Strategic, Operational, and Analytical Customer Relationship Management

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Strategic, Operational, and Analytical Customer Relationship ManagementReiny Irianaa; Francis Buttlea

a Macquarie Graduate School of Management (MGSM), Macquarie University, Sydney, Australia

To cite this Article Iriana, Reiny and Buttle, Francis(2007) 'Strategic, Operational, and Analytical Customer RelationshipManagement', Journal of Relationship Marketing, 5: 4, 23 — 42To link to this Article: DOI: 10.1300/J366v05n04_03URL: http://dx.doi.org/10.1300/J366v05n04_03

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Strategic, Operational, and AnalyticalCustomer Relationship Management:

Attributes and Measures

Reiny Iriana

Macquarie University

Francis Buttle

Macquarie University

ABSTRACT. Customer Relationship Management (CRM) means dif-ferent things to different people. For some, CRM is the term used to de-scribe a set of IT applications that automate customer-facing processesin marketing, selling and service. For others, it is about an organizationaldesire to be more customer focused. Others associate CRM with the cap-ture, analysis and exploitation of customer-related data. One distinctionthat has been made is between strategic, operational and analyticalCRM. This paper sets out to understand, conceptualize and operationalizethese terms. Our research generally supports the idea of a multi-dimen-sional conceptualization of CRM. We develop and present an instru-ment, consisting of a thirteen-item scale, which can be used to assess anorganization’s orientation towards one or more of these three forms ofCRM. doi:10.1300/J366v05n04_03 [Article copies available for a fee fromThe Haworth Document Delivery Service: 1-800-HAWORTH. E-mail address:

Reiny Iriana, MM, is a Doctoral Candidate and Francis Buttle, PhD, is Professor ofManagement and Chair of Marketing, both at Macquarie Graduate School of Manage-ment (MGSM), Macquarie University, North Ryde, Sydney, Australia.

Address correspondence to: Francis Buttle, Macquarie Graduate School of Man-agement (MGSM), Talavera Road, North Ryde, Sydney, NSW 2109, Australia (E-mail:[email protected]).

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KEYWORDS. Customer relationship management, CRM, strategicCRM, operational CRM, analytical CRM, measurement scale

CRM DEFINITIONS AND PERSPECTIVES

Many definitions of Customer Relationship Management (CRM)have been developed and published. Academics and practitioners seeCRM as touching on issues of business strategy (Gummesson, 2002;CRMguru.com, quoted in Tan et al., 2002), customer life-cycle man-agement processes (Galbreath & Rogers, 1999; Nancarrow et al., 2003;Parvatiyar & Sheth, 2001), information technology (Gefen & Ridings,2002; Shoemaker, 2001), and communications strategy (Kay Mandati,quoted in McKim, 2002; Swift, 2001). CRM is also seen as multiple-variate construct, a combination between strategy and IT (Payne &Frow, 2005), between process and IT (Plakoyiannaki & Tzokas, 2002),between strategy, process and IT (Buttle, 2004; Rigby et al., 2002), andbetween process, strategy, philosophy, capability and IT (Zablah et al.,2004). These many definitions are evidence of the emergent and variednature of CRM. Some authorities have concluded that an agreement ona definition of CRM is needed before it can become a distinct manage-ment discipline (Paas & Kuijlen, 2001; Parvatiyar & Sheth, 2001;Plouffe et al., 2004).

Given the diversity of definitions and descriptions of CRM’s scope itshould come as no surprise that there have been several attempts to pro-duce taxonomies that recognize different forms of CRM. One earlyeffort identified three different forms of CRM: Operational, Collabora-tive, and Analytical CRM (METAGroup, 2001, p. 5). They defined theseforms as follows:

Operational CRM comprises “the business processes and technol-ogies that can help improve the efficiency and accuracy of day-to-day customer-facing operations.” This includes sales, marketing,and service automation.

Collaborative CRM comprises “the components and processesthat allow an enterprise to interact and collaborate with theircustomers.” This includes voice technologies, Web store-fronts,e-mail, conferencing and face-to-face interactions.

