Customer Metrics Research Articles

Relative importance of competing marketing strategies on different customer metrics: a meta-analytic review of customer equity drivers

Purpose This meta-analytic study aims to generalize the impacts of three customer equity drivers (CEDs), including value equity (VE), brand equity (BE) and relationship equity (RE), on different customer metrics (e.g. loyalty, word of mouth [WoM] and satisfaction); examine the relative importance of CEDs on customer metrics; and explore boundary conditions, considering geographic and methodological characteristics. Design/methodology/approach This study used a meta-analytic approach, collected and coded 85 articles published between 2001 and 2022. After some exclusions, the authors used 272 observations (average of individuals’ sample M = 1,015, min = 10, max = 8,924). Findings The generalized effects of VE, BE, and RE on the selected customer metrics are positive. However, the importance of each CED differs for WoM and social equity. Between VE and BE, BE correlates more with WoM. RE correlates more with social equity than VE and BE That is, RE is effective in both WoM and social equity. In addition, the impacts of the CEDs on customer loyalty vary across multiple geographic and methodological characteristics. For example, the impacts of VE and RE on loyalty are stronger in more individualistic, more masculine, long-term orientation or more restraint cultures. Research limitations/implications While the authors examined VE, BE and RE as the most important marketing strategies, there might be other types of CEDs, such as interactions with others (e.g. employees and customers). Interactions with others at any touchpoints along the customer journey are important experiences (Lemon and Verhoef, 2016). Second, the authors limited the customer metrics to customer loyalty, WoM, customer satisfaction, customer trust and social equity. Practical implications The magnitudes of VE, BE and RE differ across the three customer metrics. Compared with VE, BE symbolizes customers’ identity, status and extended self, which motivates WoM. Compared with VE and BE, RE convinces customers of companies’ actions in social equity such as corporate social responsibilities. Originality/value The meta-analysis resolves the issue of inconsistent impacts of CEDs across studies. Moreover, including CEDs in a model provides insight into these strategies’ relative importance when considering different marketing objectives. Finally, this study enriches understanding of the boundary conditions on the CEDs–loyalty link.

Predicting e-commerce CLV with neural networks: The role of NPS, ATV, and CES

Accurately predicting Customer Lifetime Value (CLV) is paramount in optimizing customer relationship management. This study introduces a novel deep learning approach, employing a neural network model to forecast CLV for a leading international e-commerce retailer. This investigation delves into the interplay of key performance indicators—Net Promoter Score (NPS), Average Transaction Value (ATV), and Customer Effort Score (CES)—and their collective impact on CLV. The research utilized a dataset of 15,000 customer profiles and crafted a sequential neural network with dense layers optimized through hyperparameter tuning and regularization to thwart overfitting. The model's efficacy was assessed on a 10 % test set, revealing its adeptness at capturing intricate, nonlinear predictor-customer lifetime value (CLV) relationships. Consistency in training and test performance metrics underscored the model's generalizability, while high R-squared and explained variance scores confirmed the predictive strength of the chosen factors. This research seeks to provide a solution for building an artificial intelligence model with an artificial neural network algorithm to predict customer lifetime value. By incorporating this principle, the study aims to leverage the power of neural networks to forecast CLV, enabling retailers to make informed decisions and optimize customer relationships accurately. This study finds that Net Promoter Score (NPS) and Customer Effort Score (CES) have a powerful impact on the neural network model's ability to predict Customer Lifetime Value (CLV) accurately. On the other hand, while Average Transaction Value (ATV) exhibits the least impact, it still significantly contributes to the accuracy of Customer Lifetime Value (CLV) predictions. These results underscore the importance of incorporating customer feedback metrics like NPS and CES when building predictive models for CLV estimation. Integrating critical customer metrics into neural networks gives retailers enhanced insights, enabling precise customer segmentation, resource allocation, and strategic growth. The study paves the way for future research to refine further CLV prediction, including dataset expansion, customer profile enrichment, and prescriptive marketing optimization.

Pendekatan Balance Scorecard Dalam Menganalisis Pengukuran Kinerja Bank Negara Indonesia (Persero) Tbk

This research seeks to assess PT. BNI (Persero) Tbk's performance through the utilization of the balanced scorecard approach, encompassing financial, customer, internal processes, and learning/growth perspectives. The study, employing a descriptive method, focuses on PT. BNI (Persero) as the sample population, utilizing documentation techniques for data collection. Results indicate favorable financial indicators (ROA, ROE, NPM, BOPO, LDR), subpar customer metrics (customer acquisition, retention), excellent internal business processes (AETR, NGR), and positive learning/growth aspects (employee productivity, ETTE).

