to integrate marketing performance indicators into the corporate system for evaluating the company's performance. The authors of the current research stick to an integrated approach that corresponds to the requirements of today's industrial enterprises. Extending Sheth et al.'s approach, we devise a relationship marketing balanced scorecard (RMBS) based on Kaplan and Norton's balanced scorecard construct (Table 1).
While keeping a financial component as the main parameter of a managerial and business process, the system at the same time places a high emphasis on a set of criteria that associate a long-term financial success with such indicators as clientele, internal processes, employees and systematic work of the whole company [5. P. 25].
Financial indicators characterize return on investment in building relationships and are indicators of the correspondence between the relationship marketing strategy and the company's corporate goals. The indicators for the business perspective "Relationships with customers" are the key ones for assessing the results of relationship marketing management. The presented indicators, calculated and analyzed, allow an industrial enterprise to identify a group of clients to concentrate its attention on and develop cooperation with a view to retaining customers having the largest share in the company's sales volume. The indicators for the business perspective "Internal business processes" make it possible to establish the types of activities which are of the greatest importance for customers in the industrial market affecting their decision on further cooperation with the company. For industrial enterprises, the most significant aspects of cooperation are the following: the correspondence between product quality and production process specifications, timely order fulfilment, stock availability and high-quality maintenance service.
A company's employees also contribute extensively to the process of value creation. For industrial enterprises, the decisive factor in the success of relationship marketing is investment in and smart management of employees' intellectual capital. For this reason, we believe it is expedient to include employee satisfaction in the RMBS indicators for the business perspective "Training and growth". This indicator is a factor that ensures high work performance of employees. To measure employee satisfaction, we employ a method for assessing customer satisfaction (CSAT). Employees are asked a question "Would you recommend working for this company to your relatives, partners and friends?': Those who on a ten-point scale choose a score of 9 or 10 were classified as employees with high satisfaction.
In addition to the four classic trends in business development proposed by Kaplan and Norton - finance, customer relationships, internal business processes, training and growth - we propose fostering relationships with suppliers. We suggest that the RMBS indicators for the business perspective of "Relationships with suppliers" should embrace such indicators as the longevity of a supplier relationship, the percentage of raw materials (components) of the proper quality that came into production, fulfilment of obligations by supplier, the cost of raw materials (components) and supplier satisfaction with cooperation with the company. These indicators mirror the factors which affect the productivity of a customer relationship, since they are the characteristics of the elements of the value chain for customers in the industrial market.
We claim that in order to obtain a holistic picture of the productivity of relationship marketing management, it is necessary to conduct a comprehensive analysis of the absolute values of the RMBS and their dynamics, as well as to identify the interdependence of the indicators' values for various business perspectives. Such an approach allows determining the factors influencing the values of the selected indicators, assessing their role in financial performance of a company and formulating recommendations for the development of the relationship marketing program.
The stages of measuring the productivity of relationship marketing of an industrial enterprise on the basis of a balanced scorecard are presented in Fig. 2.
The final results of the productivity of relationship marketing are obtained in stages after:
1) analysing the values of the RMBS indicators;
2) evaluating the correlation between the indicators' values for various business perspectives using statistical methods;
3) conducting in-depth interviews.
During the first stage, the indicators' values are analyzed and a preliminary conclusion about a company's performance for each business perspective is made. At the same time, the first stage provides information about the dynamics of the indicators and reveals the marketing tools which were introduced at the industrial enterprise. The results of this stage serve as the basis for issuing a set of recommenda-
Table 1 - A relationship marketing balanced scorecard of an industrial enterprise P
Business prospect Objectives of relationship marketing Relationship marketing indicators
Finance Stimulating product consumption A product's share in total revenue
Relative price
Increasing sales rate Growth rates in sales
Annual Recurring Billings (ARB)
Customer relationships Identification of target segments of the market and success factors of relationship marketing within target segments Total number of customers
The share of target customers
Purchase frequency
Repeat order rate
Customer share in sales volume
Customer Retention Rate ^RR)
Customer Profitability (CP)
Customer Lifetime Value (CLV)
Customer Satisfaction (CSAT)
Net Promoter Score (NPS)
Longevity of a customer relationship
Share of new customers
Internal business processes Customer-oriented business processes, building relationships with customers Stock availability (the percentage of out-of-stock products)
Timely order fulfillment
Maintenance service level
Evaluation of product quality
Training and promotion Employee satisfaction Employee satisfaction indicator
Supplier relationships Building long-term relationships with suppliers Longevity of a supplier relationship
The percentage of raw materials of the proper quality that came into production
Supplier satisfaction
Fulfilment of obligations by supplier
The cost of raw materials
tions on increasing the productivity of customer relationship and adjusting the relationship marketing strategies for interacting with customers and suppliers.
The second stage is designed to identify the cause and effect relationships between the marketing indicators and various business perspectives with the use of mathematical statistics methods that allow pinpointing the avenues for enhancing the productivity of relationship marketing.