24 JOURNAL OF RELATIONSHIP MARKETING


Analytical CRM “provides analysis of customer data and behav-ioral patterns to improve business decisions.” This includes theunderlying data warehouse architecture, customer profiling/seg-mentation systems, reporting, and analysis.

Building on the META Group’s representation of a tripartite CRMecosystem, Payne and Frow (2005) proposed a strategic framework forCRM consisting of five interrelated cross-functional processes: thestrategy development process, value creation process, multi-channel in-tegration process, information management process, and performanceassessment process. Four of these five processes are subsumed withinthree forms of CRM–Strategic, Operational, and Analytical–as shownin Figure 1.

Strategic CRM encompasses the strategy development process andthe value creation process, and therefore answers questions such as“what business are we in?”, “which customers do we serve?”, and “howdo we create and deliver value to these customers?” Operational CRMis focused on the management of the virtual and physical channelsthrough which customers and organization communicate and transact.Analytical CRM is focused on the development and exploitation of cus-tomer data. Figure 1 also illustrates how these three forms of CRM areinterrelated. Analytical CRM, for example, supports Operational CRMby feeding the right information at the right time to agents and channelsinteracting with customers (Payne, 2006; Payne & Frow, 2005).

Reiny Iriana and Francis Buttle 25

STRATEGIC CRM OPERATIONAL CRM

StrategyDevelopment

Process Value Creation ProcessMulti-Channel

Integration Process

Physical& VirtualChannels

Information Management Process

IntegratedChannel

Management

PerformanceAssessment

Process

ShareholderResults

PerformanceMonitoring

ANALYTICAL CRM

BusinessStrategy

ValueOrganization

Receives

ValueCustomerReceives

CustomerSegmentLifetimeValue

AnalysisCustomerStrategy

FIGURE 1. Strategic, Operational, and Analytical CRM


CRM initiatives can also be classified according to their implementa-tion objectives. Organizations implement CRM to achieve certain busi-ness outcomes, which are reflected in their expectations of CRM. Xuand Walton (2005) provide examples of CRM objectives, including thefollowing: to improve customer satisfaction levels, to retain customers,to improve customer lifetime value, to deliver better strategic informa-tion to relevant departments, to attract new customers and to cut cost.An organization implementing an Analytical CRM project would aimto have better marketing and sales programs by collecting customer dataand analyzing relevant data into actionable information, resulting cus-tomers being offered an appropriate product, in suitable channels at theright time. A company implementing an Operational CRM project mightbe keen to reduce cost-to-serve and improve transactional accuracy. Acompany implementing Strategic CRM project might be aiming to trans-form the business into a customer-centric organization with the goal ofincreasing customer profitability (Chye & Gerry, 2002; Hughes, 2002).

STRATEGIC, OPERATIONAL,AND ANALYTICAL CRM

We now explore in greater detail the three forms of CRM identifiedby Payne and Frow (2005)–Strategic, Operational, and Analytical (SOA)CRM.

Strategic CRM. Buttle (2004) defined Strategic CRM as “a top downperspective on CRM, which views CRM as a core customer centricbusiness strategy that aims at winning and keeping profitable custom-ers” (p. 3). Plakoyiannaki and Tzokas (2002) explained that when CRMserves as a basic business strategy, it reflects a long-term vision of striv-ing to create and deliver value to customers. Lin and Su (2003) addedthat Strategic CRM gives the opportunity to leverage customer knowl-edge and create value for customers and, in the end, helps organizationsto understand and fulfill current and potential customers’ needs.

Payne and Frow (2005) noted that an important goal in StrategicCRM is to align the broader business strategy with customer strategy.They suggest that an understanding of business strategy issues, such ascorporate vision and industry and competitor profiles, can help an orga-nization develop Strategic CRM that is consistent vis-á-vis its own con-text. Customer strategy is concerned with aligning customer segmentsto relationship management strategies. The managerial discipline ofcustomer portfolio analysis (Turnbull & Zolkiewski, 1997) enables



companies to carve up their current and potential customer base intosegments that can then be treated to specific relationship managementstrategies. Buttle (2004) identifies seven basic relationship strategiesfor identified segments: start a relationship, re-engineer the relation-ship, enhance the relationship, protect the relationship, harvest the rela-tionship, win-back the relationship, and end the relationship.

