Industrial Management & Data Systems Emerald Article: Gaining customer knowledge through analytical CRM Mark Xu, John Walton

Transcription

1 Industrial Management & Data Systems Emerald Article: Gaining customer knowledge through analytical CRM Mark Xu, John Walton Article information: To cite this document: Mark Xu, John Walton, (2005),"Gaining customer knowledge through analytical CRM", Industrial Management & Data Systems, Vol. 105 Iss: Permanent link to this document: htt://dx.doi.org/ / Downloaded on: References: This document contains references to 48 other documents Citations: This document has been cited by 5 other documents To coy this document: [email protected] This document has been downloaded times. Access to this document was granted through an Emerald subscrition rovided by OHIO STATE UNIVERSITY For Authors: If you would like to write for this, or any other Emerald ublication, then lease use our Emerald for Authors service. Information about how to choose which ublication to write for and submission guidelines are available for all. Additional hel for authors is available for Emerald subscribers. Please visit for more information. About Emerald With over forty years' exerience, Emerald Grou Publishing is a leading indeendent ublisher of global research with imact in business, society, ublic olicy and education. In total, Emerald ublishes over 275 journals and more than 130 book series, as well as an extensive range of online roducts and services. Emerald is both COUNTER 3 and TRANSFER comliant. The organization is a artner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive reservation. *Related content and download information correct at time of download.

2 The Emerald Research Register for this journal is available at The current issue and full text archive of this journal is available at Gaining customer knowledge through analytical CRM Mark Xu and John Walton Deartment of Strategy & Business Systems, Portsmouth Business School, University of Portsmouth, Portsmouth, UK Gaining customer knowledge 955 Abstract Purose This aer aims to examine how customer relationshi management (CRM) systems are imlemented in ractice with a focus on the strategic alication, i.e. how analytical CRM systems are used to suort customer knowledge acquisition and how such a system can be develoed. Design/methodology/aroach The current ractice of CRM alication is based on examining data reorted from a four-year survey of CRM alications in the UK and an evaluation of CRM analytical functions rovided by 20 leading software vendors. A concetual model of an analytical CRM system for customer knowledge acquisition is develoed based on the findings and literature review. Findings Current CRM systems are dominated by oerational alications such as call centres. The alication of analytical CRM has been low, and the rovision of these systems is limited to a few leading software vendors. Practical imlications The findings shed light on the otential area in which organisations can strategically use CRM systems. It also rovides guidance for the IT industry as to how an analytical CRM system should be develoed to suort customer knowledge acquisition. Originality/value The latest findings on CRM systems alication are reorted, and an innovative analytical CRM system is roosed for customer knowledge acquisition. Keywords Customer relations, Information systems, Knowledge management, Customer information, Customer retention, United Kingdom Paer tye Research aer Introduction Customer relationshi management (CRM) has been widely regarded as a comany activity related to develoing and retaining customers through increased satisfaction and loyalty. IT-based CRM systems have been alied in many industry sectors, and research on advancing these systems is continuing (Kotorov, 2002; Rowley, 2002; Xu et al., 2002; Bose, 2002; Choy et al., 2003; Ferguson et al., 2004; Sweet, 2004). One aroach to address future CRM systems develoment is to link knowledge management (KM) and CRM in order to maximize not only oerational, but strategic efficiency of CRM through gaining and sharing knowledge about customers (Cambell, 2003; Rowley, 2004; Minna and Aino, 2005). Rowley (2004) argues that there is a need to develo an understanding of the interaction and interface between KM and relationshi marketing (RM), and to oerationalise this in the arallel contexts of systems, eole and rocesses. The key KM rocess includes knowledge creation, sharing, dissemination and exloitation, and the RM rocess includes communication, creation of loyalty and stable customer base, customer service, trust cultivation and relationshi maintenance. Rowley (2004) suggests that from a ractical ersective, customer data or information can be used as a latform for both relationshis and knowledge. Tzokas and Saren (2002) recognised some convergence of knowledge and Industrial Management & Data Systems Vol. 105 No. 7, q Emerald Grou Publishing Limited DOI /

