Vulnerabilities that Drive Customer Defection - Literature review Example

Vulnerabilities That Drive Customer Defection and Development of Temporal Models to Predict Customer Defection Introduction Evidence has shown that customers who seem to be contented with the service provider most often than not end up defecting. The service provider cannot be at peace with existing number of customers that he has because he cannot foresee how many are likely to defect. Customer defection is an initiated action by the customer to terminate a service or using certain goods for a given company or service provider. Relationship attrition refers to the population of clients who terminate their relationship every month (Anderson & Simester, 2004). This is shown as a fraction or a percentage of the total customers that were present at the beginning of every month. Customer defection brings forth the importance of understanding customer loyalty. Companies that are focused solely on the product and not the customer and the market are likely to face high rates of attrition or customer defection. Majority of these companies do not follow up to analyze the reasons for customer defection. Many business enterprises recognize the importance of customer loyalty and do everything within their means to ensure that they retain a customer and attract others. This paper looks at vulnerabilities which bring about defection of customers and also discuss some of the models that are available for predicting customer defection. MacAlexander, Schouten & Koening (2002) concur that the value of customer loyalty surpasses the essence of allocating a colossal budget to the marketing and sales department. It costs less to retain a customer than try to attract a new relationship with another customer. Some businesses focus more in stock prices and profitability as compared to customer loyalty and satisfaction. Business enterprises that use their operations in creation of value to customer have a great chance of becoming market leaders. Lexus came up with a model that shows how much a business can gain through customer loyalty. Lexus acknowledged the essence of customer retention. The model trained and empowered employees to provide complete satisfaction to customers (Verhoef, 2003). Firms that do not focus on customer value and do not invest in preventing defection of customers are bound to lose close to half of their customers in a period of five years. If those companies do not go back and evaluate the reason of customer satisfaction, they lose market share due to competitions and profit margins. Creation of customer value is a crucial initiative towards prevention of customer defection. Lehmann, Gupta and Stuart (2004) acknowledge that getting to know the reasons that cause customer defection is one step towards prevention of customer defection. The concept of customer defection and customer are inversely related in the meaning; the higher the value of customer, the lower the rate of customer defection. Companies have to learn from their customers if they have to understand customer defection. Over the years it has been established that customer satisfaction is one of the fundamental concepts in marketing as expressed by Verhoef (2003). Academic research has extensively studied the importance of customer satisfaction through analyzing of different issues such as measurement and conceptualization of satisfaction constructs, influence of customer satisfaction in regard to retention of customer, customer profitability and satisfaction, value’s role in satisfaction of customer, loyalty and customer satisfaction among others (Gupta, Lehman & Stuart, 2004). The need to keep customers satisfied has increased firms focus on relationship marketing as observed by many scholars and practitioners in the field of business. Relationship marketing is the maintenance and establishment of long period of seller-buyer relationship has immensely changed marketing practice and theory. Relationship marketing has been viewed by scholars as a paradigm shift. Management teams are looking for ways of doing it in better ways. Whereas theoretically relationship marketing has been seen to be perfect, in practice it is not easy to sustain it. Companies have to work very hard to ensure that they retain customers and attract more to boost their market share. An effective way of ensuring that the company does not suffer and steadily grows is safeguarding revenue through retention of the current customers (Thomas, 2001). This objective can be attained in many ways but moves that are unplanned can be accompanied with risks. Price-cutting can be retrogressive move in a setting where uncertainty and fear are supported a strong attachment to quality. The strategy can lead to dwindling sales since the customers value quality goods regardless of the price. It is wise to understand the environment within which the business is operating. It is cheaper to keep the existing customers that trying to win new ones. Promotional and marketing activities are very expensive in a market that is competitive. The existing customers are a guarantee for growth in revenues which is cost-effective and reliable. A business enterprise has to understand the reason that makes the customer to leave or defect. The rate of customer attrition has been growing steadily. MacAlexander, Schouten & Koening (2002) disputes the assumption that customer attrition is attributed to price dynamics. Customers defect as a result of shifting in status quo. Service providers who ensure that their customers are satisfied make their existing customers to be loyalty and not tempted to seek for alternatives in the market. It is when the status quo is changed owing to changes in the environment, company’s offering, or the needs of the customer that customers look for alternatives. During this time, customers are exposed to risk and can leave any time. Customer retention has an important impact on the profitability of the firm. Lehmann, Gupta and Stuart (2004) established that one percent improvement in retention can lead to improvement of the value of the firm by 5%. Churn refers to tendency of customers to defect or stop business with a given firm. Marketers who want to increase lifetime value appreciate that customer retention is key in the determination