At the third stage, in-depth interviews are conducted with managers or staff of the companies that represent the target segment (these companies have shown a relatively low level of satisfaction) in order to identify and eliminate problems in interaction with key consumers. In-depth interviews aim to evaluate the indicators for the business perspective "Internal business processes". These indicators can be differentiated by customer groups in the industrial market, and, unlike a standardized questionnaire, an in-depth interview provides unique information about the special features of the production process, its location, delivery date, details of the maintenance service, etc.
The distinguishing feature of the proposed method for measuring the productivity of relationship marketing of an industrial enterprise is an integrated selection of indicators that encompass the metrics designed to evaluate the outcome of the relationships with the key participants in the production chain (corporate clients and suppliers), as well as to establish the extent to which business processes are concentrated on the industrial customer which pays special attention to the following aspects of relationships: the correspondence between the product quality and the production process, timely order fulfilment, stock availability, the quality of maintenance and customer service.
MEASURING RELATIONSHIP MARKETING PRODUCTIVITY OF AN INDUSTRIAL ENTERPRISE USING A BALANCED SCORECARD
The evaluation of relationship marketing productivity using the RMBS is illustrated by the case study of the Aramil Plant of Advanced Technologies (APAT)1. The plant special-
1 Aramil is a town in Sverdlovsk oblast, Russia.
8 1 Маркетинговые стратегии и практики
Detailing parameters of information to calculate the indicators
Stage 1. Analyzing the obtained values of the RMBS indicators
Stage 2. Analysing the correlation between the indicators' values for various business perspectives
Analysing the dependence of the customer share in the total sales volume on their satisfaction
Analysing whether the length of employee-customer relationships is dependent on employee satisfaction with their work for the company
Investigating if there is a link between customer lifetime value and customer satisfaction
Analysis of variance
Correlation analysis
Studying the dependence of a company's gross profit on the values of customer loyalty index
Regression analysis
The results of the analysis of the correlation between the indicators' values for various business perspectives
Stage 3. Conducting in-depth interviews with target consumers displaying low satisfaction
Producing recommendations for enhancing the productivity of relationship marketing
Developing relationship marketing strategies for interacting with customers and suppliers
Fig. 2. The stages of evaluation of relation
izes in the production of pipes insulated with polyurethane foam and insulating elements for pipes and pipeline systems. We hypothesize about the key factors in the productivity of relationship marketing of an industrial enterprise (Table 2).
The information base of the study includes the customer database of the APAT with the use of the software package SPSS (Statistical Package for the Social Science).
Test of Hypothesis 1. The value of one-way ANOVA p = 0.048 (< 0.05) and the value of F-test = 2.536 (> 1) confirm the statistical significance of the differences in the mean values of the groups of variables under verification. This allows us to arrive at the conclusion that customers with better sat-
ip marketing productivity using the RMBS
isfaction have the largest share in the company's total sales volume, and vice versa. Consequently, the contribution of customer relationships to the company's annual income is largely dependent on customer satisfaction with the product and the interaction process with the company.
Test of Hypothesis 2. The values p < 0.05 and F-test = 5.38 (> 1) confirm the hypothesis that the company's employees with a high level of satisfaction build a long-term relationship with customers, which proves their work to be effective.
Test of Hypothesis 3. The values of the correlation coefficients for both the entire customer database (R = 0.349 when p < 0.01) and the target segments (R = 0.631 when
Table 2 - Hypotheses about the factors affecting relationship marketing productivity (the case study of the APAT)
Hypothesis Methods for testing the hypothesis
1. Customers with better satisfaction have the largest share in the company's total sales volume One-way ANOVA, analysis of contingency tables
2. Employees with a high level of satisfaction build a long-term relationship with customers One-way ANOVA, analysis of contingency tables
3. There is an interrelation between target customer satisfaction and customer lifetime value Pairwise correlation analysis
p < 0.01) demonstrate that there is a positive correlation between customer profitability and customer satisfaction with the interaction process with the company. In addition, this correlation is much higher for the target segment (R=0.631 when p > 0.5) if compared to the company's entire customer database. At the same time, rather low values of correlation coefficients indicate that, apart from customer satisfaction, there are other factors influencing profitability which are associated with the peculiarities of the business. It is necessary, therefore, to identify these factors by using the technique of in-depth interviewing with clients and by examining the specificity of the key customers' business.
The method of in-depth interviewing helped us to find that, according to a certain amount of customers of the Aramil Plant of Advanced Technologies, the company was sometimes irregular in fulfilling the order in full and providing a timely warranty repair of insulants. We have revealed the need to organize the system for online orders and online support. These weaknesses of the organisational mechanism for establishing a customer relationship require
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a marketing program and activities aimed at increasing . relationship marketing productivity to be developed. The 5 authors also gave some recommendations to the APAT: to forge closer relationships with organizations exhibiting a relatively low level of satisfaction and prospective values of customer lifetime value (CP and CLV); to arrange visits of sales managers and technical support specialists to the enterprises; to initiate personal contacts with those who are responsible for procurement; to ensure the targeting of information sent to an organization; to track the feedback regularly.
The implementation of the proposed measures in 2017 resulted in the overall positive dynamics of all the RMBS indicators (Table 3).