3 IMDS 105,7 956 relationshi marketing and cometitive advantages, and develoed a concetualisation of the dynamics of the two significant management aradigms. Minna and Aino (2005) conclude that there is an evident need in the marketing disciline to further elaborate on the concets of customer knowledge and customer knowledge management. Knowledge is the only meaningful economic resource (Drucker, 1996), and gaining this knowledge is becoming an imortant differentiator for cometitive advantage (Paiva et al., 2002; Tzokas and Saren, 2002). In the context of studying manufacturing comanies, Paiva et al. (2002) found that customers information is the tye of information that is most frequently udated, and the comany focuses on secific customer information instead of general market information. Bose (2002) argues that to gain cometitive advantage, there needs to be a shift from mass marketing and traditional customer segmentation towards customer-centric orientation and one-to-one marketing, which is centred on treating every customer individually and uniquely, according to the customer s reference. Ahn et al. (2003) acknowledges that managing relationshis with customers is a key oint to solidify cometitive ower of a comany. However, effective use of customer information and knowledge, articularly in the context of marketing decisions, is still inchoate in many organisations (Bose and Sugumaran, 2003). The customer is a strategic element in a comany s downstream suly chain. It relates to the immediate business environment that a comany needs to scan for strategic information (Xu et al., 2003). The customer, according to Daft et al. s (1988) environment sector classification, is in the layer closest to the organisation s task environment that has direct transaction with an organisation. Changes in the tye of customers, behaviour and atterns of customers are likely to have immediate effect on the oerations of a comany and also have imlications for decision making relating to strategy setting in the future. It is recognised that not every customer is equally imortant to an organisation in terms of his/her lifetime value, thus, customers need to be segmented in order to identify strategically imortant customers. Imortant factors for imroving customer service are to identify the reasons why customers defect and also ways of reventing customer defections. This requires information about customers references and behaviour atterns. However, very few studies have been established to address customer knowledge acquisition in the context of CRM imlementation. Although a range of CRM technologies, articularly CRM software, are witnessed being develoed and imlemented in ractice (Luck and Lancaster, 2003; Feinberg et al., 2002; Ferguson et al., 2004), there is little research addressing to what extent CRM has been imlemented to rovide strategic customer information i.e. to gain customer knowledge. Research on how to incororate analytical functions into oerational CRM has been limited (Xu et al., 2002; Bose, 2002), and the concetualisation of such systems tends to be general and vague. As suggested by Ahn et al. (2003) the main concern in CRM systems is to understand and make ractical use of customer information, and argue that with an enormous amount of data stored in databases and data warehouses, it is increasingly imortant to develo owerful tools for the analysis of such data and mining interesting knowledge from it. This study aims to examine the imlementation of CRM systems in ractice with a focus on its strategic alication, i.e. to gain customer knowledge, and to exlore the

4 ways of embracing CRM technology for strategic customer information rovision. The significance of this investigation is to exlore the otential of CRM systems and the ways that organisations can better use the system to unlock the wealth of customer information and deliver it, enterrise wide, to both internal and external users. Gaining customer knowledge Literature review CRM is a rocess designed to collect data related to customers, to gras features of customers, and to aly those qualities in secific marketing activities (Swift, 2001). Choy et al. (2003) suggests that CRM is an information industry term for methodologies, software, and usually internet caabilities that hel an enterrise manage customer relationshis in an organised way. It focuses on leveraging and exloiting interactions with the customer to maximise customer satisfaction, ensure return business, and ultimately enhance customer rofitability. In ractice, however, managers often erceive CRM from different ersectives, for examle, CRM is a art of marketing efforts, customer service, articular software and technology, or even rocess and strategy. Luck and Lancaster (2003) suggest that the term CRM has become a buzzword, with the concet being used to reflect a number of different ersectives. In this aer, the term CRM system is used to reflect comuter-based systems that suort CRM. 957 Customer knowledge Rowley (2002) defines customer knowledge as:. knowledge about customers, which includes knowledge about otential customers, customer segments and individual customers; and. knowledge ossessed by customers. Minna and Aino (2005) differentiate customer knowledge from customer data and customer information, and suggest that customer knowledge can be exlicit, the structured customer information in databases, or in tacit customer knowledge knowledge in mind of emloyees and customers. In this aer, the term customer knowledge means knowledge about customers. There is no doubt about the imortance of gaining customer knowledge. For instance, Zineldin (2000) suggests that IT tools should be used not only to rovide relationshi building credibility and oortunities but also to enable marketers to kee their fingers on the customer s ulse and resond to changing needs. This is emhasised by Roscoe (2003), who argues that marketers must embrace customer knowledge management (CKM) to really get under the skin of consumers and deliver a rofitable relationshi. CKM needs to rovide customer insight, rofiles, habits, contact references and understanding to imrove an organisation s contact with the customer. It can be argued that knowledge gained on customers will enable organisations to make intelligent decisions as to which customer to acquire and develo, what channels to use when contacting the customer, what roducts/services to sell, acquire and develo, and how to get the business to deliver excellence using the CRM strategy. The strategic imortance of gaining customer knowledge has been erceived by many managers, as stated by Shaw and Ivens (2002) that 71 er cent of senior business leaders say that customer exerience is the new cometitive battleground and is a source of sustainable differentiation.