Payne and Frow (2005) explained that in the value creation process,business and customer strategy decisions are translated into implementa-tion programs that generate value for customers and organization alike.The main perspectives of the value creation process are the value thecustomer receives and the value the organization receives. The value thecustomer receives is delivered by the value proposition of the organiza-tion. Organizations generally strive to develop offers that they believewill meet the needs and expectations of customers more effectively orefficiently than competing offers. The value the organization receives isthe return on investments in the value creation process. Customer Life-time Value (CLV) is a metric that can be used to measure the customer’spotential profit over a defined lifetime of transactions.

Operational CRM. Buttle (2004) defined Operational CRM as “aperspective on CRM which focuses on major automation projects with-in the front-office functions of selling, marketing and service.” Opera-tional CRM automates the business processes underpinning the day-to-day tasks of sales, marketing, and service functions across a range ofcustomer touch points and channels. Sales force automation appliestechnology to the management of selling activities to optimize salesproductivity by improving the speed and quality of information flowto improve internal communications between the sales force and man-agement (Speier & Venkatesh, 2002; Tan et al., 2002). Tan et al. (2002)observe that marketing automation applies technology to marketingprocesses to help organizations manage their marketing programs. Sim-ilarly, service automation allows organizations to automate their serviceoperations, often with the objective of increased customer satisfactionby accelerating the inquiry and feedback processes across multiplecommunication channels. The general objective of Operational CRMis to improve the efficiency and effectiveness of customer manage-ment processes, by personalizing the relationship with customers, byimproving organizational response to customers’ needs (Xu & Walton,2005) and by increasing the speed and quality of information flows inthe organization, and between the organization and its external employ-ees and partners (Speier & Venkatesh, 2002).



Payne and Frow (2005) point out that channel integration is animportant motivation for many Operational CRM system implementa-tions. This multi-channel integration process attempts to ensure consis-tency and high quality in the customer’s experience across differentcommunications and transaction channels.

Chan (2005) explained that Operational CRM data consists of trans-actional data from front-line customer touch points, such as sales,surveys, customer inquiries, and other customer interactions. Xu andWalton (2005) noted that Operational CRM data also exist in contact cen-tres and derive from contact management activities. Fayerman (2002)argued that data from back office functions, such as from human re-sources and finance, might be needed for Operational CRM to functioneffectively.

Analytical CRM. Buttle (2004) defined Analytical CRM as “a bot-tom-up perspective, which focuses on the intelligent mining of cus-tomer data for strategic or tactical purposes.” Payne and Frow (2005)suggest that Analytical CRM refers to the information managementprocesses that rotate around the collection, accumulation, and analysisof customer information from customer interfaces. Knox, Maklan,Payne, Peppard, and Ryals (2003) explained that this informationmanagement process supports the strategy development process byproviding information about market characteristics that can be used todevelop customer strategy, as well as assist in the value creation pro-cess, determine customer lifetime value and develop new products andservices.

Analytical CRM uses technology to accumulate, store, organize,interpret, distribute, and exploit customer data. Customer informationmay be analyzed to develop customer profiles and opportunities thatwill be delivered to the touch points and channels for better OperationalCRM applications (Payne, 2006). Customer information helps the orga-nization to understand customer behavior better, to conduct the righttransaction at the right time, and to be able to segment its market effec-tively (Plakoyiannaki & Tzokas, 2002; Xu & Walton, 2005).

Herschel (2002) identified several applications within AnalyticalCRM, including customer segmentation analysis, customer profitabil-ity analysis, “what if” analysis, real-time event monitoring and trigger-ing, campaign management, and personalization. Doyle (2002) alsosuggested other analytical tools such as, analysis of the characteristicsand behavior of customers, modeling to predict customer behavior,communications management with customers, personalized communi-cations with customers, interactive management and optimization to



determine the best combination of customers, products, and communica-tions channels. Gebert, Geib, Kolbe, and Brenner (2003) claim that datawarehousing and data mining solutions are standard technology appli-cations in Analytical CRM.

