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Customer Value in an All-
Inclusive Travel Vacation Club:
An Application of the RFM
Framework
Shelly-Ann Lumsden a , Srikanth Beldona a & Alastair
M. Morrison b
a University of Delaware,
b Purdue University, West Lafayette, IN, USA
Available online: 11 Oct 2008
To cite this article: Shelly-Ann Lumsden, Srikanth Beldona & Alastair M. Morrison
(2008): Customer Value in an All-Inclusive Travel Vacation Club: An Application of the
RFM Framework, Journal of Hospitality & Leisure Marketing, 16:3, 270-285
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Journal of Hospitality & Leisure Marketing, Vol. 16(3) 2008
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270 doi:10.1080/10507050801946858
WHMM1050-70511541-0897Journal of Hospitality & Leisure Marketing, Vol. 16, No. 3, Mar 2008: pp. 0–0Journal of Hospitality & Leisure Marketi ng
Customer Value in an All-Inclusive
Travel Vacation Club: An Application
of the RFM Framework
Lumsden, Beldona, and MorrisonJournal of Hospitality & Leisure Marketi ng Shelly-Ann Lumsden
Srikanth Beldona
Alastair M. Morrison
ABSTRACT. In this study, the RFM (Recency, Frequency, and Mon-
etary) framework is applied as a method of distinguishing customer
value based on pre-purchase motivations of membership initiation in
an all-inclusive travel vacation club. Findings suggest that frequency
is the strongest predictor of supply side customer value in travel
vacation clubs, compared to recency and monetary value. Findings are
useful for a variety of travel firms in the complex travel-package
industry in the areas of customer segmentation, targeting, and market-
ing communications.
KEYWORDS. Recency, Frequency, and Monetary (RFM), perceived
customer value, travel vacation club
Shelly-Ann Lumsden, MS, and Srikanth Beldona, PhD, are affiliated with
University of Delaware.
Alastair M. Morrison, PhD, is affiliated with Purdue University, West
Lafayette, IN.
Address correspondence to: Srikanth Beldona, University of Delaware, 14
West Main Street, Newark, DE 19716 (E-mail: beldona@udel.edu).
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Lumsden, Beldona, and Morrison 271
INTRODUCTION
Astute marketers realize that it is easier and less expensive to get an
existing customer to buy again than it is to acquire a new one
(Schoenbachler, Gordon, Foley, & Spellman, 1997). Given this
premise of marketing, customer retention and targeting has become
paramount to the success of companies. A very common practice used
by database marketers is the recency, frequency, and monetary value
(RFM) of past responses to estimate the likelihood of a future
response (Colombo & Jiang, 1999) or to determine the firm’s most
valuable customers.
The context of this study is a membership-based travel vacation
club (TVC) in the United States. A travel vacation club plays an
important role in the travel industry by providing all-inclusive pack-
age tours to domestic and international destinations year-round.
Essentially, various tourism products and services are combined into a
single unit organized, sold, and managed by a single entity. Morrison
(2003) describes an all-inclusive package tour as a trip planned and
paid for in a single price in advance, covering important travel compo-
nents such as commercial transportation (flights, transfers, etc.),
accommodations, meals, and sightseeing. In the vacation travel indus-
try in the United States, there are several types of players, each with
unique value propositions to attract vacationers. The packaged
vacation club competes directly with all packaged and non-
packaged travel services because of the ready-to-serve nature of their
offerings.
Previous research specific to all-inclusive tours (Heung & Chu,
2000) identified important selection factors in relation to choosing a
travel agency for all-inclusive package tours. Specific to travel, the
RFM technique has been applied to outbound Taiwanese travelers,
although this has not been tied directly to profitability for the firm per
se (Wong, Chen, Chung, & Kao, 2006). The purpose of this study
therefore is to apply the RFM model as a method to distinguish value
for the firm, based on pre-purchase motivations of membership initia-
tion in an all-inclusive travel vacation club.
The study is guided by the following research questions: (1) based
on RFM, what group or groups of VTC members contribute the high-
est monetary value to the club?, and (2) which members, based on
motivations for membership initiation, are likely to remain loyal to the
club?