5 IMDS 105,7 958 Review of develoing analytical CRM systems Enhancing the analytical ower of CRM systems has been recognised by researchers. For examle, Rowley (2004) suggests that CRM systems include online order, and knowledge bases that can be used to generate customer rofiles, and to ersonalise service. Xu et al. (2002) state that CRM technologies allow the organisation to gain an insight into the behaviour of individual customers and, in turn to target and customise marketing communication and messages. In addition, these tools generate data that suort the calculation of customer lifetime value for individual customers. The studies, however, do not secify the key comonents of the system, nor how such a system can be develoed. Bose (2002) outlines a CRM develoment lan based on the tyical system develoment life-cycle aroach, in which he suggests that CRM involves acquisition, analysis and use of knowledge about customers in order to sell more goods or services and to do it more efficiently. Develoing such a system builds on an enterrise-wide integration of technologies working together such as data warehouse, web site, intranet/extranet, hone suort systems, accounting, sales, marketing and roduction. The analytical function may be fulfilled by searate systems, such as decision suort systems and exert systems. This aroach is vague on how customer knowledge might be created, because it is not clear as to what technology in ractice actually turns customer data into knowledge. A similar aroach is suggested by Lee and Hong (2002) to create an organisation-wide KM infrastructure. In the model, database, data warehouse, digital library, data mining and online analytical rocess (OLAP) are suggested as being the tools to cature and develo knowledge. The model, however, is general to organisational KM rather than secific to customer knowledge creation. Ahn et al. (2003) rooses that data mining/analysis tools and a knowledge base should be the function of a CRM system, but did not go further to illustrate how such a system can be develoed. Although how to develo an analytical CRM is far from clear, some exlorative research may benefit develoing such a system. For examle, Choy et al. (2003) reorts to use case-based reasoning to evaluate and select suliers in order to fulfil the requirements of the key customers so as to retain a good relationshi. Bose (2002) based on Wells et al. s (1999) argument to suggest that exanding customer data needs to include non-transactional information, which is equally, if not more, valuable than the transactional data. Such data may include general inquiries, suort calls, suggestions, emloyee/management comments, registration cards and comlaints. CRM systems alication in ractice The imlementation of CRM systems has been widely reorted by both CRM software vendors and academic researchers. The oular CRM systems aear to be: call centre, contact management, data warehousing, ortals, workflow and business rocess management for the uroses of retaining existing customers and develoing new customers. Xu et al. (2002) suggest that contact centres have been laying a major role within the CRM icture. Taylor and Hunter (2002) reort that the Euroean customer suort and service market is still largely focused on call centres, articularly in the UK. Very few ractitioners are making otimum use of their client database, because they are failing to udate, quantify and qualify the information collated about the clients (Dyer, 1998). A few reorts even suggest that CRM systems fail to have the

6 transformational imact widely romised by the software industry and exected by the business community. For examle, Harvey (2001) cited Gartner s reort by saying that 65 er cent of CRM imlementations result in failure. Most CRM systems are used to imrove customer-facing oerations. Rowley (2002) argues in line with Harvey that 80 er cent of CRM imlementations fail, and academics exress sceticism about the viability of interreting customer data in such a way that it generates useful insights into customer and user behaviour. Bolton (2004) consents with these arguments by stating that many of the early CRM imlementations seem to have failed. Sweet (2001, 2002, 2003, 2004) reorted four survey results related to CRM alications in UK comanies. The surveys were conducted by PMP Research from 2001 to A range of CRM-related issues are investigated including the success level of CRM, reasons for imlementing CRM alications, degree of customising CRM solutions, current sending and future investment in CRM, degree of using analytical tools, and the ercetion of gaining cometitive advantage from CRM. The following is a revisit of the data that is relevant to this study. Reasons for imlementing CRM. The motivating factors for comanies moving towards CRM technology are resented in Table I. The data shows that major considerations for comanies in using CRM is to imrove customer satisfaction level, to retain existing customers and to imrove customer lifetime value. Providing strategic information from the CRM systems aears less imortant than imroving satisfaction level and customer lifetime value. Using CRM systems to attract new customers has been erceived less imortant in the four surveys. This shows that most managers accet the view that gaining a new customer is more costly than retaining an existing customer. Several authors highlight the strategic advantage of maintaining the customer base as oosed to merely attracting new customers (Luck and Lancaster, 2003; Rowley, 2004). For examle, Kandamully and Duddy (1999) quote that it costs five times more to attract a new customer than it does to kee an existing one. Zineldin (1999) argues that getting customers is imortant, but keeing and satisfying them is more imortant. Customer retention is less costly and, therefore, more rofitable than customer attraction. Retention also contributes to the creation of reutation, which in turn further lowers customer acquisition costs. Managers no longer see CRM as a quick way to bring new customers on board. Using CRM for cost reduction is ranked the last in the four-year survey. This suggests that most managers do not erceive CRM systems as simly a means of Gaining customer knowledge 959 Mean Reasons for imlementing CRM Imroving customer satisfaction level Retaining existing customers Imroving customer lifetime value Providing better strategic information to sales, marketing, finance, etc Attracting new customers Cost savings Notes: 1 not imortant; 5 very imortant Table I. Reasons for imlementing CRM

