Understanding customer experience

Anyone who has signed up for cell phone service, attempted to claim a rebate, or navigated a call center has probably suffered from a company's apparent indifference to what should be its first concern: the customer experiences that culminate in either satisfaction or disappointment and defection. Customer experience is the subjective response customers have to direct or indirect contact with a company. It encompasses every aspect of an offering: customer care, advertising, packaging, features, ease of use, reliability. Customer experience is shaped by customers' expectations, which largely reflect previous experiences. Few CEOs would argue against the significance of customer experience or against measuring and analyzing it. But many don't appreciate how those activities differ from CRM or just how illuminating the data can be. For instance, the majority of the companies in a recent survey believed they have been providing "superior" experiences to customers, but most customers disagreed. The authors describe a customer experience management (CEM) process that involves three kinds of monitoring: past patterns (evaluating completed transactions), present patterns (tracking current relationships), and potential patterns (conducting inquiries in the hope of unveiling future opportunities). Data are collected at or about touch points through such methods as surveys, interviews, focus groups, and online forums. Companies need to involve every function in the effort, not just a single customer-facing group. The authors go on to illustrate how a cross-functional CEM system is created. With such a system, companies can discover which customers are prospects for growth and which require immediate intervention.     

Accounting for organizational performance: The construction of the customer in the privatized water industry

The concept of the customer exercising market power to obtain the desired combination of attributes in terms of price and quality of the product to be purchased has been integral to the Conservative Government's justification of privatization. However the practical import of giving effect to customer sovereignty was problematic if it was not accompanied by an increase in competition and choice for customers. This is particularly true of the recently privatized Water industry, where the monopoly character of the industry has remained unaltered. To give effect to its claims that customers would benefit, and to prevent overcharging and to protect standards of service, the Government had to introduce a new regulatory system operated by the Office of Water Services (Ofwat). In pursuing these objectives the Director General of Ofwat has stated that his aim is to secure for the customer a place that he/she would have were the companies operating in a competitive market. This paper, drawing on Miller and Rose's analysis of Governing economic life, examines the attempts that have been made to give effect to this “place for customers”. In doing so much of the analysis focuses on exploring how notions of “the customer”, and “customer service”, have been constructed through new forms of accounting and accountability, and how this new accounting for customer service has enabled the concept of “the customer” to be made operational within the newly privatized Water plcs, even though their monopoly status has remained unaltered. Central to this has been Ofwat's determination of performance indicators on levels of service to customers, its measurement of company performance against these indicators, and assessments based on these measures of companies' success in “serving customers”. The paper seeks to demonstrate how these new accounts of organizational performance required of the Water plcs by Ofwat have only been made possible by rendering “customer service” a calculable and comparable entity. The paper also looks at some of the ways in which this accounting for customer service has been incorporated into other accounts of managerial and organizational performance.     

An approach for the identification of cross-sell and up-sell opportunities using a financial services customer database

The collection, management and manipulation of customer data are key to the successful operation of many relationship marketing and customer relationship management endeavours. To make effective use of the data, however, requires that organisations know how to analyse it in order to generate valuable information for marketing purposes. One of the key challenges to maintaining an ongoing relationship with customers is to be able to predict what products customers will need to buy next and at what point so that appropriate marketing offers can be made. This paper illustrates an analytical approach that can be used in such a situation. Using actual customer data from a financial institution, the paper illustrates the application of segmentation analysis, purchase acquisition trees and survival analysis. While the results are of particular interest to financial institutions, the methodology has applicability in a number of contexts where customer data are available.     

Share of wallet's role in customer profitability

Understanding the financial contribution customers make to their organisations is an initial step in customer relationship management. Set in the banking industry, this paper examines the strength of ‘share of wallet’ as a proxy variable for measuring customer profitability. Data from a study of 1,100 personal retail banking customers of a New Zealand regional bank were used in combination with the bank's own customer contribution data for each of those respondents. Results indicate that although share of wallet might be used as a proxy for customer contribution at a macro level of customer classification, details of specific financial relationships customers have with their main bank are still necessary. Nevertheless, share of wallet ought to become a standard entry in a bank's customer database.     