Marketing Metrics in the Wine Retailing Industry

Over the years, many companies integrated the Key Performance Indicators (KPIs) tools, into their reporting activities, leading to a deep transformation of the business models and marketing strategies. This study has dual aims: first, to recognize and validate the studies on Marketing Performance Measurement (MPM) in the wine retailing industry; second, to examine the relationships among the firm’s efforts to apply marketing metrics and some characteristics of the competitive environment. To reach these research aims, data on the overall 31 wineries were collected and analyzed in three different countries. The main research tool is the structured questionnaire that considers three different marketing metrics dimensions, that is transactional, attitudinal and web customer metrics. Subsequently, by a structural equation method (PLS-PM), it will be statistically estimated the weight of marketing metrics in the wine retailing industry.

A critical psychometrical analysis of customer relationship management practices in the Local Government Authorities in SADC

The purpose of the study is to explore the critical success factors for CRM in the local government authorities in SADC. Although many empirical studies have been conducted on customer-relationship-management (CRM), little research on the psychometric properties of CRM scale items in the local government authorities’ context has been conducted. This empirical study, based on key informant data drawn from sampled local government authorities in three SADC countries (Zimbabwe, Botswana and South Africa), developed a reliable scale with demonstrated content and convergent validity. In this study, confirmatory factor analysis (CFA) was employed using the Amos 18 version and the SPSS version 20 software. The study results revealed that for CRM Strategy success to be achieved, LGA needs to consider the following factors: Due diligence, Strategy focus and alignment, customer focus, change management, Implementation Strategy, Implementation approach, Metrics, Project management, Process design, Buy-in and adoption. Therefore, the study results suggested that city and town council managers must seriously consider all the ten critical success factors to improve the CRM performance of local government authorities.

The interplay of marketing performance measurement and market orientation leading to high business performance in manufacturing SMEs

ABSTRACT Whereas marketing performance measurement (MPM) and market orientation (MO) are among the most studied marketing concepts, there is still a lack of knowledge about the configurations leading to high business performance. Therefore, we performed a fuzzy-set qualitative comparative analysis (fsQCA) in the context of 150 manufacturing SMEs combining customer, competitor, and financial metrics of MPM, MO level, and both subjective and objective business performance. The goal was to identify MPM and MO configurations leading to high business performance. We found, identically with the prior research, that high-performing SMEs benefited from the combination of high MO and focusing only on particular domains of MPM (customer, financial). However, contrary to the previous investigation, we also found configurations in which a high MO level was not necessary for high business performance when substituted with the appropriate MPM system, dominated by competitor metrics. Our study supports the conclusion of diverse paths to business success.

Attribution done right: How to prove the real value of marketing

Marketing attribution models are used by businesses to keep the marketing department accountable for the expenditure and the resources they use, as marketing is often seen as a cost centre within many organisations. Marketers implement marketing attribution models for two purposes. Firstly, to justify the money spent on marketing campaigns and activities, and secondly, to identify which marketing channels and tactics produce the desired results or outcomes. However, marketing departments continually struggle to use marketing attribution models to justify expenditure or show results. The most common reasons many marketers struggle to implement attribution models are issues with data integrity, lack of knowledge around how to effectively use marketing attribution tools and the sheer complexity of the buyer's journey. In this paper, it is argued that the actual problem lies in how marketers perceive the use of attribution reporting. Furthermore, it is posited that those reasons are just symptoms of a larger problem with marketers' approach to marketing attribution. If marketers want to use attribution successfully then they need to change the purpose of their attribution models to focus on customer metrics and not business outcomes. Nearly all marketing attribution focuses on return on investment as a desired outcome; however ROI is a business outcome, not a customer metric. Focusing on customer metrics such as brand awareness, brand engagement and churn rate will provide marketers with the informed outcomes they desire. The ability to gain insight from an attribution model comes from establishing the goal of the attribution model and then aligning the proper marketing metrics to the desired outcome.