7 IMDS 105,7 960 reducing the costs of customer service. Sweet (2003) reorts that secialist software suorting CRM oeration such as contact management systems are erceived as imortant by 66 er cent of the resondents, 52 er cent of the resondents regard the call centre as imortant. The ercentages are significantly higher than that of the analytical CRM systems. Revisiting the data suggests that many CRM systems imlemented are aimed at imroving oerational asects of CRM. The oerational efficiency in dealing with customer enquiries could result in imroved customer satisfaction level and customer loyalty. However, gaining customer knowledge from CRM systems and roviding strategically imortant customer information to other deartments are not erceived as imortant as imroving oerational efficiency. The extent of using analytical CRM. Analytical CRM systems incororate tools that can rocess the sheer volume of customer data to suort strategic customer information rovision and customer knowledge acquisition. Sweet (2001, 2002, 2003, 2004) reveals that the alication of analytical CRM in the UK comanies has been low. Figure 1 shows the alication level of using analytical CRM. As shown by the chart, only a quarter of the UK comanies use analytical CRM, although there is an increase in 2003 (38 er cent). The data suorts our contention that CRM systems are mainly used for oerational activities e.g. contact management, call centre, workflow, and multile touch oints. There is a lack of focus on gaining customer knowledge for strategic decision making from CRM systems, and a lack of analytical CRM solutions from vendors. Methodology It is believed that evaluating the analytical CRM solutions is useful to exlore the reasons behind the low level alication of analytical CRM. Thus, a self-evaluation aroach is adoted to assess the functionality of CRM systems rovided by some leading vendors. To evaluate the analytical function of current CRM software, 20 CRM systems are selected including comanies such as SAP, PeoleSoft, Siebel, Sage, Microsoft, Saratoga, Intersho, Firstwave, Eicor, etc. The CRM systems are evaluated based on the demo systems and the additional information available from the comany s brochures, web site, and other literature. The following four categories suggested by Chaudhury and Kuiboer (2002) and Sa.com (2003) are used to evaluate the 20 CRM systems. Oerational CRM. Customer data is collected through a whole range of touch oints such as contact centre, contact management system, mail, fax, sales force, web, etc. The Figure 1. Usage of analytical CRM (resonses in er cent)

8 data then are stored and organised in a customer centric database, which is made available to all users who interact with the customer. A tyical oerational CRM is the contact centre and contact management. A contact management system can rovide comlete and comrehensive tracking of information relating to any contact with customers. This is known as 100 er cent focus on the customer (Kotorov, 2002). The benefit of this tye of CRM is to ersonalise the relationshi with the customer, and to broaden the organisational resonse to the customer s needs. Analytical CRM. Data stored in the contact centric database is analysed through a range of analytical tools in order to generate customer rofiles, identify behaviour atterns, determine satisfaction level, and suort customer segmentation. The information and knowledge acquired from the analytical CRM will hel develo aroriate marketing and romotion strategies. This tye of CRM is referred by Kotorov (2002) as a 3608 view of the customer. Technologies underinning the analytical CRM system include CRM ortals, data warehouses, redictive and analytical engines (Eckerson and Watson, 2001); attern discovery association rules, sequential atterns; clustering, classification and evaluation of customer value (Ahn et al., 2003). As a result of the analysis, customers are more effectively segmented and offered roducts and services that better fit their buying rofiles. Collaborative CRM. The CRM systems are integrated with enterrise-wide systems to allow greater resonsiveness to customers throughout the suly chain (Kracklauer and Mills, 2004). For instance, a CRM can be extended to include emloyees, suliers, or artners. A collaborative selling CRM can offer knowledge and tools to everyone in the extended enterrise, and to hel drive sales through every channel from call centre to the web. e-crm. Allows customer information to be available at all touch-oints within the comany and among external business artners through the internet and the intranet. e-crm can be defined as a web-centric aroach to synchronizing customer relationshis across communication channels, business functions, and audiences (Forrester Research, 2001). e-crm enables online ordering, , a knowledge base that can be used to generate customer rofiles, ersonalised service, the generation of automatic resonse to , and automatic hel (Rowley, 2002). Gaining customer knowledge 961 Findings: rovision of analytical CRM functions Table II shows the result of the evaluation of 20 leading CRM software functions (see Aendix). The results show that almost all of the CRM systems evaluated have oerational functions with tyical systems such as contact management, call centre alications, field sales and field service suort, and anoramic customer view. Some 40 er cent of the CRM systems offer analytical functions, for examle, mysap CRM rovides customer knowledge and analysis to the entire organization. PeoleSoft s analytical CRM function Frequency Per cent ðn ¼ 20Þ Oerational CRM Analytical CRM 8 40 Collaborative CRM 4 20 e-crm (web-based) 9 45 Table II. Common functions of CRM software