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272 JOURNAL OF HOSPITALITY & LEISURE MARKETING
REVIEW OF LITERATURE
Consumer marketing is necessary for customer acquisition and reten-
tion in today’s competitive marketing environment. Schoenbachler,
Gordon, Foley, & Spellman (1997) assert that marketing requires a shift
from the shotgun approach of mass advertising to a rifle approach, targeting
the most profitable existing customers and prospective new customers
who are most likely to purchase a product or service. With the informa-
tion revolution driven by the widespread use of computers and computer
networks, particularly the internet, it is now possible for companies to
gather a tremendous amount of information about their customers (Alencar,
Ribeiro, Ferreira, Schmitz, Lima, & Manso, 2006). This has given rise to the
concept of customer relationship management (CRM) in which companies
undertake to know and understand their customers’ preferences, spending
habits, and idiosyncrasies in order to serve them better. In addition, the avail-
ability and fairly low cost of computer-based analytic tools and decision
support systems make it much easier to mine data for a strategic marketing
advantage. One traditional technique of predicting customers’ purchase
behavior is the RFM model. The concepts underlying the RFM model are
easily mastered, even by marketers with little mathematical and statistical
background (Kahan, 1998; Alencar, et al., 2006).
Recency, Frequency, and Monetary Value
The RFM model is most commonly used for selection and segmenta-
tion in direct marketing (Bult & Wansbeek, 1995) and has proven very
effective (Wu & Lin, 2005) when applied to marketing databases. As the
model is easy and cost-effective, provided that customer and transactional
data are stored in an accessible electronic form, RFM can be a powerful
behavioral analysis technique (Kahan, 1998). Customers are segmented
according to three attributes of buying behavior–recency, frequency, and
monetary value. Recency is determined by the most recent purchase
made; frequency is the number of purchases made during a specific
period, and monetary value is the customer’s average spending with the
firm over a defined period. Companies want to be able to identify their
most valuable customers as well as determine to which customers they
should make an offer, and RFM is an effective way of analyzing a com-
pany’s customer database.
The underlying concept of the RFM framework is that customers who
have purchased recently are more likely to make more purchases than
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Lumsden, Beldona, and Morrison 273
those who have not; customers who purchased frequently are more likely
to purchase again, and those who spent the most money are likely to buy
again. It means that customers can be segmented into profitable and
unprofitable segments.
This model has been used extensively in improving the effectiveness of
direct mailings of catalogs and other marketing communications by deter-
mining the optimal mailing design (Vriens, Scheer, Hoekstra, & Bult,
1998). In fact, it is documented that this type of behavioral analysis
technique was first created accidentally by Sears Roebuck & Company,
who discovered that by inserting a catalog with an outgoing order, their
most recent customers were more likely to order again (Kahan, 1998).
Currently, catalogers assume that a mailing decision should be made
when the expected profit (or lifetime value) is positive or when the
expected profit exceeds a certain threshold (Gonul, Kim, & Shi, 2000).
Specific to travel, Wong et al. (2006) applied RFM to identify valuable
travelers using data mining techniques to determine demographics, buying
and decision-making behavior patterns, and destinations visited.
Kahan further notes that the RFM framework allows marketers to test
campaigns with smaller segments of customers, and that marketers can
direct larger campaigns only towards those customer segments that are
predicted to respond profitably. Furthermore, Schoenbachler et al. (1997)
assert that a low profit customer can easily become high profit with the
right marketing program. By reducing marketing efforts towards custom-
ers who are unlikely to make purchases, through RFM segmentation, the
overall financial results of a company’s marketing program is expected to
improve considerably (Alencar, et al., 2006). Given that customers can be
clustered into different segments in terms of value, appropriate marketing
strategies can be formulated to target each group of customers. According
to Chen, Wu, & Chen (2005), the RFM process can help decision makers
understand customer needs and adjust their marketing strategies accord-
ingly to seek maximum return with limited resources.
The RFM framework has been applied to several different products
and services from varying levels of complexity, and the values (R, F, M)
tend to be firm-specific and based on the nature of the products/services.
For instance, Chen et al. (2005) found that when applied to customer
value in a banking context, recency (the most recent purchase date) bears
no significant influence on the analysis of customer value in credit card
transactions. Frequency and monetary value were more important in this
context. In another recent study, using new customers of an online music
site, Fader, Hardie, & Lee (2005) found that for low levels of recency,
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274 JOURNAL OF HOSPITALITY & LEISURE MARKETING
customers with greater frequency were likely to have lower future
purchasing potential than customers with lower pre-purchasing rates.
There is no evidence of the application of RFM specific to the travel
context. In this study, RFM is applied to distinguish customer value based
on pre-purchase motivations of membership initiation in an all-inclusive
travel vacation club.