Analytical CRM systems can increase revenue in many ways, such asthrough cross-sell and up-sell campaigns, predicting which customersare most likely to buy, identifying high value customers, increasingbrand awareness, and promoting customer satisfaction, loyalty and re-ferrals (SAS, 2002). Key success factors for Analytical CRM systemimplementation have been identified as the empowerment of manage-ment through the sharing of customer information (Xu & Walton, 2005)and strong teamwork between marketing and customer service (Herschel,2002). The lack of an integrated view of customers, insufficient cus-tomer intelligence, inability to act on customer intelligence quickly(SAS, 2002), and the lack of the awareness of the potential benefit ofAnalytical CRM (Xu & Walton, 2005) were identified as reasons forfailures to implement Analytical CRM systems effectively.

RESEARCH OBJECTIVES

Our research aims to develop an instrument that can be used to assess acompany’s orientation towards Strategic, Operational or AnalyticalCRM (collectively SOA CRM). Our research process establishes whetherthese three forms of CRM are conceptually and operationally different.

Research Methodology and Analysis. Our method for creating thescale is broadly based on the recommendations of Churchill (1979) forthe development of better marketing constructs.

The Generation of Scale Items

Our literature review on CRM definitions and perspectives, which issummarized above, generated an exhaustive set of attributes that hadbeen used to describe and discriminate between different types of CRMinitiative. Appendix 1 contains the 32 items which appeared in our orig-inal pool of CRM descriptors, identifies which items were initially asso-ciated with each type of CRM and the position in which the itemsappeared in the questionnaire that we developed for the first stage of thescale refinement process.



Scale Refinement

First Study

For the first study, a questionnaire was developed, piloted, refinedand distributed to a convenience sample of Executive Master of Busi-ness Administration (MBA) students who had taken one of three pre-sentations of an elective CRM course. The average age of the studentswas 32 years and the average length of business experience was 9 years.In total, 115 questionnaires were distributed and 48 responses or 41.7%were returned for analysis. Participants were asked to reflect on cus-tomer management practices in their own organizations and to expressthe degree to which they agreed or disagreed that the 32 scale itemsdescribed the customer management practices of their own companies.Participants were advised that even though their organization may nothave developed a formal CRM strategy, it would have a de facto CRMstrategy with people, process, and technology used for the managementof customer relationships. A 7-point, Likert type response format wasused in which 1indicated that the respondent strongly disagreed with theitem statement and 7 indicated that the respondent strongly agreed withthe item statement.

The initial stage of scale reduction (purification) was performed usingtwo statistical processes: exploratory factor analysis as recommended byChurchill (1979) and item-total correlations (Nunnally, 1978).

Factor analysis is used to identify the underlying dimensions, or fac-tors, that explain correlations among variables (Malhotra et al., 2002).This process aims to discover whether a smaller number of factors canaccount for the variance within the data set. The Kaiser-Meyer-Olkin(KMO) measure was used to determine whether the data set was suitedto factor analysis. The KMO measure of sampling adequacy for ourdata is 0.811, a high value and close to 1, the perfect adequacy level(Malhotra et al., 2002). This supports the application of factor analysisto the data. Bartlett’s test of sphericity also confirmed that the data weresuited to factor analysis.

The data set was factor analyzed using principal component analysisfollowed by varimax rotation. This generated a 7-factor solution, witheach factor having an eigenvalue exceeding 1. The 7-factor solutionaccounted for 77.85% of the variance. The results of the EFA are inAppendix 2.

Items with loadings of 0.40 or greater on more than one of the factorswere removed. This resulted in the removal of seven items that had been



developed initially as Strategic CRM items (S7, S14, S20, S22, S26,S29, and S30), five items from the Operational CRM battery (O4, O6,O9, O10, and O11), and two items from the Analytical CRM battery(A12 and A13). The remaining 18 items were again factor analyzed, us-ing principal component analysis followed by varimax rotation. Based onthe SOA conceptualization of CRM, we made an a priori determinationthat three factors would be retained (Hair Jr. et al., 1998). The KMO mea-sure of sampling adequacy was 0.846 and the Bartlett’s test of sphericitysignificance level was less than 0.05, both indicators again suggestingthat the data were suitable for factor analysis. The resulting 3-factor solu-tion, as indicated in Appendix 3, accounted for 66.04% of the variance.