Valuing customers and loyalty: The rhetoric of customer focus versus the reality of alienation and exclusion of (de valued) customers

The accounting practice of customer valuation ostensibly emerged from the so-called “customer revolution" of the 1980s. Early conceptions centred around notions such as customer focus and providing value to customers, but these ideas have latterly given way to calculation of the financial value of customers to an organisation. Integral to customer valuation are the reconstruction of the customer as an asset (or liability) of the organisation, the segmentation of customers into identifiable groups, and the treatment of customers as dollars rather than people. Whilst rhetoric of “the customer is king" persists, accounting for customer valuation brings its own transformative terminology and has become a means for organisations to selectively focus on particular customers, rather than the customer in general. The paper examines the health insurance and banking industries as exemplars of the affects of customer valuation, and discusses pivotal issues of access, equity, alienation, and social exclusion. Customer valuation is shown to have become a means to increase shareholder income and wealth, almost inevitably at the cost of (further) marginalising the poor and disadvantaged.     

The mismanagement of customer loyalty

Who wouldn't want loyal customers? Surely they should cost less to serve, they'd be willing to pay more than other customers, and they'd actively market your company by word of mouth, right? Maybe not. Careful study of the relationship between customer loyalty and profits plumbed from 16,000 customers in four companies' databases tells a different story. The authors found no evidence to support any of these claims. What they did find was that the link between customers and profitability was more complicated because customers fall into four groups, not two. Simply put: Not all loyal customers are profitable, and not all profitable customers are loyal. Traditional tools for segmenting customers do a poor job of identifying that latter group, causing companies to chase expensively after initially profitable customers who hold little promise of future profits. The authors suggest an alternative approach, based on well-established "event-history modeling" techniques, that more accurately predicts future buying probabilities. Armed with such a tool, marketers can correctly identify which customers belong in which category and market accordingly. The challenge in managing customers who are profitable but disloyal--the "butterflies"--is to milk them for as much as you can while they're buying from you. A softly-softly approach is more appropriate for the profitable customers who are likely to stay loyal--your "true friends." As for highly loyal but not very profitable customers--the "barnacles"--you need to find out if they have the potential to spend more than they currently do. And, of course, for the "strangers"--those who generate no loyalty and no profits--the answer is simple: Identify early and don't invest anything.     

The quest for customer focus

Companies have poured enormous amounts of money into customer relationship management, but in many cases the investment hasn't really paid off. That's because getting closer to customers isn't about building an information technology system. It's a learning journey-one that unfolds over four stages, requiring people and business units to coordinate in progressively more sophisticated ways. The journey begins with the creation of a companywide repository containing each interaction a customer has with the company, organized not by product, purchase, or location, but by customer. Communal coordination is what's called for at this stage, as each group contributes its information to the data pool separately from the others and then taps into it as needed. In the second stage, one-way serial coordination from centralized IT through analytical units and out to the operating units allows companies to go beyond just assembling data to drawing inferences. In stage three, companies shift their focus from past relationships to future behavior. Through symbiotic coordination, information flows back and forth between central analytic units and various organizational units like marketing, sales, and operations, as together they seek answers to questions like "How can we prevent customers from switching to a competitor?" and "Who would be most likely to buy a new product in the future"? In stage four, firms begin to move past discrete, formal initiatives and, through integral coordination, bring an increasingly sophisticated understanding oftheir customers to bear in all day-to-day operations. Skipping stages denies organizations the sure foundation they need to build a lasting customer-focused mind-set. Those that recognize this will invest their customer relationship dollars much more wisely-and will see their customer-focusing efforts pay offon the bottom line.     

Silo busting: how to execute on the promise of customer focus

For many senior executives, shifting from selling products to selling solutions--packages of products and services--is a priority in today's increasingly commoditized markets. Companies, however, aren't always structured to make that shift. Knowledge and expertise often reside in silos, and many companies have trouble harnessing their resources across those boundaries in a way that customers value and are willing to pay for. Some companies--like GE Healthcare, Best Buy, and commercial real estate provider Jones Lang LaSalle (JLL)--have restructured themselves around customer needs to deliver true solutions. They did so by engaging in four sets of activities: COORDINATION: To deliver customer-focused solutions, three things must occur easily across boundaries: information sharing, division of labor, and decision making. Sometimes this involves replacing traditional silos with customer-focused ones, but more often it entails transcending existing boundaries. JLL has experimented with both approaches. COOPERATION: Customer-centric companies, such as Cisco Systems, develop metrics for customer satisfaction and incentives that reward customer-focused cooperation. Most also shake up the power structure so that people who are closest to customers have the authority to act on their behalf. CAPABILITY: Delivering customer-focused solutions requires some employees to be generalists instead of specialists. They need experience with more than one product or service, a deep knowledge of customer needs, and the ability to traverse internal boundaries. CONNECTION: By combining their offerings with those of a partner, companies can cut costs even as they create higher-value solutions, as Starbucks has found through its diverse partnerships. To stand out in a commoditized market, companies must understand what customers value. Ultimately, some customers may be better off purchasing products and services piecemeal.     

