HOW TO MEASURE THE IMPACT OF A CRM STRATEGY ON THE FIRM
PERFORMANCE

M. Rosa Llamas and M. Aránzazu Sulé
Área de Comercialización e Investigación de Mercados
Facultad de Ciencias Económicas y Empresariales
Universidad de León
Campus de Vegazana, s/n
24071 León (Spain)

M. Rosa Llamas e-mail:
Tl: +34 987 291455
Fax: +34 987 291454
M. Aránzazu Sulé e-mail:
Tl: +34 987 291000 Ext. 5451
Fax: 34 987 291454

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The importance of customer relationship management as source of competitive advantages
has been recognized for decades (McKenna, 1993; Woodcock, 2000), nevertheless, it has
been in recent years, with the deployment of the information technologies, when CRM has
gained growing popularity.

This business philosophy combines strategy and technology with the aim of get to know the
customer and establishing a two-way communication and interaction in order to improve the
efficiency and effectiveness of the business processes, increasing the value for both, customer
and company. There are three issues underlying the RM concept: relationships, networks and
interaction (Gummesson, 2002).

Srivastava, Shervani and Fahey (1999) in a special number of the Journal of Marketing
entitled “Fundamental issues and directions for marketing”, point out that the CRM is one of
the three key aspects in business processes since it lets the company identify consumers,
create knowledge, build relationships with customers and model their perceptions about the
company and its products. Brown (2000) considers that managing relationships with
customers is revolutionizing marketing and redefining business models. In this sense,
Greenberg (2001, p. 6) talking about CRM, states that we are on the verge of the most
significant transformation in business.

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Although CRM concept has been the central core of many articles, conferences and seminars,
so far most of them corresponds to enterprise initiatives and there is a lack of empirical
academic research (Ang and Buttle, 2002; Kim, Suh and Hwang, 2003; Plakoyiannaki and
Tzokas, 2001; Winer, 2001).

The CRM approach is simple but its implementation is complex, for that reason, a high
percentage of CRM projects fails. In this sense, authors like Grabner-Kraeuter and
Moedritscher (2000) and Woodcock (2000) and consulting firms such as Gartner (2001) and
Meta Group (2002) maintain that defining project objectives clearly and having metrics that

Business Performance Measurement (BPM) has a lot of branches in a wide variety of
disciplines, including accounting, economics, human resource management, marketing,
operations management, psychology and sociology. In the field of marketing, performance
measurement has not been developed all that much. In fact, it has been the target of criticisms
due to its short term orientation (Dekimpe and Haussens, 1995, 1999), its limited diagnostic
power (Day and Wensley, 1988), the lack of consensus in relation to the number of measures
and the subsequent difficulty for making comparisons (Clark, 1999; Ambler and Kokkinaki,
1997).

The reasons for this poor development of marketing accountability are the difficulties in
measurement which involves the assessment of the results derived from the implementation of

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different marketing strategies. One of these barriers is the complexity to isolate the effects of
a particular marketing strategy (Bonoma and Clark, 1998). Another one, is that those effects
are perceived, in most of the cases, in the long term (Dekimpe and Hanssens, 1995).

Nevertheless, it is very useful and neccessary to measure performance in order to evaluate the
result of the different marketing strategies. It lets reinforce those with positive results and
correct others not providing the expected benefits. Furthermore, it is said that what gets
measured, gets managed. According to Metrus Group (2003) there is considerable evidence of
strategic performance measurement on strategy execution and strategic performance. This
company carried out a study about the benefits of strategic performance measurement, finding
six reasons why strategic performance measurement is so powerful in improving business
performance: (1) measurement rapidly forges increased strategic agreement; (2) measurement
provides a common language to communicate strategy and key values; (3) measurement helps
forge alignment throughout the organization; (4) measurement accelerates the rate of
successful change; (5) measurement increases a company’s predictive power and early
warning capability; (6) measurement helps provide managers with a holistic perspective.


Ittner and Larcker, 1998b; Szymaski and Henard, 2001), customer loyalty (Dick and Basu,
1994), brand equity (Keller, 1998), employee equity (Amir and Lev, 1996; Srivastava,

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Shervani and Fahey, 1998) and profitability was proved, and subsequently this type of
measures started to have a great deployment.

Nowadays the increasing dynamic and competitive business environment demands holistic
measurement systems which provide the company with a complete “map” of different aspects
influencing the results of companies, in order to neutralize their weaknesses, reinforce the
strengthens and create new ones. In a CRM world, companies have a great amount of data
which can be transformed into useful information by easing strategic management and control
process. Managing this information in a systematic and dynamic way can yield a competitive
advantage.

According to Ambler, Kokkinaki and Puntoni (2002) the evolution of marketing metrics
seems to fit the following pattern:

- Little awareness regarding the necessity of using marketing metrics at top executive
level.
- Measurement systems based exclusively on financial metrics.
- Broad vision of performance measurement including non-financial metrics.
- Seeking some rationale(s) to reduce the number of metrics, about 25 or less (Unilever,
1998).

Performance measurement metrics can be classified into different categories: financial versus
non-financial; one-dimensional versus multi-criteria (Grabner-Kraeuter and Moedritscher,
2002); input, management and output measures (Clark, 1999); hard versus soft (Ang and
Buttle, 2002); tangible versus intangible.


quality/esteem; loyalty/retention; relative perceived quality.

In spite of academics think that non-financial metrics should leader performance
measurement, practitioners remain using predominantly classical ones. We can find the
explanation for this behaviour in the fact that these indicators are much easier to measure. In
addition, conventional methods have the advantage of being investment evaluation settings.
Their major drawback of evaluation is that they focus on the estimation of cash flows and
accounting criteria (Kim, Suh and Hwang, 2003). Nevertheless, traditional performance
systems do not provide a full understanding of the influences on profits. The major criticisms
to classical metrics are summarized in the following:

- Accounting metrics have a focus on the short-term and take little account of the value
to the firm of long-term customer preference, or the marketing investment which
created it (e.g. Ambler, Kokkinaki and Puntoni, 2002).
- They are not adequate for assessing investments whose benefits will be intangible,
indirect or strategic (e.g. Bukowitz and Petrash, 1997; Grembergen and Amelinckx,
2002).
- They only report functional processes (e.g. Ittner and Larcker, 1998a).
- They do not take into account the influence of marketing decisions on such variables
as inventory levels, working capital needs, and financing costs that need to be
managed for the well-being of the enterprise (e.g. Srivastava, 2004).
- They do not let aggregation from an operational level to a strategic one They just look
backwards, recording historical data so their prediction power is limited (e.g.
Chakravarthy, 1986; Ittner and Larcker, 1998a; Yeniyurt, 2003).
- They are not suitable for strategic decisions (e.g. Kaplan and Norton, 1992).
- The do not measure the value created (e.g. Lehn and Makhija, 1996).
- They provide little information on deviations (e.g. Ittner and Larcker, 1998a).
- There is a high number of metrics, so researchers should find some convergence in
order to describe more with less numbers (e.g. Frigo and Krumwiede, 2000; Kaplan
and Norton, 1992).