Boots’ ‘prescribe kindness’ campaign: A case study of one UK retailer’s response to the COVID-19 pandemic

This paper covers the marketing programmes undertaken during the COVID pandemic by Boots, the UK’s leading health and beauty retailer (part of Walgreens Boots Alliance, with over 2,200 stores ranging from local community pharmacies to large destination health and beauty stores) whose purpose is to serve their customers’ well-being for life. At the start of the pandemic, Boots introduced a new approach, ‘Prescribe Kindness’, throughout the business and in its ongoing communication to customers. The retailer used research and social listening to capture the mood of the nation and the questions and concerns voiced by many during an unprecedented period of certainty. Using this insight, Boots was able to produce timely and relevant content targeted at the right consumers at the right time, meeting their need to have the very best and most relevant health and well-being information during and beyond periods of lockdown. As a result, Boots saw an unprecedented increase in customer engagement and strengthened brand health and customer metrics, which have given the brand a strong foundation as consumers’ lives evolve again beyond the original periods of lockdown in the UK. The brand has also learnt valuable lessons on delivering a faster speed to market with more relevant and targeted content tapping into themes that are highly relevant in people’s lives today and has helped to shape its new brand purpose — ‘Boots. With You. For Life’.

P 67 Satisfaction with and reliability of in-hospital video-electroencephalography monitoring systems in epilepsy diagnosis among German epilepsy centers

Introduction: Video-electroencephalography monitoring (VEM) is the current gold standard for in-hospital epilepsy diagnosis as well as for the diagnostics of many other paroxysmal and recurrent neurological symptoms. Consequently, high-performance VEM systems (VEMS) have become indispensable for performing modern in-hospital differential and presurgical epilepsy diagnostics. As a central diagnostic tool and interface between technology and doctors, VEMS also represent a relevant safety factor in inpatient diagnostics. Recently, complaints about malfunctions of VEMS have been reported repeatedly, some of which hinder the clinical diagnosis of epilepsy patients. Therefore, we investigated the reliability of, customer satisfaction with and potential for improvement of the VEMS used in German epilepsy centres. Materials and Methods: Between December 2020 and January 2021, a survey was conducted among German epilepsy centres. Using a short questionnaire including established business to customer metrics, such as the Net Promoter Score, the Customer Satisfaction Score, the Customer Effort Score and the Things Gone Wrong Metric, the reliability, customer satisfaction and potential for general or specific improvements of VEMS were accessed without aiming to compare individual manufacturers or systems in detail. Results: A total of 16 of 27 contacted epilepsy centres (59%) participated in the survey. Customer satisfaction with VEMS was low with only 13 % of clients that would actively recommend their system to other clinicians or epileptologists. Only 50 % of users were satisfied with the overall performance of their VEMS, and only 18 % were satisfied with the manufacturer's after-sales service. Major software or hardware problems were reported in the diagnostic of approximately every 10th patient. Common problem areas mentioned were the VEMS user interface, the stability of software, a shortage of regular updates and a lack of customer-oriented improvements. The greatest potential for improvement was found in software and hardware stability as well as in customer service. Conclusion: As far as it can reasonably be assessed from this German multicenter survey, the level of satisfaction among German epilepsy centres regarding their VEMS is soberingly low. This unsatisfaction seems to be mainly based on frequent and sometimes serious malfunctions of hardware and software on the one hand and a subjective dissatisfaction with the manufacturer’s aftermarket customer service on the other hand. The fact that on average the diagnosis of every 10th patient is hampered by hardware or software problems should be an alarming sign, regardless of the general satisfaction with VEMS. Besides the obvious potential for improvement, there is an urgent need for national and international functional and safety standards for VEMS.

CX transformation of Tele2: From a discounter to a customer service leader

The case is devoted to the transition of the telecommunications company Tele2 to a management system based on the principles of continuous improvement of customer experience, or CX-transformation. The case describes the development of Tele2 in the Russian cellular market in 2003–2020. Firstly, it outlines the main aspects of the Tele2’s business strategy in 2003–2016. Secondly, it provides a detailed description of events that took place in 2015–2016, when Tele2’s financial and operational performance indicators dwindled, and the mobile operator was challenged to develop a new business strategy that meets the changing market realities. Finally, there is a description of a new customer-focused strategy that implied the integration of customer metrics into all organizational processes and the restructuring of the internal customer experience management system. The case describes actions taken by the company during 2017–2020 to implement customer experience management practices and outlines the key results of Tele2’s CX transformation. The case is based on Tele2’s internal reports, retrospective interviews with the company’s representatives involved in the CX transformation process, and secondary opensource information. The case can be used to discuss the prerequisites, goals, components, and success factors of CX transformation.

