Influencing Consumer Decisions Through Personalization.

Abstract

Web-based technologies have enabled companies to reach out to their customers and influence decision making in new and different ways. Personalization has shown promise as an approach to attracting an individual's interest and influencing their decision making, and it can be effectively delivered over the Internet. New technologies allow a rich mix of media, interconnected streams of social conversation between users, and one-on-one interaction between the user and the technology delivering the message. These characteristics can be used to influence a decision maker based on research suggesting that consumers will respond more favorably to individualized messages than generalized ones. This paper focuses on socio-technical aspects of personalization by addressing human and technical issues in the implementation and impact of personalization. We provide a Understand-Measure-Deliver theory of personalization and report a case study of a global company that successfully used personalization to influence consumer decisions in the tourism industry. The findings are that customization based on relevant data provides a personalized experience; customers become product designers and product testers with Web 2.0 technologies; and interaction between a human and the technology amplifies user experience.

Full text

REFERENCE: Phillips-Wren, G. and Wygant, J. (2010). Influencing
consumer decisions through personalization. Bridging the Socio-Technical
Gap in Decision Support Systems, Proceedings of 15th IFIP WG8.3 International
Conference, (A. Respicio, F. Adam, G. Phillips-Wren, Teixeira, C, Telhada, J.,
eds.), ISBN 978-1-60750-576-1, 152-162.
Influencing Consumer Decisions Through
Personalization
Gloria PHILLIPS-WRENa,
1
and Jeffrey WYGANT b
a Loyola University Maryland, Baltimore, MD USA
b Euro RSCG Discovery, Baltimore, MD USA
Abstract. Web-based technologies have enabled companies to reach out to their
customers and influence decision making in new and different ways.
Personalization has shown promise as an approach to attracting an individual’s
interest and influencing their decision making, and it can be effectively delivered
over the Internet. New technologies allow a rich mix of media, interconnected
streams of social conversation between users, and one-on-one interaction between
the user and the technology delivering the message. These characteristics can be
used to influence a decision maker based on research suggesting that consumers
will respond more favorably to individualized messages than generalized ones.
This paper focuses on socio-technical aspects of personalization by addressing
human and technical issues in the implementation and impact of personalization.
We provide a Understand-Measure-Deliver theory of personalization and report a
case study of a global company that successfully used personalization to influence
consumer decisions in the tourism industry. The findings are that customization
based on relevant data provides a personalized experience; customers become
product designers and product testers with Web 2.0 technologies; and interaction
between a human and the technology amplifies user experience.
Keywords. Personalization, decision making, socio-technical, Web 2.0
Introduction
Web-based technologies have enabled companies to reach out to their customers and
influence decision making in new and different ways. Personalization has shown
promise as an approach to attracting an individual’s interest and retaining their
attention, and it can be effectively delivered over the Internet (Mussi, 2003; Kennedy,
2008). Personalization is the process of obtaining data about individual consumers,
converting that data into actionable information and knowledge, and then into wisdom
by matching characteristics of the product with knowledge about the individual
(Kennedy, 2008). It can range from highly individualized approaches based on detailed
information about an individual, to more generalized group preferences based on
clustering methods, with the approach dependent on the fidelity of the available
information and the flexibility of the delivery system (Picariello and Sansone, 2008).
Web 2.0 offers technologies that allow a rich mix of media, interconnected streams of
social conversation between users, and one-on-one interaction between the user and the
technology delivering the message. These characteristics can be used to influence a
1
Corresponding Author. Sellinger School of Business and Management, Loyola University Maryland,
4501 N. Charles Street, Baltimore, MD 21210 USA; 410-617-5470; gwren@loyola.edu