9 IMDS 105,7 962 CRM rovides real-time information about customer s buying atterns, re-and ost-sales behaviour and factors for customer retention. Forty-five er cent of the CRM vendors evaluated rovide e-crm solutions. The e-crm systems allow internal and external users to access customer-related information via the internet or intranet, and also to enable e-commerce functionality. For examle, Oracle s E-commerce alications can develo, manage and ersonalize scalable internet storefronts for B2B and B2C sales. Such alications offer self-service access to critical information and integrates contact management functionality with online store oerations. Collaborative CRM has been offered by less than a quarter (20 er cent) of the vendors. This is in line with the survey data that only one in five (20 er cent) of the comanies surveyed (2001) had already extended their CRM systems to include emloyees, suliers, or artners, whilst the survey in 2003 found only 12 er cent. The findings confirm Bose s (2002) argument that currently, standard CRM ackages have only scratched the surface of management suort ossibilities and that IT will need to look beyond the current offerings of just one or two vendors. The findings are in line with Kirchheimer s (2003) assertion that there are very few ure lay analytics vendors and even fewer analytical CRM vendors. Analytical CRM in most cases are made u of a number of discrete ieces of technologies that work together to rovide actionable information about customers. Most analytical CRM vendors are jostling for osition within the market, having come from very different backgrounds and with very different technologies. In summary, the main driving force of the current imlementation of CRM systems aears to be imroving oerational efficiency, rather than acquiring strategic customer information from the systems. There is great otential for analytical CRM and e-crm systems to be develoed, as at resent, they are rovided by less than half of the software vendors. It is certain that the real challenge does not lie in automating the front office with call center and contact management systems, but in the way CRM system is strategically used by organizations, in articular, how the analytical CRM systems should be develoed to rovide customer knowledge throughout the organization. The next section will discuss some of the analytical functions of the CRM system, and their ractical imlication to those organizations that wish to become a true customer centric organisation. An analytical CRM model The essential of acquiring customer knowledge is to know not only who they are (customer rofiling and segmentation) but also how they behave and what attern they follow. Customer knowledge acquisition should be treated as a dynamic and continuous rocess, to collect information about existing customers (internal), defecting customers (cross organisational boundary) and new customers. Knowledge about rosective customers and customers that are loyal to cometitors (external) should also be obtained. The findings suggest that in order to gain strategic benefits from the investment of CRM systems, managers on the one hand need to be aware of the ower of analytical CRM systems and the strategic imortance of gaining customer knowledge; on the other hand, analytical CRM systems that can suort customer knowledge acquisition need to be readily available and affordable. Thus, an analytical CRM system model that enables customer knowledge rovision is develoed and shown in Figure 2. The ractical imlication of this system is to increase the awareness

10 Gaining customer knowledge 963 Figure 2. An analytical CRM for customer knowledge acquisition and the ercetion of the ower of analytical CRM systems within managers and to rovide guidance to CRM vendors to develo more analytical solutions for customer knowledge acquisition. Identifying strategically significant customers Bolton (2004) refers to a bank s CRM system by suggesting that maintaining the rocessing of cheques, withdrawals, transfers, etc. is well established. However, it is simly transactional. It has no concet of whether the erson is an imortant and valued customer. An analytical CRM should rovide customer rofiling and customer segmentation functions with the caability to identify strategically significant customers. Marcus (2001) identified four tyes of strategically significant customers, which underins the suggested system. The first is the high lifetime value customer. Lifetime value otential is the resent-day value of all future margins that might be earned in a relationshi. Some customers have higher value to an organisation than others. Alexander and Turner (2001) suggest that all customers are not equal in their future value to an organisation some may even affect a loss. Thus, organisations need to calculate and redict customer lifetime value. Not all high volume customers are necessarily high lifetime value, and as such it is the high life value customers that must be the focus of customer retention efforts. There are many ways to identify high value customers, for examle, the Pareto or 80/20 rule, i.e. 20 er cent of existing customers may contribute 80 er cent of the rofit (or revenue). For a more accurate rediction of the life long value of a customer, the rofit/cost matrix together with retention/loyalty levels (variables) could be used. Figure 3 shows the rofit/cost matrix for determining customer value. Customer rofitability is the difference between revenue and costs. Calculating the customer contribution margin requires detailed analysis including factors such as roduct costs, costs to acquire, costs to serve and cost to retain. Predicting the lifetime value of a customer also needs to take into account the retention level and loyalty weighting.

11 IMDS 105,7 964 Figure 3. Profit-cost matrix The second grou of strategically significant customers are benchmarks. They may not necessarily be high value or high volume customers, but they are the early adoters of new roducts and the role model that will set the trend. Understanding the rofile and the behaviour of these benchmarks would enable the comany to foresee consumer trends earlier than their cometitors. The third grou are customers who insire changes in the sulying comany. They may be customers who stimulate the suliers to find new alications, come u with new roduct ideas, and find ways of imroving quality or reducing cost. Such customers may be the most demanding, or even frequent comlainers, but they offer otential sources of value. The final grou are customers who absorb a disroortionately high volume of fixed costs, thus enabling other smaller customers to become rofitable. This grou of customers is a valuable source for analysing costs associated with CRM. Managing strategically significant customers should be the focus of senior management. It is envisaged that an effective analytical CRM should be able to continuously identify and track such customers. Segmenting customers to ersonalize services In addition to identifying strategically significant customers, the analytical CRM system will hel rofile and segment existing customers. Customer rofiling combines multile asects of customers into a coherent evaluation, such as customer details, historical records and contact details, customer attractiveness, or customer satisfaction. Ferguson et al. (2004) reorted such a system used in a financial service comany that can rofile customers and the service reresentative can romtly assist the customer by ulling u all the customer s relevant information. Even though customer rofiling is oriented more towards the oerational function than the analytical function, it does rovide a comrehensive view of each customer. This is the information required to understand the true value of the customer and gain insights to understand customer behaviour. Existing customers can be segmented in many ways. This can lead to greater understanding about which customers and roducts have the most imact on the comany s oeration and strategy. The segmentation enables the comany to rovide more ersonalized and, therefore, more attractive roduct and service offerings to individual customer grous. Criteria for segmenting customers include: customer rofitability score, retention score, satisfaction and loyalty score, resonse to romotion. PeoleSoft uses a customer scorecard to track key erformance measurements and communicate rogress against CRM-related goals. The key erformance indicators