The Psychometric Properties of Customer Relationship Management Framework in the Local Government Authorities in Zimbabwe

Although a lot of empirical studies have been conducted on customer-relationship-management (CRM), little research on the exploration of the psychometric properties of CRM scale items, in the Zimbabwean context has been conducted. This empirical study, based on key informant data drawn from sampled local government authorities in Zimbabwe (LGAZ), developed a reliable scale with demonstrated content and convergent validity. Amongst some of the reliable and valid antecedents and consequences of CRM Strategy success the study found; Due diligence, Strategy focus and alignment, Customer focus, Change management, Implementation Strategy, Implementation approach, Metrics, Project management, Process design, Buy-in and adoption to be some of the most important.. Therefore, using the confirmatory factor analysis approach, the research findings offer one more robustness in the applicability of CRM scale items by confirming that CRM city managers use psychometrically valid scale items to generate, disseminate and respond to information with a view to improving CRM performance of LGAZ.

An analysis of configurations of relationship quality dimensions to explain sources of behavioral outcomes in globalized manufacturing

PurposeThis paper aims to explore the role of configurations of relationship quality dimensions for explaining sources of behavioral outcomes in the globalized manufacturing industry.Design/methodology/approachA joint analysis of behavioral and objective performance data from globalized manufacturing links perceptual customer metrics that relate to dimensions of relationship quality (i.e. attitudinal loyalty, perceived customer orientation, customers’ perceived innovativeness of the supplier and perceived customer influence on supplier innovation) with behavioral outcomes (i.e. share of wallet (SOW) and customer account profitability). Using data from a global business-to-business (B2B) customer survey together with archival performance data from a multinational mechanical engineering firm, a fuzzy set qualitative comparative analysis (fsQCA) is performed.FindingsThe fsQCA results suggest that perceptual customer metrics related to innovation can be relevant aspects of relationship quality, in line with Anderson and Mittal’s (2000) satisfaction-repurchase-profitability chain framework and its adaptation to SOW. However, the underlying complexities in the different combinations of attributes in the recipe are such that they are not equifinal in leading to higher SOW or higher profitability. This paper finds indications for non-linearities between perceptual measures investigated and profitability of customer accounts, with particular relevance for the role of perceived customer orientation, perceived product innovativeness of the supplier and attitudinal loyalty.Research limitations/implicationsThe analysis faces a number of limitations, starting with its reliance on cross-sectional survey data, which does not enable us to account for feedback mechanisms, for example, arising from customer perceptions regarding innovation aspects. The lack of a multidimensional conceptionalization of the perceptual customer constructs may have limited the analysis, considering also recent evidence from retail companies in the furniture sector in Spain, suggesting that the multidimensional conceptualization of relationship value explained satisfaction and loyalty levels to a greater extent than the one-dimensional conceptualization (Ruiz-Martínezet al., 2019).Practical implicationsIn terms of managerial implication, the results suggest that customers perceive limited value in participating in the focal firm’s innovation value chain funnel, hence customer loyalty cannot be bought using simple incentive strategies. The results with regard to customer account profitability suggest that B2B customers investigated here may distinguish when interacting with their globalized supplier in the innovation funnel: they may see a positive customer value when the innovation is a product, and thus, relation-specific, whereas they may see limited customer value when innovation is considered in more generic terms (customers’ perceived influence on supplier innovation in general).Originality/valueThis paper starts from the premise that perceptual customer metrics can matter for supplier performance, as the customer relationship and customer value management research has shown. However, there is limited empirical evidence from globalized manufacturing sectors incorporating perceptual constructs in behavioral outcomes, and limited evidence assessing customer-perceived value in such sectors through alternate approaches to main-effects focused analyzes. We employ qualitative comparative analysis using fuzzy sets (Russoet al., 2019) to address these gaps, focusing on two key behavioral outcomes, namely, customer account profitability and SOW.

Customer Satisfaction With Communications Services in the US: Room for Improvement?