of factors of customer defection (churn) and can be in a position of predicting those customers who can defect at a later date. An understanding of customer defection drivers can assist companies in the designing of customer relationship strategies and other interventions geared towards increasing loyalty of customers and prolonging their lifetime with the company (Rokkan, Heide & Wathne, 2003). Given the significance of retention, firms apply a range of mechanism for reducing customer defection. The efforts include: improving quality of service, loyalty programs, and using interventions to prevent defection. The investment of the firm in the improvement of the quality of service and customer satisfaction is based on the assumption that they boost retention of customers. Some studies have cited the link between retention and satisfaction while others have opposed this finding. Scholars agree that rates of retention have been found to be affected by the channel (s) used by customers. A study showed that e-mails make people to visit the internet; and purchases done over the internet reduce inertia in loyalty and buying. They conjecture that comes up from lower service levels and lower costs of switching find the opposite effect in the setting of purchases of grocery owing to the utilization of e-shopping lists which are able to bring up switching costs. In the wake findings that are conflicting, it is better to determine the role of the optimal channel of mix retention. Following the introduction of regular flier program by American Airlines in the 1980, loyalty schemes or programs have become widely spread in many industries. The focus on loyalty schemes has increased as many companies to seek to develop relationships with their clients, retaining customers, and stimulating service or product usage (Flint, Woodruff & Gardial, 2002). Despite the popularity of loyalty programs their effectiveness has not been clearly identified as stated by many scholars. However, some studies have established that loyalty programs increase customer development and customer retention. The essence of controlling the rate of customer attrition is very important since the strategic and financial costs associated with outcome that is undesirable. In many cases companies lose an average of ten percent of their customers which is a very big number. Gaining a new customer can cost five times more as compared to retaining and satisfying an a relationship that is existing. It is less expensive to cross-sell and up-sell to customers who exist than pursuing new and untested prospect (Jap & Shankar, 2000). The significance of retained customers transcends the high costs of replacement; they spend more; they shop more often, purchase products in high quantities and refer buyers to the service or product provider. In regard to referrals, the customers act as ambassadors is a cost-effective and powerful avenue of marketing. Loyal customers are knowledgeable and proactive concerning brand relationships on the brand relationships. It cost less to drive and support high margins of contribution. Most of these benefits go down the drain when a customer leave or terminate his or her association with the company. Securing and nurturing a commensurate replacement for the customers who leave. Quantification of customer value is a difficult exercise since statistics differ from one industry to another, service, or product or geographic setting (De Wulf, Gaby & Dawn, 2001). Research has shows that five percent defection in rate of customer defection can boost profitability by 25 to 125 percent. 2% increase in the rate of customer retention has an effect on the profitability of the company as there is a subsequent reduction in the costs. In a setting where there is an urgency to maximize both cost efficiency and revenue, the important of retention of customers seem to be poignant (Kivetz, 2003). Customer retention is becoming a pressing issue in the competitive world today. When the customer is maintained in the company for a long period the company generates more profits. Customer defection has increasingly become important to businesses and has been at the center stage of various studies (Mittal & Kamakura, 2001). However its social aspects have not been widely explored. This demonstrates the gaps that exist in the current literature. There are many reasons that are attributed to customer defection. Customer can be lost through consideration of price. While it may appear important to attract new clients, it can seem to be a minor practice of trying to develop loyalty schemes that can help in retention of customers. Price accounts to close to fifteen percent why customers defect (Bolton, 2008). Secondly, customers can also defect due to physical factor. Physical factors may consist of things like convenient location of the business or competitor invention or action. Competitor activity and marketing account for about 15% of the reason for defection. Customers can change product or service provider due to the inattention or the indifference displayed by the former as far as the needs of the customers are concerned. Customer sophistication is also another factor that contributes to defection. Changing social needs have complicated the manner in which customers choose their product or service providers. Bowman & Das (2001) expostulate that the complexity of buying decision making makes it hard for product and service providers to predict the next move of the customers in their purchase decisions. The level of competition has increased in all industries. Advancement in technology and globalization make customers to seek or demand for better quality of goods and services. Having a customer profitability analysis can result into development of a relationship that is profitable (Bowman & Das, 2001). Successful customer retention commences with a customer-centric plan. Firms have to create and implement means of measuring their existing customers effectively and continuously. This involves studying customer attributes such as history, loyalty, and purchasing power. These actions bring about valuable business intelligence which can be applied in influencing marketing and operational levers which are available to the company for influencing customer perception and behavior (Parasuraman & Grewal, 2000). The coming of rewards or loyalty schemes has yielded positive results as far as customer attachment to the company is concerned. This is a way of promoting repeat purchase behavior and projecting an image that is customer-centric. These positive trends have high contribution to the growth in margins. Expansion of marketing budget is another way that programs that are customer oriented are developed. Many companies embrace the idea of outsourcing office marketing tasks to carry out these significant but not core functions cost-effectively and successfully (Bolton, Kanna & Bramlett, 2000). In the perspective of contemporary marketing, customer loyalty has been intricately connected to satisfaction and trust. These are constructs which have a long time been featured in tradition research. Practitioners and constructs have passionately used the construct of customer satisfaction for quite a long time with the objective that understanding and measuring customer satisfaction will assist in predicting the behavior of customers as well as give a hint on the aspect of retention of customers. Relationship marketing theory holds that trust is a key antecedent to relational outcomes that are positive (Rust & Zahorik, 2003). Literature concerning marketing of services put forward several factors which affect satisfaction. The factors can be grouped into two groups: (a) factors external to the client such as competitors, service providers, and attributes of services and (b) factors internal to the client like mood and values of the client. The first groups of factors that influence customer satisfaction are external to the client. Contemporary marketing literature is full of such factors. In the banking sector, the quality of the services provided affect to a large extent the level of customer satisfaction. Judgment of customers in regard to the delivered service reliability and the experiences of customers with the process of service delivery have an influence in the banking services’ satisfaction (Reinartz & Kumar, 2000). Research literature has regarded trust as a key factor influencing the level of satisfaction between producers and consumer via the distribution channels. Customer satisfaction can be increased through provision of special treatment to the customers by the service provider. Social benefits have been known to influence satisfaction even though benefits to focus more on relationships as compared to results. Customer satisfaction serves as the main element in decisions of customer defection. Researchers explored satisfaction as a single time in time or studied as a measure which evolves over time, and have looked at satisfaction either on the basis of self-reports of customers or through conducting inferences from the behavior of the customer (Franses, 2005). Customer tenure with the company has been established to affect negatively intention to defect and further encourage the positive effect of satisfaction concerning retention of customer. Personal characteristics like customers’ age and gender have been found to significantly affect defection decisions of customers in a range of industries like the auto industry, communication services, and financial services. Absence of research concerning social influence as a driver of defection is evident. Social influence comes from the transmission of a range of information among individuals who are connected to each other (Reinartz & Kumar, 2003). This kind of transmission can happen through numerous interactions that an individual has with other people in the social circle. A person may get information concerning a product through behavioral learning. He sees other people with the product or using the product. He can also to other people concerning the product, or gets information from third parties concerning another person who uses the product. Social influence happens via transmission of information which results into reduction of search effort and uncertainty (Donkers, Frenses & Verhoef, 2003). Social influence can also happen through social and normative pressure, or a result of externalities in the network. It not is clear whether the degree of social influence on defection of customers is same as that on adoption (David, 2004). As opposed to adopters, prospective defectors have knowledge concerning their personal knowledge on brand and may not need information from others. Defections are propelled by or associated with negative information or word of mouth that leads to further defection. Negative publicity has further much consequences that positive publicity. The other group of factors influencing customer satisfaction is founded on the well-known conceptualization model called Oliver’s expectancy disconfirmation. Satisfaction on the other hand, influences purchase intention and change in attitude. In this perspective, customers form expectations that act as a standard against which performance of service is judged. A comparison of perceptions and expectations will occasion either disconfirmation or confirmation. Expectations of customers are confirmed in the case where service or product perceptions precisely meet expectation (Bougie, Pieters & Zeelenberg, 2003). Disconfirmation is the difference between perceptions and expectations, and it falls into two categories. The first category is known as positive disconfirmation and happens when the performance of the product is far above the prior expectations. The second category is known as negative disconfirmation whereby expectations are more than performance. Positive disconfirmation and confirmation will result into satisfaction. On the other hand negative disconfirmation occasions dissatisfaction. Satisfaction is perceived as aggregate impression of collective events or a single occurrence (Sirdeshmukh & Sabol, 2002). In the perspective of Oliver, this is an important aspect for service providers. In the same regard the personal attributes of consumers like mood and values has an influence on the satisfaction of the customer to a great extent. In the course of the service experience, mood is very different from the satisfaction’s affective component since it influences the process of service delivery rather than the outcome of the service experience (Day, 2000). This does not demonstrate that satisfaction and