Perceived Customer Value
Another theoretical underpinning relevant to this study is that of per-
ceived customer value (PCV). On the supply side, organizations typically
assess customer value based on criteria such as tenure, amount of money
spent, and the frequency of purchases (Colombo & Jiang, 1999; Fader,
Hardie, & Lee, 2004). On the demand side, customer value is defined as
“the consumer’s overall assessment of the utility of a product based on
perceptions of what is received and what is given,” that is, a trade-off of
quality and price (Zeithaml, 1988, p.14). Although the concept often has
been defined as a trade-off of quality and price, several marketing
researchers posit that PCV is a more obscure and complex construct, in
which notions such as perceived price, quality, benefits, and sacrifice are
all embedded (Sinha & DeSarbo, 1998). Zeithaml (1988) further argues
that value is not clearly differentiated from quality and similar constructs
such as perceived worth and utility. However, other research has sug-
gested that while quality is an effective predictor of repurchase intentions
for new customers, the perceived value of products and services is the
most effective predictor of repurchase intentions for repeat customers
(Petrick, 2004) and competitive success (Buzzell & Gale, 1987). Per-
ceived Customer Value also has a temporal context wherein it exists
along various stages of the purchase process, namely pre-purchase, point
of use/experience, post-purchase and after use/experience (Woodall,
2003). This study focuses on applying RFM to PCV at the pre-purchase
stage.
While several researchers have identified various constructs of PCV,
Petrick’s (2002) SERV-PERVAL remains a distinctive categorization of
value from both monetary and non-monetary contexts of perceived value.
Petrick identified quality, emotional response, monetary price, non-monetary
(behavioral) price, and reputation as the dimensions of PCV in services.
Quality was operationalized as a consumer’s judgment about the overall
excellence of the service; emotional response, a descriptive judgment
regarding the pleasure derived from the service; perceived monetary
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Lumsden, Beldona, and Morrison 275
price, the price of a service as encoded by the consumer; reputation, the
perceived prestige or status of a service; and behavioral price, the time
and effort to search for service (Petrick, 2004). Behavioral price essentially
means convenience. Convenience is vital here because travel planning by
itself is a complex decision making process that involves a range of deci-
sions and sub-decisions (Jeng & Fesenmaier, 2002). The club provides
packaged vacations or tours that are planned and directly controlled by
the club itself. This level of control should be distinguished from bundled
vacations that are merely services from multiple players aggregated by an
intermediary. Therefore, convenience customers in this context are those
that seek shrink-wrapped vacations comprised of multiple services from
multiple players, but which are organized and managed by the operator
itself.
In a more specific context of PCV in a travel vacation club, Beldona,
So & Morrison (2006) discovered that there was a strong association
between convenience and the product price, choice, and social contexts of
membership in a TVC. Additionally, Beldona et al. (2006) highlighted the
important link between the vacations offered and their perceived value
within the TVC context, while simultaneously providing insights on
lesser value perceptions among those who joined for monetary reasons.
However, this study does not have ample past evidence to propose
hypotheses proposing consumption.
DATA AND METHODOLOGY
The data used for the study came from a survey of members belonging
to a private travel vacation club in the midwestern United States. 17,986
members of the club were randomly (simple random sampling) picked
from a computerized database of members. 2203, responses were
received, indicating an overall 12.25% response rate. Note that the survey
was conducted in two stages. Stage one of the data collection was done in
August of 2003 and followed by stage two in February of 2004.
The survey was administered on the web. Online surveying is an
emerging survey method wherein low response rates can be problematic
(Vehovar, Batagelj, Manfreda, & Zaletel, 2002). Although 50 to 60 per-
cent is considered as an acceptable response rate in survey research, a
more important criterion of a good sample is how representative are the
respondents of the target population being studied. This in turn will affect
how valid the results are (Lohr, 1999). Strategies suggested to deal with a
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276 JOURNAL OF HOSPITALITY & LEISURE MARKETING
relatively high non-response rate include following-up with non-respondents,
comparing respondents to the population, comparing early to late respon-
dents, “double-dipping” non-respondents, comparing respondents to non-
respondents, etc (Diem, 2002; Moore & Tarnai, 2002).
In double dipping, a random draw of non-respondents is done using an
alternative data collection technique than what was used originally the
survey such as calling by phone if the survey was originally conducted
through the Internet. Differences are then ascertained between original
respondents and those collected through the alternative technique (now
classified as non-respondents). The two pools of data are combined if
there are no differences. Alternatively, given that differences are found, a
weighted procedure is applied to correct for non-response bias.