Modelling bank customer behaviour using feature engineering and classification techniques

This study investigates customer behaviour and activity in the banking sector and uses various feature transformation techniques to convert the behavioural data into different data structures. Feature selection is then performed to generate feature subsets from the transformed datasets. Several classification methods used in the literature are applied to the original and transformed feature subsets. The proposed combined knowledge mining model enable us to conduct a benchmark study on the prediction of bank customer behaviour. A real bank customer dataset, drawn from 24,000 active and inactive customers, is used for an experimental analysis, which sheds new light on the role of feature engineering in bank customer classification. This paper’s detailed systematic analysis of the modelling of bank customer behaviour can help banking institutions take the right steps to increase their customers’ activity.     

商业银行分客户的盈利评价模型研究

已有的分客户的盈利评价方法大多局限于计算分客户的会计利润,本文提出的商业银行分客户的EVA评价模型通过计量分客户的收入、分客户的成本以及分客户的经济资本成本,获得商业银行分客户盈利评价的EVA值.与以往的盈利评价方法相比,该模型考虑了对客户经营的风险因素以及资本成本,既可用于对客户的服务定价,也可用来确定各客户的EVA值,还可用来区分不同的客户类型,针对不同客户(群)实施差异化的经营策略,从而提高资源的配置效率,提升零售业务的市场竞争力.最后,文章指出该模型的实施需要商业银行具备较强的支撑平台.     

The customer knowledge journey

Customer relationship management (CRM) is the hot topic for many organisations at the moment. this could produce significant returns on investment and deliver the objective of a one-to-one relationship with customers, but it also puts a greater onus on companies to actually deliver their ‘brand promise’. For CRM to be sustainable it has to embed the learning from its relationships with customers within a clearly defined customer strategy and deliver tactics that fulfil that common goal of true CRM.     

‘Who owns the customer?’: A commentary on channel debate through the eyes of the customer

Amid intense changing competitive environments in the insurance industry, insurance manufacturers and intermediaries are preparing themselves to be closer than ever to their customers. But are they collaborating to serve the customer or are they still playing ‘tug of war’ over who owns the customer, while their customers seek greener pastures with the competition? In this paper the authors discuss six realities of customers and the insurance industry today and finish with suggestions on how collaboration between manufacturer and intermediaries will help serve the common interest of building stronger customer relationships.     

Corporate greed: its effect on customer satisfaction,corporate social responsibility and corporate reputation among bank customers

Corporate greed has received increasing attention in recent years with various stories hitting the headlines, particularly after the global financial crisis and the ensuing negative attitudes toward banks. Customer satisfaction and corporate social responsibility are known to have a positive effect on corporate reputation among customers, but perceived corporate greed is likely to impede their effect. Corporate greed, customer satisfaction, corporate social responsibility and corporate reputation are considered, and a research model is proposed. Results indicate that the effect of corporate greed is stronger on corporate social responsibility than on customer satisfaction, implying that corporate social responsibility activities may be futile if the company is perceived to be acting greedily by its customers. Thus, perceptions of corporate greed need to be dealt with swiftly, to enable management to enhance the corporate reputation of the firm.     

The customer experience ecosystem in two cultural contexts

This study focuses on the development of a customer experience ecosystem during a journey which is embedded in meso- and macro-layers. Using the critical incident technique, the author collected in-depth interview data from bank customers in Switzerland and Iran to empirically study this ecosystem, including customer–company interaction in the micro-layer and social context of the meso-layer. Moreover, in a macro-layer analysis, the Hofstede cultural dimension was employed to show the role of cultural context in this ecosystem. The findings indicate that customer experience in the pre-encounter stage is mostly shaped by customer past experience and social context rather than company touchpoint. The importance of these factors is different in the two cultural contexts. Although customer experience in the encounter stage is mainly the result of customer and company interactions, other people have a role in this stage and cultural differences between the two countries largely explain these differences. Moreover, in the post-encounter stage, customers in different cultural contexts use various factors to evaluate their experiences and the effects on their emotional and behavioral responses. The findings provide key managerial implications for national and international companies with respect to the role of multiple layers in customer experience management.     