12 (KPIs) delivered with the customer scorecard for an organization s financial goals include revenue, margins, and rofitability; for customer goals, the KPIs include acquisition, retention, and satisfaction; for rocess goals, the KPIs include camaigns, sales, and suort; for workforce goals, the measurements include retention and cometencies. The ossible criteria to suort customer segmentation are: rofitability by customer and distribution channel; cost to suort by roduct and customer; average order value by customer; customer acquisition rate; customer defection rate; reeat customer rate; and customer satisfaction. Although retaining existing customers is erceived more imortant than acquiring new customers, turning external, otential rosective customers into the comany s customer is often the battleground between cometitors. Attracting external customers reflects a manager s oen and forward vision, which is often judged as a strategic cometence of senior managers. Knowing rosective customers and customers loyal (or defecting) to cometitors is an asset to CRM. The analytical CRM system offers the function of rofiling and analysing rosective customers. This requires data to be fed into the CRM from both internal and external sources. The CRM may also need to be integrated with a cometitive intelligence system in order to rofile and analyse customers that are loyal or have defected to the cometitors. Gaining customer knowledge 965 Tracking and modelling customer behaviour atterns Customer behaviour modelling is a rocess that includes segmenting target customer grous, establishing criteria for measuring behaviour, monitoring and tracking behaviour changes, generating behaviour atterns, and redicting ossible future behaviour. Figure 4 shows the rocess of behaviour modelling. Select target customer grous. Different customer segments may have different behaviour atterns, thus modelling customer behaviour needs to select a articular customer grou. For examle, it would be useful to know how strategically significant customers erceive the comany, interact with the comany and resond to the comany s offerings and romotions. The target customer grou may also be identified by their articular behaviour, for examle, a grou of defecting customers, a grou of regular comlainers. Based on such segmentation, their ercetions and shoing atterns can be monitored. Develoing measures to monitor customer behaviour. It is imortant but often difficult to know what needs to be known. Effective behaviour modelling needs to re-define the tyes of behaviour to be modelled and how the behaviour is to be measured. Table III outlines some tyical customer behaviour atterns that should be modelled by an analytical CRM system. Figure 4. Customer behaviour modelling

13 IMDS 105,7 966 Table III. Tyes of customer behaviour Customer behaviour Purose Measures Purchasing behaviour To know the tye of roducts and volume/value Frequency, date, time, volume and value against roduct tye Frequency of contact, length of each contact, channel of contact, and urose of the contact Contact behaviour To know how a articular customer contacts the comany Tye of retention customers, frequency of retention, average volume of customer order, factors affecting customer retention Retention behaviour Reduces the likelihood to churn among valuable customers and increase customer retention Per cent ignoring, noticing, taking action; changes in ercetion/actions, e.g. frequency of urchasing Resond behaviour Predict customer resonses to marketing and sales camaigns Percentage of defection, trends of defection, tye of defecting customers Migration and defection behaviour Tracks the changing behaviour of customers and monitors the changes in customer segments

14 Tracking and generating emerging atterns. Customer behaviour needs to be continuously monitored and tracked in order to identify customer behaviour atterns and trends, and to detect any abnormal behaviour or emerging atterns for managers attention. Monitoring and tracking should be based on the re-defined criteria to guide what to monitor and how. To fulfil this function, intelligent agent and exert systems can be included as a art of the analytical CRM system to enhance the detection, comarison, reasoning and alerting function. Predicting ossible actions. Finally, the analytical CRM will redict ossible actions that are likely to be taken by customers based on the behaviour and attern generated. PeoleSoft refers to this as redictive analytics. Such analytics will enable managers to look ahead, and to rovide guidance on how best to manage and treat customers. For examle, to redict whether a customer is likely to urchase or defect, and which grou of customers are at risk of attrition. In addition to managerial suort, the analytics can guide staff that have direct contact with customers as to which offers can imrove their satisfaction, and make real-time recommendations on the best offers. Gaining customer knowledge 967 Managerial imlications The imlications for management of using analytical CRM lie not so much with imroving oerational efficiency as with other CRM systems, but rather with the emowerment of management in the strategic decision-making rocess. Such emowerment is achieved through customer knowledge acquisition and knowledge sharing, thus enabling the business to become a knowledge driven organisation. To achieve this, senior management need to raise their awareness of analytical CRM and the otential benefits, based on which to develo a vision focusing on gaining customer knowledge, and articulating the vision throughout the organisation, whilst also being suortive to the develoment of such systems. The biggest threat to CRM, as suggested by Bose (2002), is managements focus on short-run rofits rather than long-term vision. A knowledge-based organisation would require more secialists and may need to eliminate middle managers (Drucker, 1998). The organisational strategy, structure and rocess may need to be transformed due to the alication of analytical CRM. The success will lie not only with successful imlementation of the analytical CRM software, but the synergy of the systems, rocess and eole. Much of the customer knowledge gained through the analytical CRM can be codified, thus it can be made exlicit for sharing. This falls rimarily into the codification strategy for KM as suggested by Hansen et al. (1999). Codification strategy for imlementing KM requires an information system that stores knowledge and allows its reuse. This is oosite to ersonalisation strategy for KM, which calls for a network system that links emloyees/exertise for sharing tacit knowledge. It is, however, envisaged that the analytical CRM will enhance customer knowledge creation, whilst the KM tools will enable customer knowledge to be communicated, disseminated and effectively used. Integration between the multile touch oints with customers (oerational CRM), the analytical CRM, and KM tools is required in order to maximise the full ower of the analytical system. How to imlement the analytical CRM system for customer knowledge acquisition is beyond the scoe of this aer, however, some issues tend to be critical to all tyes of