In this study, we employed a combination of following-up with non-
respondents and comparing early to late respondents. Differences between
early and late respondents were evaluated based on socio-demographic fac-
tors such as gender, race, age, education, occupation, and income. Across
all these factors, no significant differences were found. Additionally, the
same analysis was replicated to evaluate differences between follow-up
respondents of the first and second stages. This is because evidence has
shown that late respondents are often similar to non-respondents (Moore &
Tarnai, 2002). Here too, chi-square analyses reflected no significant differ-
ences. Therefore, it can be inferred that the sample was a fair representation
of the target population.
To determine customer value propositions, club managers and the
researchers deliberated over the firm’s interpretations and existing aca-
demic literature pertaining to PCV. In the initial stages of questionnaire
development, the managers of the club were asked to develop a list of rea-
sons as to why potential travelers sought membership at their club. This
list of reasons was then reviewed using known theories, and subsequently
six major reasons were identified as to why travelers sought membership
at the club. These were convenience, packages offered, promotional offers,
family and friends, specific trips, and 10% discounts on allied airlines.
Convenience is a well known construct (Berry, Seiders & Grewal,
2002), and in the context of this club, prevails at the pre-purchase level,
wherein customers need not go through the complexities of the travel
planning process, and at the experiential level where customers have a
pre-determined schedule, organized transport, accommodations, a few
events and a tour guide. Vacation packages, as a value proposition, are an
adaptation of quality (Petrick, 2000; Sweeney & Soutar, 2001). More
specifically, vacation packages mean the type of destinations offered, the
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Lumsden, Beldona, and Morrison 277
breadth of choice, and to some extent, the quality of services offered during
the vacation. Family and friends is based on social value (Sweeney & Soutar,
2001) and specific trip is based on Sheth, Newman and Gross’s (1991) inter-
pretation of conditional or contingency benefits. Promotional offers and 10%
discounts on the allied airlines are based on monetary reasons (Zeithaml,
1988), and were combined into one group for analysis. An “other” option
was provided so as to capture other value types based on customers’ own
interpretations of value perceived in membership initiation. However, analy-
sis of these responses indicated that they were largely secondary in nature
(gifts, employee perks, etc.), and did not fall within the purview of the main
categories and were not substantial enough for statistical analysis.
The measurement of RFM was done using formulae suggested by Bult
and Wansbeek (1995). Recency was measured using a variable seeking as
to the year in which the member bought the most recent vacation. Fre-
quency was measured by dividing the number of vacations by the number
of years spent in the club. Monetary value was measured by calculating
the average spend per vacation. Analysis of Variance (ANOVA) was used
to determine differences between the five groups across monetary value.
Post-hoc tests were administered to determine the relative performance of
pre-purchase perceptions of value towards the club.
FINDINGS
Table 1 illustrates the descriptive statistics of the five groups used in the
study, namely convenience, vacation packages, social value, monetary
value and contingency. First, there were no significant differences based
on pre-defined age groups. Given that travel search and consumption is
dependent on the family lifecycle (Fodness, 1992) or age cohort (Beldona,
2005), it was decided to make three age groups. The first group was 34
years or younger and belonged to Generation X at large. Those between 35
and 49 years comprised the younger and middle age baby boomers. The
last group was 50 years or older and comprised older boomers and seniors.
At large, all groups had a relatively similar number of percentages of
respondents in the 35 to 49 category, which comprises early and middle
aged boomers. However, the convenience group had a relatively larger
proportion of respondents in the over 50 category of older boomers and
seniors. Also, this group (convenience) had the lowest proportion (3.8%)
of respondents in the Generation X (under 34) group. This was followed
by the monetary (6.8%) and vacation packages (7.0%) groups.
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278
TABLE 1. Descriptive statistics (N = 2,203)