To achieve a more parsimonious scale, the nine items loading on fac-tor 1 were analyzed using item-total correlations. Item-total correlationmeasures the correlation between a single scale item and the overallcomposite factor score. Items having low correlations are candidates forelimination from the scale. This resulted in the removal of a further fouritems. At the end of the scale refinement process, 14 items remained,clustered, interpreted, and named as follows:

Factor 1: Strategic CRM. This factor comprises five items in total,made up of three items from the Strategic CRM inventory (S19, S21, andS28), and two items with the highest corrected item-total correlations,both initially associated with the Analytical CRM set (A31 and A32).

Factor 2: Analytical CRM. This factor comprises five items in total,made up of four items from the Analytical CRM inventory (A1, A2, A3,and A5), and one item initially associated with the Operational CRMset (O15).

Factor 3: Operational CRM. This factor comprises four items intotal, made up entirely of items initially associated with the OperationalCRM inventory (O16, O23, O24, and O25).

These factors are closely, but not perfectly, aligned with the a prioriclassification of Strategic, Operational, and Analytical CRM.

The reliability of each component or factor (Strategic, Operational,and Analytical CRM) and the overall (combined) scale were assessed bycomputing Cronbach alpha (Gerbing & Anderson, 1988). Reliabilities ofthe component scales are in the range of 0.751 to 0.891, with the overallCronbach alpha for the SOA scale being 0.904. These levels of reliabil-ity are satisfactory. In addition, according to a Monte Carlo study byGuadagnoli and Velicer (as cited in Stevens, 2002), constructs with fouror more loadings above 0.60 in absolute value are reliable, regardless ofsample size.



Second Study

A second phase of scale refinement was conducted as part of alarger project. Invitations to participate were sent to named individu-als in 1,449 public and private-sector organizations in Australia. Thelist, which included individuals holding management positions insales, marketing, customer service, and information technology in 11industries, was obtained from Dun and Bradstreet Information Ser-vices. Participants were sent a six-page questionnaire, with cover let-ter and reply paid envelope. After sending reminders by surface mailand a follow-up phone call encouraging people to participate, a totalof 134 questionnaires were returned (9.25% response rate). A totalof 101 questionnaires were identified as usable. The questionnairecontained questions on a number of CRM topics, including the 14SOA CRM items remaining from the first scale refinement study. Alow response rate had been anticipated because only organizationswith a CRM system in place could complete the survey and from pre-vious research we knew that only 35% of Australian organizationswith 500 employees or more had implemented any form of CRM strat-egy (Peterson, 2003).

In evaluating whether the SOA measurement model is unidimen-sional, each of the three elements of the SOA CRM construct wastreated as a one-factor congeneric model (Joreskog, 1971). This is atype of measurement model within which a single latent variable (in thiscase, Strategic or Operational or Analytical CRM) is measured byseveral observed variables (the items making up the SOA inventory).Latent variables are theoretical constructs that are not directly observ-able or measurable but must be assessed indirectly or inferred from itemscores. The raw data from the 101 respondents were adjusted to take ac-count of some missing variables. These were input into the AMOSStructural Equation Modeling (SEM) program version 5.0 (Arbuckle,1999). Table 1 shows the model fit results for Strategic, Operational,and Analytical CRM.

From Table 1, Operational and Analytical CRM have non-significantchi-square or CMIN, with GFI (Goodness of Fit Index) and CFI (Com-parative Fit Index) above 0.90, indicating that the models fit the datawell. For Strategic CRM, although GFI is above 0.90, CMIN is signifi-cant at the 0.05 level and CFI is below 0.90. This indicates thatsome model modification for Strategic CRM is needed to produce abetter model fit. The first item in the Strategic CRM construct (S19) wasremoved from the model because it had the lowest factor loading (0.51).



Table 2 shows the model fit results for Strategic CRM after modifica-tion.