The overall dynamics of all the indicators of relationship marketing productivity of the enterprise is positive; the values of consumer loyalty index, customer retention rate and customer profitability have increased. Implementation of the measures for enhancing relationship marketing productivity resulted in an increase in the company's revenue by 1.4%.
Table 3 - The dynamics of the RMBS indicators of the Aramil Plant of Advanced Technologies after the implementation of the relationship marketing program in 2017
Indicator Values of marketing metrics Increment to 2016, %
1. Total number of customers 74 companies 0
2. Number of the target segment customers 30 companies 3,45
3. Share of customers in the target segment "large customers", % 40,5 1,5
4. Share of the target segment customers in sales volume, % 92 3
5. Net Promoter Score in the target segment (NPS), % 52,3 4,3
6. Net Promoter Score (NPS), % 32,4 4
7. Target segment customer profitability, rubles CP of the most profitable customer CP of the least profitable customer 11 698 136,13 1 415 129,71 1,2 0,9
8. Customer retention rate (CRR), % 89,8 0,9
9. CLV of the target segment customer, rubles CLV of the most profitable customer CLV of the least profitable customer 47 319 487,59 5 724 263,42 5,39 6,07
10. Share of new clients, % 2,8
11. Average duration of a customer relationship, years Average duration of a target segment customer relationship 6,12 6,52 14,39 14,59
12. Annual income 1,4
13. Employee satisfaction, score Score 7,96
^ CONCLUSION
z
® The conducted research proved the relevance of meas-£ uring relationship marketing productivity of an industrial g enterprise in the B2B market, which allowed evaluating the =r return on investment in customer relationships and its influ-5 ence on the company's financial performance. | The authors distinguished the five methodological apS proaches to measuring the productivity of relationship marketing based on the various criteria of the diversity of the company's partners and the outcome of relationships: Company - Customer Retention - Profitability; Supplier - Company - Customer; Company - Creating value jointly with the customer; Company - Network interaction efficiency; Company - Integration of marketing into a company's general management system.
The authors chose to apply the integrated approach as the one corresponding to the specificity of the industrial market and today's business requirements. To hold a holistic view of the productivity of relationship marketing management, the authors split the integrated analysis of the RMBS indicators and their dynamics into stages and identified the interrelation of the marketing indicators for various business perspectives.
To test the proposed approach, we measured relationship marketing productivity of the Aramil Plant of Advanced Technologies and put forward the following hypotheses:
1) customers with better satisfaction have the largest share in the company's total sales volume;
2) employees with a high level of satisfaction build a long-term relationship with customers;
3) there is an interrelation between target customer satisfaction and customer lifetime value.
The hypotheses were tested using statistical methods and by holding in-depth interviews with customers and suppliers. The test results confirmed that relationships with partners exerted a significant effect on the industrial enterprise's financial performance. The calculation of the RMBS indicators and their analysis made it possible to design a relationship marketing program, the implementation of which resulted in an increase in the company's revenue.
The strengths of the authors' approach to measuring the productivity of relationship marketing are:
1) optimization of the system of marketing indicators;
2) assessment of return on investment in marketing activities for all business perspectives;
3) attention to the role of suppliers in measuring relationship marketing productivity of an industrial enterprise;
4) a possibility to adjust the goals and strategies of relationship marketing management according to the results of the analysis of absolute values and the dynamics of the balanced scorecard of relationship marketing of an industrial enterprise.
Источники
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12. Finch D., O'Reilly N., Hillenbrand C., Abeza G. Standing on the Shoulders of Giants: An Examination of the Interdisciplinary Foundation of Relationship Marketing. Journal of Relationship Marketing, 2015, vol. 14, no. 3, pp. 171-196.
13. Finch D., O'Reilly N., Abeza G. The Independent Sales Contractor and Relationship Quality: An Exploratory Study of Relational Attitudes and Behavioral-Intention. Journal of Relationship Marketing, 2018, vol. 17, no. 2, pp. 152-169.
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15. Gummesson E. Total Relationship Marketing. Rethinking Marketing Management: From 4 Ps to 30 Rs. Oxford: Butterworth-Heinemann, 1999.
16. Gupta S., Hanssens D., Hardie B. et al. Modeling Customer Lifetime Value. Journal of Service Research, 2006, vol. 9, no. 2, pp. 139-155.
17. Hougaard S., Bjerre M. Strategic Relationship Marketing. Heidelberg: Springer-Verlag, 2002.
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20. Rust R., Ambler T., Carpenter G.S. et al. Measuring Marketing Productivity: Current Knowledge and Future Directions. Journal of Marketing, 2004, vol. 68, no. 4, pp. 76-89.
21. Sheth J.N., Parvatiyar A., Sinha M. The Conceptual Foundations of Relationship Marketing: Review and Synthesis. Journal of Economic Sociology, 2015, vol. 16, no. 2, pp. 119-149.
22. Storbacka K., Strandvik T., Grönroos C. Managing customer relationship for profit: the dynamics of relationship quality. International Journal of Service Industry Management, 1994, vol. 5(5), pp. 21-38.
23. Vollmann T., Cordon C., Raabe H. From Supply Chain Management to Demand Chain Management. IMD Perspectives for Managers. November, 1995.
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