Variables Convenience
(513)(%) Vacation
Packages (485)(%) Social
(353)(%) Monetary
(471)(%) Contingency
(238)(%) F or χ2
Age
<=34 3.8 7.0 15.1 6.8 10.2 χ2: 28.06***
35–49 35.3 36.4 35.9 38.7 36.6
>=50 60.8 56.7 49.0 54.4 53.2
Gender
Male 28.7 47.0 39.4 43.0 32.2 χ2: 28.05***
Female 71.3 53.0 60.6 57.0 67.8
Marital Status
Married 75.4 70.6 73.6 82.4 74.7 χ2: 8.86
Other 24.6 29.4 26.4 17.6 25.3
Income
<= 100,000 48.3 44.5 57.0 41.9 39.5 χ2: 9.90***
> $100,000 51.7 55.5 43.0 58.1 60.5
Education
Associate degree and lower 37.8 37.9 40.6 35.6 40.0 χ2: 1.94
Bachelor degree and higher 62.2 62.1 59.4 64.4 60.0
Type of Membership
Single 21.0 16.1 27.9 15.4 27.8 χ2: 38.12***
Family W children 29.4 35.5 37.1 40.7 26.3
Family W/O children 49.7 48.5 35.1 43.9 45.9
***p < 0.001.
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Lumsden, Beldona, and Morrison 279
When it came to gender, the sample was skewed towards females with
most groups reporting more females (61.1%) than males (38.9%).
According to managers, this is not related to the composition of the club’s
membership. However, this may be a reflection of the evolving role of
women in the travel decision-making process (Litvin, Xu & Kang, 2004)
as well as the fact that females demonstrate more involvement in the
travel purchase process (Josiam, Kinley & Kim, 2005). Also, females
appear to be particularly influential in the purchase tasks such as information
search, information processing, and determination of a specific package
holiday in the purchase of family holidays (Koc, 2005). Therefore, they
are more likely to serve as representative interfaces of their family units
for the purpose of interacting with the club.
Further analysis was done using three way cross-tabulations to evaluate
gender differences based on whether participants were single or married. Here
too, statistically significant gender differences were present for both males
and females. Therefore, for this particular instance, findings suggest that the
interface process (persons interacting with the club on behalf of the family or
self for leisure needs) is female dominant because 79.8% of the sample com-
prised married units. Past research has also provided evidence of this fact.
One will also note that the convenience group has a relatively larger
proportion of females (71.3%) compared to all other groups. This is
closely followed by the contingency group (67.8% female) and the social
group, which had 60.6% female respondents. The group with the relative
smallest proportion of females was the vacation packages group (53%
female). There were no significant differences between groups when it
came to marital status. There was statistical significance of association
when it came to income and PCV at the pre-purchase stage. Note that the
median income of the sample was at a high $100,000. Most notably, the
contingency and monetary groups had relatively larger proportions of
respondents above the $100,000 per annum bracket. Compared to every
other group, the social group was the only one that had more respondents
below the $100,000 per annum bracket.
There were no differences between the five groups when it came to
education. At an aggregate level, 61.9% of the sample had a bachelor’s
degree or higher and the remaining 38.1% had an associate’s degree or
less. Specific to the type of membership, the sample had a relatively large
proportion of families without children (44.8% of the sample). However,
the social group was least represented here with only 35.1%, compared to
all other groups which had percentages above 40%. Furthermore, the con-
venience group had the highest percentages of families without children
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280 JOURNAL OF HOSPITALITY & LEISURE MARKETING
(49.7%) closely followed by the vacation packages group (48.5%). In the
case of single memberships, the social (27.9%) and the contingency
groups (27.8%) had relatively higher percentages of respondents.
ANOVA Findings
One of the key assumptions of ANOVA is a normally distributed
dependent variable (Hair, Anderson, Tatham, & Black, 1998). Two key
measures to test normality are skewness and kurtosis. Skewness refers to
the asymmetry or the tilt of frequency or probability distributions, and
kurtosis is the peakedness of a distribution (Garson, 2006). Both skewness
and kurtosis figures should be within the zone of acceptance (−2 to +2)
(Garson, 2006). A logarithmic transformation was done on all three vari-
ables, which resulted in both skewness and kurtosis figures within the
acceptable range for all three variables.
Table 2 outlines the ANOVA findings across the five groups based on
three random sample draws from the data. Large samples are a problem
wherein even very weak relationships may be statistically significant, a
phenomenon also known as substantive significance (Garson, 2006). To
reaffirm the results because of the large sample size, three smaller sam-
ples with approximately 25% of the original number of cases were drawn
and ANOVA analysis was done on these sub-samples. There were statis-
tically significant differences in frequency and recency components of
RFM and no differences when it came to monetary value. The same dif-
ferences (overall F as well as post hoc comparisons) were prevalent in the
analysis of these sub-samples when compared with the larger sample.
TABLE 2. Recency, frequency, and monetary value
one-way ANOVA findings
Factor Sample 1 Sample 2 Sample 3
Recency F = 3.15* F = 4.70*** 3.84**
Df (4, 265) Df (4, 299) Df (4, 304)
Frequency 17.66*** 12.82*** 6.62***
Df (4, 326) Df (4, 368) Df (4, 347)
Monetary 1.10 1.19 1.59
Df (4, 265) Df (4, 299) Df (4, 304)
*p < 0.05, **p < 0.01, ***p < 0.001.