Let us work together: The impact of customer strategic alliances on IPO underpricing and post-IPO performance

Leveraging the availability of three years of pre-IPO data and related vs unrelated-party customer information for Chinese firms, we examine the impact of customer strategic alliances (CSA) on IPO underpricing from 2007 to 2015. Our core findings suggest that IPO firms with CSAs have less IPO underpricing than those without such a relationship. The decrease in underpricing is more salient for IPO firms that have non-related-party customers. Additional analysis suggests that the core findings are primarily driven by firms with good information environment pre-IPO, including high audit quality, high analyst following, and low earnings management. We interpret the results as indicating that a good pre-IPO information environment enhances the credibility of CSA relationships and signals high IPO quality. Furthermore, we document that a CSA relationship has a positive impact on an IPO firm's post-IPO performance, especially when the firm has non-related-party customers. Overall, CSAs reduce IPO underpricing and enhance IPO returns post-IPO.     

Determinants of customer loyalty and share of wallet in retail banking

Previous research has investigated the determinants and consequences of customer loyalty, but, in banking, a critical measure largely neglected in previous studies is the customer's ‘share of wallet’. This study, based on a survey of 1,924 retail banking customers, suggests that a large proportion of the variance in stated behavioural intentions can be predicted, in particular, by customers' attitude measures. More importantly, the study shows that a substantial amount of the variance in share of wallet can be predicted, allowing banks to identify and focus on customer segments where there is most potential for growth. In recognition of the fact that dissatisfied customers are a distinct segment, the study models actual behaviour in terms of share of wallet for dissatisfied customers. Implications for research and for business are discussed.     

Investment guarantees in unit-linked life insurance from the customer perspective

Interest rate guarantees are a typical contract feature in unit-linked-life insurance products. As the financial crisis of 2007/2008 has shown, these guarantees can be of substantial value for policyholders since they ensure that at least a minimum amount will be paid back even if the mutual fund value falls below a specific guaranteed level. However, from the insurance company’s view, these guarantees can be costly—especially in highly volatile markets—due to the required risk management measures which must be undertaken to secure the guarantees promised to the customers. Thus, the aim of this paper is to investigate whether customers really value these guarantees and if their willingness to pay (WTP) is sufficient to cover the guarantee costs. To elicit customer WTP, we use an online questionnaire and compare these results to the actual guarantee costs calculated with the Black and Scholes option pricing formula. One main finding is that even though most of the participants in the online questionnaire work in the financial industry, subjective prices are difficult to derive and are lower, on average, than the prices obtained using a financial pricing model. However, many participants are still willing to pay a substantially higher price.     

How does customer motivational orientation affect satisfaction?

This study examines the link between customer motivational orientation and customer satisfaction in the Chinese context. The customer motivational orientation–satisfaction model was tested on 349 Chinese bank customers in Macao, China. Results of structural equation modelling indicated that task-oriented and interaction-oriented customers were not equally responsive to the financial services provided. Specifically, task motivational orientation was directly and indirectly related to customer satisfaction through customer perceived service quality, whereas interaction motivational orientation only linked to customer satisfaction through customer perceived service quality as a mediator. The theoretical and practical implications of the findings are discussed.     

Modelling and predicting customer churn from an insurance company

Within a company's customer relationship management strategy, finding the customers most likely to leave is a central aspect. We present a dynamic modelling approach for predicting individual customers’ risk of leaving an insurance company. A logistic longitudinal regression model that incorporates time-dynamic explanatory variables and interactions is fitted to the data. As an intermediate step in the modelling procedure, we apply generalised additive models to identify non-linear relationships between the logit and the explanatory variables. Both out-of-sample and out-of-time prediction indicate that the model performs well in terms of identifying customers likely to leave the company each month. Our approach is general and may be applied to other industries as well.     

Turn customer input into innovation

It's difficult to find a company these days that doesn't strive to be customer-driven. Too bad, then, that most companies go about the process of listening to customers all wrong--so wrong, in fact, that they undermine innovation and, ultimately, the bottom line. What usually happens is this: Companies ask their customers what they want. Customers offer solutions in the form of products or services. Companies then deliver these tangibles, and customers just don't buy. The reason is simple--customers aren't expert or informed enough to come up with solutions. That's what your R&D team is for. Rather, customers should be asked only for outcomes--what they want a new product or service to do for them. The form the solutions take should be up to you, and you alone. Using Cordis Corporation as an example, this article describes, in fine detail, a series of effective steps for capturing, analyzing, and utilizing customer input. First come indepth interviews, in which a moderator works with customers to deconstruct a process or activity in order to unearth "desired outcomes." Addressing participants' comments one at a time, the moderator rephrases them to be both unambiguous and measurable. Once the interviews are complete, researchers then compile a comprehensive list of outcomes that participants rank in order of importance and degree to which they are satisfied by existing products. Finally, using a simple mathematical formula called the "opportunity calculation," researchers can learn the relative attractiveness of key opportunity areas. These data can be used to uncover opportunities for product development, to properly segment markets, and to conduct competitive analysis.