The study of customer satisfaction and service quality is relatively new. Some of the landmark studies guiding investigations today were published only in the late 1980’s and 1990’s. Given the room for improvement in customer satisfaction with communications services, how can the FCC incorporate these more sophisticated perspectives on customers into our regulatory and policy work? Improving customer satisfaction broadly is it itself an important element of the public interest. Further, higher levels of customer satisfaction are likely to improve communications services’ contribution to the country’s overall production. This paper will review the literature, highlighting several points. 1. An overview of customer metrics from the study of marketing 2. An introduction to the American Customer Satisfaction Index (ACSI), the most widely used measure of customer satisfaction. 3. The empirical link between a firm’s growing market share and declining customer satisfaction. 4. A discussion of SERVQUAL the most widely used instrument to measure service quality. 5. The positive link between customer satisfaction and a firm’s financial performance 6. The positive link between customer satisfaction and a firm’s stock price 7. Ideas on future work

Social innovation in service: a conceptual framework and research agenda

PurposeThe purpose of this paper is to provide a framework for guiding social innovation in service (SIS), defined as the creation of novel, scalable and sustainable market based service offerings that solve systemic societal problems.Design/methodology/approachThis research provides a review and synthesis of transdisciplinary literatures to establish a basis for the conceptual framework proposed for SIS.FindingsIt is argued that the primary unit of an SIS is the service firm and that there are micro-, meso-, and macro-level actors and enablers in the ecosystem that can help bring about SIS. Examples from the hospitality and tourism industry are used to demonstrate key points.Practical implicationsBenefits of an SIS to companies include growth through new markets and innovative value offerings, sustainable supply chains in production, building consumer value and trust in the company/brand, attracting and retaining talent and being proactive in including social and environmental measures of success in customer metrics and company financial reporting.Originality/valueThis paper contributes to the social innovation and service literature by: offering a new, scientifically supported view of an SIS; providing managers with a framework to guide social innovation within their service firm and for the benefit of their company and its stakeholders; and directing service scholars to research issues necessary to advance SIS.

Modeling the relationship between firm and user generated content and the stages of the marketing funnel

While research has successfully linked social media to separate customer metrics, an in-depth conceptual and empirical understanding of how social media affects the stages of the marketing funnel is currently lacking. We draw on extant theories of consumer information processing and source credibility to conceptually link and contrast the relationships between firm generated content (FGC) dimensions of neutral valence, positive valence and vividness, user generated content (UGC) dimensions of volume and valence and the marketing funnel stages of awareness, consideration, purchase intent and satisfaction. Using daily aggregate brand-level data for 19 brands across seven industries, our analysis shows that UGC dimensions have a stronger relationship with awareness and satisfaction while FGC dimensions are more effective for consideration and purchase intent. Specifically, we observe that FGC vividness has the strongest relationship with consideration and purchase intent, while UGC valence dominates UGC volume for these stages. Our results also show that brands with higher corporate reputation have stronger relationships between dimensions of FGC and the marketing funnel stages. Findings by consumption category show that UGC and FGC dimensions have larger positive relationships with awareness for durables and non-durables, and with consideration, purchase intent, and satisfaction for services. Thus, overall, our study offers critical managerial insights into social media marketing regarding how to leverage both FGC and UGC in managing the marketing funnel and brand reputation.

Measuring Relationship Marketing Productivity in the Industrial Market

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 (singlefactor 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.

Workforce engagement: What it is, what drives it, and why it matters for organizational performance

SummaryBased on a review of the history of the employee engagement construct and its measurement, we define workforce engagement as the aggregate of the work engagement experiences of individual employees in an organization. In contrast to most research on employee engagement, we study companies rather than individuals and the companies represent a diverse set of industries. We hypothesize and demonstrate on a sample of (up to) 102 publicly traded companies that workforce engagement significantly predicts organizational financial (adjusting for industry: Return on Assets, Net Margin but not Tobin's q) and customer metrics (the American Customer Satisfaction Index and the Harris Reputation Quotient) 1 and 2 years after the workforce engagement data were collected. In addition, using a split‐sample approach to avoid method bias, we hypothesize and show that (a) company organizational practices (the strongest correlate), supervisory support, and work attributes are significant correlates of workforce engagement and (b) that workforce engagement mediates the relationship between these correlates of engagement and the organizational performance metrics. Implications of the findings for research and practice are discussed.