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Lumsden, Beldona, and Morrison 281
Given this similarity across samples, post hoc results from sample 1 are
summarized below.
1. The convenience group reported significantly lesser values for
recency of purchase when compared with the monetary (p < .001)
social (p < .01) and vacation packages (p < .05) groups.
2. No other differences were present between the remaining groups
when it came to recency of purchase.
3. The monetary group reported significantly lesser frequency of pur-
chases values when compared to convenience (p < .001), vacation
packages (p < .001), contingency (p < .01) and the social (p < .05)
groups.
4. The convenience group reported greater frequency of purchases
compared to the social (p < .05) group.
DISUSSION AND IMPLICATIONS
The study provides a good guide to the main features of the RFM con-
cept and segmenting members by perceived value at the pre-purchase
level. This tiered perspective of value provides significant marketing
implications for tour operators and travel agencies selling all-inclusive
packages. Findings indicate distinctive differences between groups across
recency and frequency. For instance, the monetary group reported
relatively more recent purchases compared to the other groups, although
significant differences were prevailing only with the convenience group.
Alternately, the same (monetary) group reported significantly lesser fre-
quency of purchases when compared with the remaining four groups.
This is especially the case with the contingency group, which typically
draws members who are in it for the short term of just one trip.
One would have expected the convenience group to demonstrate sig-
nificantly greater frequency of purchases compared to other groups given
that their tenure with club is the highest (Beldona, 2004), but this was not
the case. In general, the convenience members are relatively older and
have more disposable time. This (convenience) group reported signifi-
cantly higher levels of frequency when compared only with the social
group.
No differences were evident between the groups when it came to mon-
etary value. This could be because of the limited variability in the price
points of packages offered at the club. This then definitively suggests that
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282 JOURNAL OF HOSPITALITY & LEISURE MARKETING
frequency is the strongest indicator of supply side value in the TVC sector
of the travel industry. However, one is likely to believe that this will differ
from one firm to another, as greater variability in price points of package
offerings is likely to enhance the importance of monetary value. Recency
is important too, because it shows the distinctive level of activity by the
consumer.
Applying these results to any intermediary selling vacations which has
a CRM program like Expedia, Travelocity, etc. (albeit these are not
organized and operated as a TVC), where one is likely to contend that fre-
quency, as well as monetary, are going to be significant predictors of sup-
ply side customer value. Importantly, the application of the RFM
framework in the travel industry is firm-specific, depending upon the kind
of products a travel/tour operator provides, ranging from simple to more
complex ones, packaged or non-packaged. Findings of this study should
be viewed within the context of complex pleasure travel products at large.
However, the tiered perspective of value does provide a framework for
assisting club operators and travel agencies selling all-inclusive packages
because it identifies profitable segments based on customer value propo-
sitions. Targeted promotions aimed at profitable segments driven largely
by their value propositions can go a long way in building more sustain-
able customer relationships. Additionally, tour operators can drive devel-
opment and delivery of tours for more profitable segments.
While tour club operators should exert much effort in marketing to the
“convenience” segment, these members are likely to remain loyal to the
club’s offerings of all-inclusive packaged services which may ultimately
lead to greater monetary value to the club over longer periods of time.
Marketing communications can be refined to target convenience as one of
the major benefits provided by these clubs. At the product level, they can
re-examine the various contexts of convenience offered in order to better
target convenience and non-convenience segments. Convenience based
services can be segmented based on the pre-purchase, point of consump-
tion, and post-experience stages of consumption.
Another key finding suggests that customers with monetary motiva-
tions for membership initiation may be adding to costs of customer acqui-
sition while not delivering the required returns in terms of revenues. The
evaluation of efforts in this context is advised because of their low scores
across both recency and frequency dimensions of value fore the firm. At
the same time, these members should not be ignored. As Schoenbachler
et al. (1997) assert, a low profit customer might easily become high profit
with the right marketing program.
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Lumsden, Beldona, and Morrison 283
As a recommendation, tour club operators may also introduce these
pre-purchase value drivers on their membership registration forms,
requiring new members to select the primary reason for joining. Upon
capturing this information into their database, club operators can
determine the best marketing approach for each segment. This will
help to design and implement more efficient promotional efforts,
which will drive customer loyalty, customer acquisition, and ulti-
mately, profitability.
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