REFERENCE: Phillips-Wren, G. and Wygant, J. (2010). Influencing
consumer decisions through personalization. Bridging the Socio-Technical
Gap in Decision Support Systems, Proceedings of 15th IFIP WG8.3 International
Conference, (A. Respicio, F. Adam, G. Phillips-Wren, Teixeira, C, Telhada, J.,
eds.), ISBN 978-1-60750-576-1, 152-162.
decision maker based on research suggesting that consumers will respond more
favorably to individualized messages than generalized ones (Tam and Ho, 2006).
Socio-technical issues in this context involve obtaining information from users that can
be used for personalization, identifying relationships between technology factors such
as presentation style and content for a particular decision maker, and developing a
system that can be maintained by content providers who may not be technically
specialized.
A number of studies have reported that personalization delivered over the Web can
influence a decision maker (see, for example, Tam and Ho, 2006; Kennedy, 2008).
However, there appears to be a gap in research on socio-technical aspects of
personalization. Mackrell, Kerr and von Hellens (2009) summarized recent
perspectives on decision support systems (DSS) research by stating that “the relevance
of DSS research would improve by increasing the number of case studies, especially
interpretive case studies to help reduce the gap between research and practice … [and]
the academic rigour of DSS research would improve by broadening the reference
theory foundation from its extant narrow base … to consider perspectives ‘beyond the
technical’” (p. 143). This paper responds to the call for relevant case studies that
demonstrate application of decision making theories in actual implementations.
We focus on clients and users by addressing human and technical issues in the
implementation and the impact of personalization. We report a case study of a global
company that successfully used personalization in their website marketing efforts to
influence consumer decisions. Our goal is to learn from the case rather than attempting
to generalize the analysis, referred to by Adam, Doyle and Sammon (2008) as an
intrinsic case study. We first review the literature on personalization in section 2. In
sections 3 and 4 we discuss our research design and describe the company’s
personalization efforts. We then discuss observations and conclusions related to socio-
technical issues arising from the case in the final sections of the paper.
1. Personalization Process and Effect on Decision Making
1.1. Personalization Process
Personalization “tailors certain offerings (such as content, services, product
recommendations, communications, and e-commerce interactions) by providers (such
as e-commerce Web sites) to consumers (such as customers and visitors) based on
knowledge about them, with certain goal(s) in mind” (Adomavicius and Tuzhilin,
2005). These techniques are information intensive and require a fast response to the
consumer within the context of the decision problem to capitalize on the initial interest
and attention of the person.
Personalization is an iterative process that has three theoretical stages in the
understand-deliver-measure cycle (Adomavicius and Tuzhilin, 2005). In the first phase
the provider attempts to understand consumers by collecting as much information about
them as possible and synthesizing it to produce knowledge that can be acted upon. The
second step is to deliver personalized messages or offerings based on a deep
understanding of the consumer. The third step is to measure the impact in order to
identify deficiencies and provide feedback for improvements. When one cycle is
complete, another cycle can begin with improved personalization techniques.

REFERENCE: Phillips-Wren, G. and Wygant, J. (2010). Influencing
consumer decisions through personalization. Bridging the Socio-Technical
Gap in Decision Support Systems, Proceedings of 15th IFIP WG8.3 International
Conference, (A. Respicio, F. Adam, G. Phillips-Wren, Teixeira, C, Telhada, J.,
eds.), ISBN 978-1-60750-576-1, 152-162.
Figure 1. Personalization Process Model
(based on Adomavicius and Tuzhilin, 2005).
1.2 Effect on Decision Making
Research suggests that delivering personalized content with the Web can influence a
user’s decision making (Tam and Ho, 2006). The reason for an enhanced response to
individualized messages continues to be an area of debate. Kuiper and Rogers (1979)
proposed the idea of “the self [as] an important agent in the processing of personal
information … [serving] as an abstract cognitive structure that contains both general
traitlike entries and some specific behavioral exemplars or instances. This memory
structure is active during the input and interpretation of self-related information and
provides a degree of ‘meaning’ or embellishment to the incoming information. The self
can be seen to act as a hook or interpretative frame for the encoding of personal data”
(p. 511).
Kircher et al. (2000, 2002) used functional Magnetic Resonance Imaging to
investigate cerebral activation while subjects processed faces and trait words related to
their self and to non-self. The results suggested that there was a reaction time
advantage in self processing, and that there were both common and differentiated brain
areas involved in the two processing conditions. The differentiated areas were in areas
previously correlated with awareness of one’s self.
Tam and Ho (2006) focused on the effectiveness of Web personalization with two
mediating factors: self-reference and content relevance. Self-referent stimuli “were
found to attract more attention, enable users to create preference structures faster, and
bias the decision outcome” (p. 885). Content relevance was consistent with previous
research that shows that users recall content that is relevant to their goal, and there is an
interaction effect between personalization and content relevance. Perhaps surprising,
they found an insignificant impact of self-referent content on recall, implying that
decision makers did not recall personalized content better than generalized content.