mood in the course of service experience are totally independent. On the other hand, satisfaction and mood have to be considered as distinct in a conceptual manner as opposed to constructs that are overlapping. When the expectations of the customers are not met in regard to price, service quality, and product quality, a company will attain a high degree of customer satisfaction (Bendapudi, 2007). Customer delight results from satisfaction. When the customer expectations are not met, dissatisfaction is likely to occur. Low levels of satisfactions can make customers from buying goods from a specific product or service provider. Studies have indicated that high rates of customer retention and high levels of customer satisfaction are strongly related to corporate profitability and one another. Gaps in literature exist in regard social effects leading to defection, methods of forecasting defection, the value of long term relationship with clients, and methods of determining the rate of defection. Nevertheless, the limitations in current literature provide room for further research to be conducted, and thereby understanding deeper the impact customer defection and retention on the business. Temporal models to predict customer defection Many aspects concerning defection have been modeled in a variety of literature. Regardless of defection being observable or hidden, it influences the approach to modeling. In certain circumstances defection of customers is not observed directly since customers do not openly terminate their relationship with the company but can become docile or inactive. In other cases, nevertheless, the decision to defect is seen since the customers stop their relationship by putting an end to receiving a product or a service from a certain provider (Steenburg, Ainsle & Engbretson, 2003). The modeling approach will depend on the significance placed on the interpretation or explanation against the prediction. It has been noted that models that provide excellent explanations may not work the same in case of prediction. Available empirical literature in marketing has favored traditionally parametric models which are easy when it comes to interpretation. Such parametric models include: probit or logistic regression, zero-inflated poisson models, or parametric hazard specifications. Defection is a rare action that may need new approaches from machine learning, data mining, and non-parametric statistics that focus on the ability to predict. Such models include jump diffusion models, projection-pursuit models, tree structured models, neutral network models, spline-based models like Multivariate Adaptive Regression Spline and Generalized Additive Models (GAM), and other current approaches like boosting and support vector machines. There is need for more work in understanding the relative disadvantages and advantages of the various approaches mentioned above in customer relationship applications. The current literature falls short of providing explanation on the disadvantages and advantages of these approaches. Some insight has been given by Nelson et al (2004) in regard to performance of various approaches concerning predictive modeling basing on the Teradata tournament for modeling defections. Room for research is available for modification of flexible semi-parametric models in handling marketing data unique facets. For instance one can use semi-parametric models in handling sources heterogeneity that is unobserved in longitudinal-data settings comprising of multiple customers’ records (Bolton, Lemon & Verhoef, 2004). Further research also is required in the case of dealing with a huge number of variables that are explanatory and for modification of various models in handling rare-event data. Extensive literature on management of variables does not exist and consequently making it challenging for marketers to explore different models. Advancement in information technology has enabled companies to collect as huge amount of information concerning customer transaction. This gives firms the opportunity to apply data on revealed preferences as opposed to intentions. Besides, there is no need for sampling when the customer base is readily available. Modeling sophistication has given marketers an opportunity of converting the data available into valuable insights (Ansari & Mela, 2003). Available technology necessitates leveraging of the insights and customizing programs for specific customers. Understanding customer lifetime value highlights the importance of predicting customer defection. In this perspective, the company can use the available information to know whether to change the approach of maintaining and attracting customers. The models that have been discussed can be classified as modeling techniques in computer science. While Gupta, Lehman, and Stuart (2004) applied data from 5 firms to demonstrate that customer lifetime value may offer a good proxy for the value firm, Kumar (2006) demonstrated that customer lifetime value is closely related with the value of the firm applying longitudinal analysis of the data of the firm. The modeling approaches do not consider competition due to absence of competitive data. Updating customer lifetime value is controlled by the dynamics in particular market (Weinstein, 2002). Prediction of defection is not an easy process and needs the application of models that have been previously mentioned in this paper. In spite of this, many of the methods need further modifications or adjustments in order to deal with the measurable variable that is being investigated. The problem is compounded by the fact that some cases of defection are not easily noticeable. Conclusion Customer defection can affect a firm negatively since it reduced the customer base and number of repeat purchases. Customers who have a relationship with a company are bound to shop friendly and in large quantities. Being able to predict the behavior of customers in future gives an opportunity for the companies strategize on how to deal with upcoming events. Companies have to look for ways of dealing with the loss of customers and improve methods of attracting customers. Various models have been developed with the aim of predicting future customers’ behavior that may lead to defection. 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