15 IMDS 105,7 968 CRM success, thus are outlined below and should be taken into account when imlementing analytical CRM systems. Misunderstanding the ower of CRM Snyder and Davidson (2003) suggest that u to 80 er cent of CRM rojects resulted in failure. One of the reasons is the lack of CRM understanding. Bolton (2004) suggested that imlementation may fail because the organisation fails to adot a clear strategy and fails to make aroriate changes to its business rocess. Too many comanies install a CRM software alication in the belief that this will deliver the CRM caability the comany needs. The most common fault was to focus on technology in setting out to imlement CRM, to the exclusion of eole, rocess and organisational changes required. Lack of customer focus by senior management Harvey (2001) reorts (based on Qci Consultancy s audit of 50 comanies) that: only 17 er cent of comanies incororated customer acquisition, retention and develoment costs in their marketing lan. He concluded that desite all the talk of customer focus, there is little evidence that senior executives have their fingers on the ulse. Three quarters of senior management do not have regular, direct contact with their customers. Hung et al. (2005) examined the factors critical to adot KM systems, and highlighted the leadershi and commitment of senior management as one of the key factors. The ercetion and suort of senior managers for the develoment of analytical CRM is critical. Conclusion The CRM systems that have been imlemented by many comanies are dominated by oerational alications contact centres, sales and marketing solutions with limited customer knowledge gained from the current CRM alication. The analytical ower of CRM has not been adequately erceived by many organisations. The rovision of analytical CRM solutions is limited to some large organisations. It is suggested that CRM systems should enhance not only an organization s ability to interact, attract and build one-to-one relationshis with customers but also the ability to gain customer knowledge. Such a system should enable functionality for both internal (existing) and external (rosects) customer knowledge rovision. The system will not only rovide a anoramic customer view through rofiling but also generate customer behaviour atterns and redict future actions. The success of imlementing such a system relies on senior managers awareness and suort, the solutions rovided by the IT industry, but more imortantly, organisational changes required to create a knowledge centric organisation. The limitation of this study is noted and that the evaluation of CRM solutions is subjective. However, there is evidence to suort the argument that organisations have not yet benefited from using analytical CRM to gain customer knowledge. The model roosed in this aer would shed light on how such a system can be develoed. References Ahn, J.Y., Kim, S.K. and Han, K.S. (2003), On the design concets for CRM system, Industrial Management & Data Systems, Vol. 103 No. 5,

16 Alexander, D. and Turner, C. (2001), The CRM Pocketbook, Management Pocketbooks Ltd, Alresford. Bolton, M. (2004), Customer centric business rocessing, International Journal of Productivity and Performance Management, Vol. 53 No. 1, Bose, R. (2002), Customer relationshi management: key comonents for IT success, Industrial Management & Data Systems, Vol. 102 No. 2, Bose, R. and Sugumaran, V. (2003), Alication of knowledge management technology in customer relationshi management, Knowledge & Process Management, Vol. 10 No. 1, Cambell, A. (2003), Creating customer knowledge: managing customer relationshi management rograms strategically, Industrial Marketing Management, Vol. 32 No. 5, Chaudhury, A. and Kuiboer, J.P. (2002), e-business and e-commerce Infrastructure, McGraw-Hill, New York, NY, Choy, K.L., Fan, K.K. and Lo, V. (2003), Develoment of an intelligent customer-sulier relationshi management system: the alication of case-based reasoning, Industrial Management & Data Systems, Vol. 103 No. 4, Daft, R., Sormunen, J. and Parks, D. (1988), Chief executive scanning, environmental characteristics, and comany erformance: an emirical study, Strategic Management Journal, Vol. 9 No. 2, Drucker, P. (1996), The information executives truly need, Harvard Business Review, January-February, Drucker, P. (1998), The coming of new organisation, Harvard Business Review, January-February, Dyer, N.A. (1998), What s in a relationshi (other than relations)?, Insurance Brokers Monthly & Insurance Adviser, Vol. 48 No. 7, Eckerson, W. and Watson, H. (2001), Harnessing customer information for strategic advantage: technical challenges and business solutions, Industry Study, The Data Warehousing Institute, Seattle, WA,. 6. Feinberg, R.A., Kadam, R., Hokama, L. and Kim, I. (2002), The state of electronic customer relationshi management in retailing, International Journal of Retail & Distribution Management, Vol. 30 No. 10, Ferguson, T., Lin, B. and Chen, J. (2004), Leveraging the workforce using information technology: a financial service case study, International Journal of Management Enterrise Develoment, Vol. 1 No. 4, Forrester Research (2001), Glossary, available at: Hansen, M., Nohira, N. and Tierney, T. (1999), What s your strategy for managing knowledge?, Harvard Business Review, March-Aril, Harvey, D. (2001), Tougher times ahead, Consectus The IT Reort for Directors and Decision Makers, October, Hung, Y.C., Huang, S.M., Lin, Q.P. and Tsao, M.L. (2005), Critical factors in adoting a knowledge management system for the harmaceutical industry, Industrial Management & Data Systems, Vol. 105 No. 2, Kandamully, J. and Duddy, R. (1999), Relationshi marketing: a concet beyond rimary relationshi, Marketing Intelligence & Planning, Vol. 17 No. 7. Gaining customer knowledge 969