REFERENCE: Phillips-Wren, G. and Wygant, J. (2010). Influencing
consumer decisions through personalization. Bridging the Socio-Technical
Gap in Decision Support Systems, Proceedings of 15th IFIP WG8.3 International
Conference, (A. Respicio, F. Adam, G. Phillips-Wren, Teixeira, C, Telhada, J.,
eds.), ISBN 978-1-60750-576-1, 152-162.
The suggestion is that web developers and marketers should consider the intended role
of personalization, recall versus decision influencer, in their strategy.
2. Research Design
Over a period of five years we carried out a case study of a large global marketing
company that implemented Web personalization as a means of achieving quantifiable
impact on consumer decision making. We carried out multiple interviews with
managers involved in the project, observed users interacting with the technology,
documented modifications to the system as a result of user input, and used publically
available documents to give an in-depth look at the socio-technical issues involved in
personalization approaches. Although there are a number of studies addressing the
concept and theory of personalization in Web-enabled applications, we found little
research on the human factors involved in developing, maintaining and using these
techniques. We will refer to these factors as socio-technical in nature.
This research is primarily descriptive, and the case study is exploratory. Following
Yin (1989) and Stake (1995), we developed an initial framework for the study and
focused on the case specifically to maximize learning about the human and technical
considerations for personalization in a Web-enabled application rather than
determining the typicality of the case.
3. Euro RSCG Discovery
Euro RSCG Worldwide is a global integrated marketing company specializing in
advertising, digital, marketing services, healthcare, PR and corporate communications.
It has offices in 75 countries with 233 offices around the world (Euro RSCG, 2009).
Euro RSCG Discovery is the associated analytics, customer relationship management,
and behavioral marketing agency network. The agency combines research in
behavioral, attitudinal and lifestyle data to develop actionable insights that help clients
build loyalty, increase share, and create personal connections to their brands. Clients
include large multi-national companies including Diageo, IBM, Liberty Mutual
Insurance, Sprint and Volkswagen. The agency has offices in Chicago, Illinois;
Baltimore, Maryland; Mineola, New York; Richmond, Virginia; and Wilton,
Connecticut.
Euro RSCG Discovery was hired by the Bermuda Department of Tourism (BDOT)
to reverse a significant decline in the island’s travel and tourism industry. The island
of Bermuda, which had once welcomed royalty and presidents, had been facing a 10-
year decline in their tourism industry due to increased price competition from other
destinations and the island’s growing reputation as a destination that was solely for
honeymooners and elderly vacationers. As a result, the Bermuda Department of
Tourism hired Euro RSCG Discovery to increase call volume to 1-800-BERMUDA,
boost web traffic, and increase prospect conversion.