As shown in Table 2, Strategic CRM has a non-significant CMIN, and,with GFI and CFI both above 0.90, this is a strong indication that themodel fits the data well. Table 3 shows the final measurement instrumentconsisting of 13 items. This scale can be used to assess an organization’sorientation towards one or more of these three forms of CRM.

Reliability and Validity. The Strategic, Operational, and AnalyticalCRM scales have good reliabilities (above 0.60). However, reliabilitydoes not ensure validity (Hair Jr. et al., 1998). Satisfactory fit indices fora one-factor congeneric measurement model is evidence of good con-struct validity (Holmes-Smith et al., 2004). As shown in Tables 2 and 3,satisfactory model fit indices were achieved.

A more stringent test of validity is to determine the discriminant va-lidity of a construct. Discriminant validity among variables of a con-struct is achieved if the correlations between variables are significantlydifferent from ‘1’. Large correlations above 0.80 or 0.90 suggest a lack ofdiscriminant validity (Holmes-Smith et al., 2004). The correlation coeffi-cients between Strategic, Operational and Analytical CRM variablesrange from 0.296 to 0.582, which indicates good levels of discriminantvalidity (see Table 4).

CONCLUSION

The existing literature on CRM has identified three different but re-lated forms or types of CRM–Strategic, Operational, and Analytical.We set out to determine whether it was possible to develop a scale that


TABLE 1. Model Fit Summary

Construct Items Reliability CMIN DF GFI CFI

Strategic 5 0.808 28.483* 5 0.901 0.856

Operational 4 0.746 5.383** 2 0.973 0.963

Analytical 5 0.833 14.064*** 5 0.948 0.953

*Significant at the 0.05 level.

**Not significant at the 0.05 level.

***Not significant at the 0.01 level.


could discriminate between these forms of CRM. From a review of theliterature, we developed a set of items that appeared to have face valid-ity for describing these different types of CRM. In our first study, ex-ploratory factor analysis and item–total correlations were performed ondata collected from 48 participants. This produced item loadings thatwere unexpected. Items did not load on the factors to which they wereconceptually related. Our interpretation of the forced three-factor solu-tion supported the idea that Operational and Analytical CRM were reli-able and useful constructs. The Strategic CRM inventory, however,needed further work.

In our second study, data were collected from 101 new participantsand we were able to modify the Strategic CRM item inventory. Theone-factor congeneric model results encourage us to suggest that theStrategic, Operational, and Analytical CRM classification is a validconceptual model, and that it is possible to measure an organization’sorientation towards these three types of CRM. The final instrument con-sists of a 13-item scale that can be deployed in further CRM research.This is the first time that such a scale has been developed and published.

LIMITATIONS AND FURTHER STUDY

The major limitation of this research relates to the sample. Althoughthe sample size in our second study is within the desired level for reli-ability and validity testing, the sample size of 101 limits the ability touse more sophisticated statistical analysis to provide additional supportfor the validity of the measures, for example, the use of ConfirmatoryFactor Analysis for the three forms of CRM in a single structural model.

This model will be used in future CRM-related research. We proposeto test whether CRM system implementation outcomes vary accordingto the type of CRM initiative. For example, we want to find out whichof the three types of CRM yield the fastest outcomes, the best lon-ger-term returns, is the easiest to implement, and has most significant


TABLE 2. Strategic CRM Model Fit Summary–After Modification

Construct Items Reliability CMIN DF GFI CFI

Strategic CRM 4 0.790 4.420* 2 0.979 0.979

*Not significant at the 0.05 level.