Customer Lifetime Value

This technical note introduces important metrics firms use to monitor customer relationships. An important summary of customer activity is the profit the firm receives from each customer. profit (CP) is the metric that summarizes the past financial performance of a customer relationship and is covered in a companion note, Customer Profit (UVA-M-0799). The central difference between CP and customer lifetime value (CLV) is that CP measures the past and CLV looks forward. This note addresses the forward-looking metric that attempts to put a dollar value on a customer relationship.This technical note is an excerpt of the more comprehensive treatment of customer metrics found in Customer Profitability (UVA-M-0718). Excerpt UVA-M-0800 Rev. Jun. 19, 2014 Customer Lifetime Value As Don Peppers and Martha Rogers are fond of saying, “Some customers are more equal than others.” One way to examine these differences is through customer profit (CP), the difference between the revenues and the costs associated with the customer relationship during a specified period. The central difference between CP and customer lifetime value (CLV) is that CP measures the past and CLV looks forward. As such, CLV can be more useful in shaping managers' decisions but is much more difficult to quantify. Quantifying CP is a matter of carefully reporting and summarizing the results of past activity, whereas quantifying CLV involves forecasting future activity. Customer Lifetime Value: The Present Value of the Future Cash Flows Attributed to the Relationship The concept of CLV is nothing more than the concept of present value applied to the cash flows of the customer relationship. The present value of any stream of future cash flows is designed to measure the single lump-sum value, today, of those future cash flows. CLV represents the single lump-sum value, today, of the customer relationship. Even more simply, CLV is the dollar value of the customer relationship to the firm. It is an upper bound on what the firm would be willing to pay to acquire the customer relationship as well as an upper bound on the amount the firm would be willing to pay to avoid losing the customer relationship. If we view a customer relationship as an asset of the firm, CLV would represent the dollar value of that asset. One way to project the value of future customer cash flows is to make the heroic assumption that the customers acquired several periods ago are no better or worse (in terms of their CLV) than the ones currently acquired. We then go back and collect data on a cohort of customers, all acquired at about the same time, and carefully reconstruct their cash flows over some finite number of periods. The next steps are to discount the cash flow for each customer back to the time of acquisition, to calculate the sample customers' CLVs, and then to average all sample CLVs together to produce an estimate of the CLV of each newly acquired customer. This method is referred to as the “cohort and incubate” approach. Equivalently, one can calculate the present value of the total cash flow from the cohort and divide by the number of customers to get the average CLV for the cohort. If the value of customer relationships is stable across time, the average CLV of the cohort sample is an appropriate estimator of the CLV of newly acquired customers. . . .

Do Disclosures of Customer Metrics Lower Investors’ and Analysts’ Uncertainty but Hurt Firm Performance?

Investors, analysts, and regulators frequently advocate greater disclosure of nonfinancial information, such as customer metrics. Managers, however, argue that such metrics are costly to report, reveal sensitive information to competitors, and therefore will lower future cash flows. To examine these counterarguments, this study presents the first empirical examination of the prevalence and consequences of backward- and forward-looking disclosures of customer metrics by manually coding 511 annual reports of firms in two industries, telecommunications (365 reports) and airlines (146 reports). The results reveal significant heterogeneity in the disclosure of customer metrics across firms and between industries. On average, in both industries, firms make more backward-looking than forward-looking disclosures. Notably, forward-looking disclosures of customer metrics are negatively associated with investors’ uncertainty in both industries and with analysts’ uncertainty in the telecommunications industry. Importantly, the results do not support the managerial thesis that such disclosures have a negative impact on future cash flows.

STUDY OF CLIENT VARIABLES INFLUENCE ON THE PERFORMANCE OF RETAIL COMMERCIAL ENTERPRISES

There are four groups of indicators influenced on the performance of retail commercial enterprise. They are characteristics of the store (retail space), store location, transport and pedestrian accessibility of the store and the attitude of buyers to the shop (customer metrics). The present paper is dealt with the influence of the fourth group- «customer metrics ". The authors of this article consider such factors of this group as: the work of salespeople and other staff; the internal atmosphere of commercial enterprise; the security area of the enterprise location; brand awareness; additional services. The article describes the application of the proposed approach to the assessment and change forecast of turnover depending on the studied factors using the method of fuzzy logic by the example of the results of such shops as "Ocean" and "Pervomayskiy", retail outlets "Gastronom" format "supermarket", Izhevsk. The authors define term-sets and membership functions for each client criterion. The rule base is also developed. The presence of aggregate functions is implemented by Mamdani logical inference, which uses the min-max composition of fuzzy sets. The adequacy of the proposed mathematical model is performed on the example of results forecasting of investigated stores activities "retail network " Gastronom " format "supermarket" (Izhevsk, Russia) using the software Matlab, and then comparing the calculated value of the average purchase with actual. Monitored client performance on the basis of a network "Gastronom" has also allowed the authors to develop recommendations for shops as described in this article.