REFERENCE: Phillips-Wren, G. and Wygant, J. (2010). Influencing
consumer decisions through personalization. Bridging the Socio-Technical
Gap in Decision Support Systems, Proceedings of 15th IFIP WG8.3 International
Conference, (A. Respicio, F. Adam, G. Phillips-Wren, Teixeira, C, Telhada, J.,
eds.), ISBN 978-1-60750-576-1, 152-162.
Before working with Euro RSCG Discovery, BDOT’s marketing efforts consisted
of general awareness advertising and a generic inquiry fulfillment direct mail package.
The same promotional materials were sent to every prospect, regardless of their reasons
for visiting the island, the seasonality of their visit, or the gateway city from which they
were traveling. The travel market is highly competitive, and the customer is faced with
many choices and multiple sources of information. In such markets, differentiation
techniques were needed to make BDOT products attractive to consumers.
3.1 The Business Case – Leveraging Under-Utilized Assets
Euro RSCG Discovery implemented a consumer personalization strategy that was data-
driven and referred to as a Dynamic Marketing Environment (DME). Although the
DME required significant upfront development costs, it helped BDOT leverage two
valuable and under-used marketing assets: 1) a responder database, which was
comprised of potential visitors who had called 1-800-BERMUDA or visited
bermudatourism.com; and 2) a visitor database, which they had compiled from
completed immigration cards. These two target audiences received dynamically
generated, personalized communications that spoke to each prospect’s specific vacation
needs, aspirations, and purchase histories. This shift in communication strategy would
ultimately offer three critical advantages for BDOT:
 It would allow BDOT to create personalized content and relevant offers for each
potential visitor. This allowed Bermuda to set itself apart from competing islands
by presenting each prospect with a uniquely personal Bermuda vacation offering.
 It would enable BDOT to convert a higher percentage of prospects into visitors by
engaging them in a structured and personalized conversion program. Previously,
these leads, which were acquired through costly television campaigns, received
only one piece of communication. Prospects who didn’t visit the island were
simply abandoned.
 It would build repeat visitation and greater lifetime value for each customer by
enabling BDOT to communicate with each past visitor in a personal context.
3.2 Implementation: Bermuda’s Dynamic Marketing Environment (DME)
3.2.1 First Step in Personalization Process: ‘Understand’
The first step in a personalization process as shown in Figure 1 is to ‘Understand’ the
customer. The DME process began with lead generation from a variety of sources (see
Figure 2) to ensure relevance which was identified as a mediating factor (Tam and Ho,
2006). These leads were filtered and focused into a database that were analyzed and
mined to produce highly granular information for potential visitors to Bermuda.

REFERENCE: Phillips-Wren, G. and Wygant, J. (2010). Influencing
consumer decisions through personalization. Bridging the Socio-Technical
Gap in Decision Support Systems, Proceedings of 15th IFIP WG8.3 International
Conference, (A. Respicio, F. Adam, G. Phillips-Wren, Teixeira, C, Telhada, J.,
eds.), ISBN 978-1-60750-576-1, 152-162.
Figure 2. Process flow diagram for the Dynamic Marketing Environment.

REFERENCE: Phillips-Wren, G. and Wygant, J. (2010). Influencing
consumer decisions through personalization. Bridging the Socio-Technical
Gap in Decision Support Systems, Proceedings of 15th IFIP WG8.3 International
Conference, (A. Respicio, F. Adam, G. Phillips-Wren, Teixeira, C, Telhada, J.,
eds.), ISBN 978-1-60750-576-1, 152-162.
Figure 3. Sample Web presence for the Figure 3. Sample Web presence for t
Figure 3. Sample web presence for the Dynamic Marketing Environment.

REFERENCE: Phillips-Wren, G. and Wygant, J. (2010). Influencing
consumer decisions through personalization. Bridging the Socio-Technical
Gap in Decision Support Systems, Proceedings of 15th IFIP WG8.3 International
Conference, (A. Respicio, F. Adam, G. Phillips-Wren, Teixeira, C, Telhada, J.,
eds.), ISBN 978-1-60750-576-1, 152-162.
3.2.2 Second Step in Personalization Process: ‘Deliver’
In the second step, ‘Deliver’, various communication strategies were employed to
target specific interests and preferred communication modes of potential client.
Examples from the website are shown in Figure 3. Digitally Printing Print-On-Demand
(POD) Direct Mail Efforts allowed over 11,000 possible combinations of text and
graphics to deliver customized inquiry fulfillment communications.
Over eight years, the website evolved from brochure-ware into an interactive and
transactional site using Web 2.0 technologies. Visitors could access web-cams to take
virtual tours of golf courses, museums and other places of interest, make reservations
for on-island activities such as golf or swimming with dolphins, and check water
temperatures for diving. In addition, online booking functionality and vacation
packages made the purchasing a Bermuda vacation simple and efficient.
A particularly target group was repeat visitors. The first communication intended to
create repeat visitors to Bermuda was delivered within days of the traveler’s return
home. Each visitor received a thank you mailing from the Minister of Tourism. This
mailing directed visitors to take an online survey about their recent trip. This data was
then appended to the visitor’s file for use in remarketing efforts. Subsequent efforts
included an electronic newsletter and follow-up communications leading up to the
anniversary of the visitor’s last trip.
3.2.3 Third Step in Personalization Process: ‘Measure’
The third step in the personalization process is ‘Measure’, and a continual cycle of
assessment and refinement was adopted as shown in Figure 1 as a feedback loop. A
comprehensive set of measurements and metrics were used.
 In spite of the customized nature of the POD Direct Mail Effort fulfillment,
material costs dropped by 38% over the traditional “pick-and-pack”
fulfillment response.
 In-home delivery dropped from an average of seven days to an average of
three days.
 Since each brochure was created on an as-needed basis, BDOT incurred no
inventory costs for storing printed materials, and materials could be updated
regularly to accommodate changes. For example, changes in phone numbers
for hotels or scuba diving shops could be made in minutes.
 The repeat visitor effort generated a 27% response rate.
 The sum of these efforts reduced the time between visits and helped increase
the revisit rate of the island to 48%.
 During the eight years of DME development and use, the average length of
stay during Peak Season increased 8%.
 Visitor expenditures (on a per visitor basis) during Peak Season increased
11%.
 Leads sourced through 1-800-BERMUDA resulted in a prospect conversion
rate of 6.3% and a Return on Investment of 2,940%.
 Remarketing efforts lifted the conversion rate an additional 5.4%.
 Personalized inquiry fulfillment lifted conversion rates 7.8% over the previous
generic inquiry fulfillment mailing.
 Revisit rates climbed to 48%, second only to Maui among travel and tourism
destinations.