17 IMDS 105,7 970 Kotorov, R. (2002), Ubiquitous organisation: organisational design for e-crm, Business Process Management Journal, Vol. 8 No. 3, Kracklauer, A.H. and Mills, D.Q. (Eds) (2004), Collaborative Customer Relationshi Management: Taking CRM to the Next Level, Sringer, Berlin. Lee, S.M. and Hong, S. (2002), An enterrise-wide knowledge management system infrastructure, Industrial Management & Data Systems, Vol. 102 No. 1, Luck, D. and Lancaster, G. (2003), E-CRM: customer relationshi marketing in the hotel industry, Managerial Auditing Journal, Vol. 18 No. 3, Marcus, C. (2001), Effective CRM requires sound segmentation, Research Notes, Gartner Research, available at: Minna, R. and Aino, H. (2005), Customer knowledge management cometence: towards a theoretical framework, Proceedings of the 38th Hawaii International Conference on System Sciences, IEEE /05, available at: Paiva, E.L., Roth, A.V. and Fensterseifer, J.E. (2002), Focusing information in manufacturing: a knowledge management ersective, Industrial Management & Data Systems, Vol. 102 No. 7, Roscoe, D. (2003), So what is the future for CRM?, Journal of Customer Management, Rowley, J. (2002), Eight questions for customer knowledge management in e-business, Journal of Knowledge Management, Vol. 6 No. 5, Rowley, J. (2004), Partnering aradigms? Knowledge management and relationshi marketing, Industrial Management & Data Systems, Vol. 104 No. 2, Sa.com (2003), SAP white aer analytical CRM, available at: Shaw, C. and Ivens, J. (2002), The seven hilosohies of building great customer exeriences, Journal of Customer Management, Novemver, Snyder, M. and Davidson, I. (2003), In trouble?, Consectus The IT Reort for Directors and Decision Makers, Sweet, P. (2001), CRM urse strings tighten, Consectus The IT Reort for Directors and Decision Makers, October, Sweet, P. (2002), Users kee the faith, Consectus The IT Reort for Directors and Decision Makers, October, Sweet, P. (2003), New wave of CRM, Consectus The IT Reort for Directors and Decision Makers, March, Sweet, P. (2004), Light at the end of CRM tunnel, Consectus The IT Reort for Directors and Decision Makers, March, Swift, R.S. (2001), Accelerating Customer Relationshi Using CRM and Relationshi Technologies, Prentice-Hall, Englewood Cliffs, NJ. Taylor, S. and Hunter, G. (2002), The imact of loyalty with e-crm software and e-services, International Journal of Service Industry Management, Vol. 13 No. 5, Tzokas, N. and Saren, M. (2002), Cometitive advantage, knowledge and relationshi marketing: where, what and how?, Journal of Business & Industrial Marketing, Vol. 19 No. 2, Wells, J.D., Fuerst, W.L. and Choobineh, J. (1999), Managing information technology (IT) for one-to-one customer interaction, Information & Management, Vol. 35,. 54. Xu, X., Kaye, G.R. and Duan, Y. (2003), UK executives vision on business environment for information scanning a cross-industry study, Information & Management: The International Journal of Information Systems Alications, Vol. 40 No. 5,

18 Xu, Y., Yen, D., Lin, B. and Chou, D. (2002), Adoting customer relationshi management technology, Industrial Management & Data Systems, Vol. 102 No. 8, Zineldin, M. (1999), Exloring the common ground of total relationshi management and total quality management (TQM), Management Decision, Vol. 37 No. 9. Zineldin, M. (2000), Beyound relationshi marketing: technologicalshi marketing, Marketing Intelligence & Planning, Vol. 18 No. 1. Further reading Chien, T., Chang, T. and Su, C. (2003a), Did your efforts really win customers satisfaction?, Industrial Management & Data Systems, Vol. 103 No. 4, Chien, T., Su, C. and Su, C. (2003b), Imlementation of a customer satisfaction rogram: a case study, Industrial Management & Data Systems, Vol. 102 No. 5, PeoleSoft (2003), Predictive analytics enables business users to look ahead, PeoleSoft, available at: Gaining customer knowledge 971 Aendix CRM vendors Oerational CRM Analytical CRM Collaborative CRM e-crm (web-based) Alix UK Ascent Astea Cincom Comaq Connergent Eicor Noetica Onyx Oracle PeoleSoft royalblue Sage SAP Saratoga SAS Siebel The Prolog Tranzline Udate Table AI. Common function of CRM