TABLE 3. Refined Scale and Factor Loadings

Scale Items Loadings

Strategic Analytical Operational

Our CRM strategy aims to win and keepcarefully chosen customers or customersegments

0.60

Our company is using CRM to ensure that all ourpeople understand which customers we want toserve

0.74

Our company uses CRM to help us identifyhigh-value customers

0.71

Our company uses customer information toconstruct customer profiles which are used toimprove the consistency of the customer’sexperience

0.76

An important objective of our CRM program is tocreate a comprehensive customer-related database

0.67

An important objective of our CRM program is todeliver customer data to our people at the right timeso that they can cross-sell and up-sell customers

0.58

An important objective of our CRM program is todeliver customer data to our front-line staff so thatthey can sell, market and service our customersmore effectively

0.57

An important objective of our CRM programis to enable us to conduct intelligent analysesof customer data to guide our marketing andsales efforts

0.77

An important objective of our CRM program is toimprove the productivity of our sales people

0.82

An important objective of our CRM programis to reduce the cost of our customer-interfaceoperations

0.42

Our company uses CRM to automate customerservice processes to make them more efficientand effective

0.71

Our company uses CRM to automate marketingprocesses to make them more efficient andeffective

0.59

Our company uses CRM to automate sellingprocesses to make them more efficient andeffective

0.84


impact on customer experience. Organizations implement CRM formany reasons and generally have specific outcomes in mind. We wantto establish which types of outcomes are associated with each type ofCRM. For example, we would anticipate that a CRM objective thataimed to increase the number of products owned per customer would bemore strongly associated with Analytical CRM than Operational orStrategic CRM. Furthermore, the choice of CRM objective may affectthe strategies organizations adopt to reach the objective. We also want toidentify the strategies that are most likely to facilitate the achievementof a CRM project’s goals. Organizations implementing Strategic CRMmay find they achieve their goals by placing more importance on em-ployee behavior or organizational culture, such as moving towards amore customer-centric way of doing business, and encouraging partici-pation and team work. Organizations implementing Operational CRMmay place more importance on having efficient and effective front-officeprocesses. Organizations implementing Analytical CRM may wish toadopt the best technology for data capture and interpretation. The devel-opment of the SOA inventory will enable researchers to establish whichstrategies are most strongly associated with the successful achievementof desirable CRM outcomes.

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TABLE 4. Correlations Between SOA CRM

Strategic Operational Analytical

Strategic 1

Operational 0.582 1

Analytical 0.439 0.296 1


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doi:10.1300/J366v05n04_03




APPENDIX 1

The Initial Pool of Scale Items

Strategic CRM

S7. An important objective of our CRM program is to enhancethe lifetime value of our customers

S14. An important objective of our CRM program is to improveour understanding of customer needs, expectations, and preferences

S19. An important objective of our CRM program is to lift customersatisfaction and retention levels

S20. CRM provides the basis for our competitive advantageS21. Our CRM strategy aims to win and keep carefully chosen

customers or customer segmentsS22. Our CRM strategy creates mutual benefits for both

customers and companyS26. Our company uses CRM to create a customer-focused

business cultureS28. Our company uses CRM to ensure that all our people

understand which customers we want to serveS29. Our company uses CRM to help us be more customer

focused than our competitorsS30. Our company uses CRM to find better ways of offering

customers more value

Operational CRM

O4. An important objective of our CRM program is to enableus to adapt our offers to suit different customers’ requirements

O6. An important objective of our CRM program is to enable usto select the most appropriate communication channelsfor interaction with customers

O9. An important objective of our CRM program is to helpour marketing people run more effective and efficient campaigns

O10. An important objective of our CRM program is to help our salespeople to have more effective and efficient interactions with customers

O11. An important objective of our CRM program is to improvecollaboration with our customers and channel partners

O15. An important objective of our CRM program is to improvethe productivity of our sales people



APPENDIX 1 (continued)

O16. An important objective of our CRM program is to reducethe cost of our customer-interface operations

O18. An important objective of our CRM program isto deliver consistent customer experience across allcustomer touch points and channels

O23. Our company uses CRM to automate customer serviceprocesses to make them more efficient and effective

O24. Our company uses CRM to automate marketing processesto make them more efficient and effective

O25. Our company uses CRM to automate selling processesto make them more efficient and effective

Analytical CRM

A1. An important objective of our CRM program isto create a comprehensive customer-related database

A2. An important objective of our CRM program isto deliver customer data to our people at the right timeso that they can cross-sell and up-sell customers

A3. An important objective of our CRM program isto deliver customer data to our front-line staff so thatthey can sell, market and service our customers more effectively

A5. An important objective of our CRM program is to enableus to conduct intelligent analyses of customer data to guideour marketing and sales efforts