REFERENCE: Phillips-Wren, G. and Wygant, J. (2010). Influencing
consumer decisions through personalization. Bridging the Socio-Technical
Gap in Decision Support Systems, Proceedings of 15th IFIP WG8.3 International
Conference, (A. Respicio, F. Adam, G. Phillips-Wren, Teixeira, C, Telhada, J.,
eds.), ISBN 978-1-60750-576-1, 152-162.
3.3 Socio-Technical Issues
Attitudes toward, and maintenance of, the DME presented challenging socio-technical
problems. The BDOT organization was non-technical and not trained in using
advanced technology. Yet much of the content needed for personalization needed to be
refreshed and updated continually by expert providers who did not have technical
training. To overcome the lack of technical knowledge, simple logistics were needed
for a sophisticated system.
To aid in the adoption of the platform, Euro RSCG made the DME easy and
efficient to update by BDOT staff members who had never been exposed to this level
of technology (see Figure 3):
(1) The call center provided software screens for the customer service representatives,
which communicated with the central database and became integrated into the DME.
The Call Center scripts were updated dynamically based on the caller's needs and could
be updated by the BDOT staff without a programmer’s assistance. This allowed
Bermuda to adjust their travel offers and island information to react to market demands.
(2) The automated e-mail marketing program enabled the Tourism staff and Euro
RSCG Discovery to create emails for any segment of the customer database, adding
words, text and graphics to create marketing emails. These emails were part of an
ongoing Touchpoint marketing plan, which was based on the consumer's preferences
and their intended travel dates. The automated system also interacted with the Call
Center to allow outbound telemarketing calls to be part of the Touchpoint marketing
plan.
(3) The calendar of events allowed visitors to search events by date and/or topic. The
tourism staff kept the calendar up-to-date, providing visitors with a valuable tool to
plan an exciting and memorable visit to the island.
(4) A variety of e-mail and web-based communications and alerts were produced
through the website and centralized database. E-newsletters were produced on an
ongoing basis and were delivered to various segments of the customer database based
on interests. Web-Updates were alerts produced by the website when special marketing
offers were updated on the website by content providers. This allowed customers to
be updated on airfare specials and other travel offers. E-Postcards allowed visitors to
produce and e-mail their own postcards to friends and families before, during, or after
their trip, and create a valuable word-of-mouth marketing medium.
4. Conclusions and Limitations
We have provided support for the theoretical process of personalization - Understand,
Deliver, Measure – in a real setting. Associated socio-technical issues included
developing ways that content providers and consumers with little technical expertise
could interact with a sophisticated system. The Euro RSCG Discovery case provides
deep knowledge about the ways that personalization can influence decision makers,
consistent with theories of the self as an interpretative frame. Our findings are
consistent with Tam and Ho (2006) who found in a laboratory setting that personalized
web services attracted more attention, enabled users to more quickly create preference
structures faster, and biased the decision outcome.
The DME case study suggests a refinement of the Personalization Process Model
shown in Figure 1. Customers created content and products in the Web 2.0

REFERENCE: Phillips-Wren, G. and Wygant, J. (2010). Influencing
consumer decisions through personalization. Bridging the Socio-Technical
Gap in Decision Support Systems, Proceedings of 15th IFIP WG8.3 International
Conference, (A. Respicio, F. Adam, G. Phillips-Wren, Teixeira, C, Telhada, J.,
eds.), ISBN 978-1-60750-576-1, 152-162.
environment that became a feedback loop. An area of future study is to incorporate
customer involvement in the theoretical model of personalization. Other findings
include:
Customization based on relevant data provides a personalized experience. The
DME allowed Bermuda to set itself apart from other islands with similar product
offerings by delivering a personal vacation experience, beginning with the consumer’s
first interaction with the island.
Customers become product designers and product testers with Web 2.0 technologies.
The DME invited prospects to play varying roles and enjoy varying experiences. The
Bermuda DME turned prospective visitors into product designers and product testers as
suggested by Nambisan and Nambisan (2008). By choosing own their interests, hotel
preferences, gateway cities, and other variables, each prospect was designing his or her
own unique island experience.
Interaction between a human and the technology amplifies user experience. By
taking virtual tours, prospects could sample Bermuda’s golf courses, accommodations,
and historic sites – getting a taste of the island experience before booking a trip. The
online presence, in particular, created a pragmatic experience for the prospective visitor,
by providing relevant, detailed information on a variety of subjects. For example,
scuba enthusiasts could visit the website and find average water temperatures for each
season of the year. Fisherman could determine which fish were in season at any given
time. Birdwatchers could visit the “birding” section of the site and listen to recorded
calls from indigenous and migratory birds. In the case of Bermuda tourism, the
interaction between a human and the technology reinforced an inherently hedonic
experience, based on the recreational nature of the product.
There are, of course, limitations to our study. Since the research involves a live case
over a long time period, it was not possible to control all variables that could
potentially influence the output measurements. The measures given to determine the
effect of personalization in this case are material costs and inventory costs associated
with advertising, repeat visitor response rate, time between visits, revisit rate, average
length of stay, prospect conversion rate, return on investment, and visitor expenditures.
Although we have presented a large number of potential metrics to validate the effect
of personalization, it is possible that factors such as increased market penetration
contributed to the changes in output measures that we observed.
5. Summary
The Euro RSCG Discovery experience with the Dynamic Marketing Environment
empirically supports theory on the effect of personalization on decision making and
provides insight into the process of personalization, its implementation, and metrics
that can be used to assess its effectiveness. The case shows that personalization can be
used to influence decisions in product choice by shaping each customer’s brand
experience from the initial point of contact with the product through usage and
afterwards. The findings suggest an improvement to the theoretical model by including
the effect of consumer co-creation of content in the model.

REFERENCE: Phillips-Wren, G. and Wygant, J. (2010). Influencing
consumer decisions through personalization. Bridging the Socio-Technical
Gap in Decision Support Systems, Proceedings of 15th IFIP WG8.3 International
Conference, (A. Respicio, F. Adam, G. Phillips-Wren, Teixeira, C, Telhada, J.,
eds.), ISBN 978-1-60750-576-1, 152-162.
Socio-technical issues discussed in this paper primarily involve users’ attitudes
toward, and interaction with, the sophisticated system needed to deliver personalized
services. The case illustrates that an organization resistant to technology can adopt and
use technology if they are given tools that are perceived as valuable and simple to use,
similar factors in the Technology Acceptance Model (Davis, 1989). Providers need to
modify and update content to provide a rich set of information that can be used to
personalize a product, and consumers need access to advanced technologies that enable
aspects of personalization. The organizations in our study found that delivering
personalization with Web 2.0 and emerging 3.0 technologies can simultaneously
influence consumer decisions and reduce costs.
6. Acknowledgements
We would like to thank Euro RSCG Discovery for their participation and cooperation.
We would also like to thank the reviewers for their suggestions which improved the
quality of the paper.
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