A8. An important objective of our CRM program is to ensure that analysisof customer-related data underpins all our customer interactions

A12. An important objective of our CRM program isto improve our ability to conduct real-time analysesof data when interacting with customers

A13. An important objective of our CRM program is to improveour forecasting capabilities

A17. An important part of our CRM program is the useof analytical tools to make sense of, and profit from, customer data

A27. Our company uses CRM to enable us to obtain acompetitive advantage from customer data

A31. Our company uses CRM to help us identify high-value customersA32. Our company uses customer information to construct customer profiles

which are used to improve the consistency of the customer’s experience



APPENDIX 2

Factor Loadings for the Initial 7-Factor Solution

Component or Factor

1 2 3 4 5 6 7A31 0.785 0.225 0.318 0.144 0.191 0.084 0.041S28 0.774 0.205 0.121 0.144 0.080 0.033 �0.057A32 0.706 0.129 0.290 0.288 0.209 0.222 0.143A27 0.702 0.392 0.284 0.158 0.213 0.091 �0.057S30 0.656 0.270 0.454 0.346 0.070 0.158 �0.045O10 0.595 0.535 0.162 �0.043 0.108 0.196 0.232S14 0.576 0.153 0.435 0.222 0.346 �0.144 0.286S29 0.571 0.328 0.494 0.114 0.046 0.224 �0.108S26 0.544 0.305 0.300 0.290 0.401 0.118 �0.094O15 0.152 0.852 0.097 0.025 �0.044 0.273 0.094A2 0.209 0.750 0.242 0.209 0.083 0.052 �0.005A3 0.361 0.742 0.179 0.019 0.116 0.186 0.167A5 0.196 0.673 0.271 0.326 0.087 0.007 �0.007A1 0.159 0.640 0.266 0.245 0.188 �0.013 0.134S21 0.292 0.306 0.805 0.074 0.029 0.045 0.159S20 0.404 0.218 0.706 0.136 0.196 0.238 �0.037S22 0.458 0.116 0.635 0.133 0.061 0.183 0.111O4 0.157 0.406 0.611 0.391 0.237 �0.033 �0.058S19 0.339 0.121 0.603 0.353 0.122 0.122 0.356A8 0.388 0.360 0.077 0.706 0.173 0.119 �0.116S7 0.098 0.188 0.549 0.685 0.068 0.088 �0.024O6 0.200 0.120 0.341 0.599 0.407 0.096 0.180O9 0.501 0.262 0.012 0.588 �0.024 �0.202 0.267O18 0.242 0.029 0.383 0.489 0.332 0.215 0.306A13 0.083 0.195 0.518 0.100 0.691 0.065 �0.004O11 0.420 �0.054 0.016 0.293 0.642 0.211 0.264A12 0.311 0.572 �0.147 0.056 0.576 0.133 �0.088A17 0.252 0.340 0.386 0.341 0.455 0.146 0.252O25 0.005 0.385 �0.013 0.132 �0.104 0.817 �0.008O23 0.173 0.051 0.151 �0.106 0.240 0.792 0.207O24 0.253 0.069 0.376 0.251 0.249 0.645 0.178O16 �0.050 0.150 0.091 0.058 0.075 0.201 0.854



APPENDIX 3

Factor Loadings for Forced 3-Factor Solution

Component or Factor

1 2 3

A32 0.836 0.186 0.221

A31 0.831 0.297 0.046

A27 0.727 0.492 �0.004

S19 0.722 0.161 0.323

O18 0.700 0.030 0.391

A17 0.669 0.326 0.356

S28 0.625 0.304 �0.069

S21 0.615 0.330 0.222

A8 0.568 0.465 0.017

O15 0.062 0.871 0.272

A3 0.319 0.781 0.226

A2 0.317 0.776 0.078

A5 0.401 0.686 0.055

A1 0.381 0.660 0.105

O23 0.203 0.081 0.795

O24 0.502 0.150 0.679

O25 �0.068 0.434 0.672

O16 0.094 0.040 0.640


Strategic, Operational, and Analytical Customer Relationship Management

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