A FRAMEWORK OF WEB ANALYTICS
Deploying the Emergent Knowledge of Customers
to Leverage Competitive Advantage
Claudio Luis Cruz de Oliveira
Production Engineering Dept. of Polytechnic Engineering School, University of São Paulo
Av. Prof. Almeida Prado, 128 Tr.2 Biênio 2° Andar, ZIP 05508-900, São Paulo, SP, Brazil
Business Administration Dept., Superior School of Advertising and Marketing
Dr. Álvaro Alvim, 123, Vila Mariana, ZIP 04018-010, São Paulo, SP, Brazil
Faculty of Administration and Accountancy, Santa Cecilia University
Rua Oswaldo Cruz, 277, ZIP 11045-101, Santos, SP, Brazil
Fernando José Barbin Laurindo
Production Engineering Dept. of Polytechnic Engineering School, University of São Paulo
Av. Prof. Almeida Prado, 128 Tr.2 Biênio 2
°
Andar, ZIP 05508-900, São Paulo, SP, Brazil
Keywords: Web Analytics, Strategy, e-Business.
Abstract: Internet has changed competition, shifting products, supply-chains and even markets. Its democratization
gives power to the consumers what could be considered a threat to corporations. Although, the emergent
knowledge derived from digital media can contribute to personalized services, innovation and
communication with consumers in a real-time basis. Based on multiple case studies, this paper aims to
develop a comprehensive application of web analytics to achieve these business goals and thus support the
competitive advantage.
1 INTRODUCTION
When Internet business applications appeared on the
90s, they caused a significant impact on the
economy. Industries intend to manage their
processes to fit consumer needs, this flexibility
imposes a new dynamic to the economy. Nowadays,
it is possible the fulfilment of specific niches
considered unviable in traditional economies of
scale (Anderson, 2006).
The use of emergent knowledge generated by the
interaction of the consumer with the online presence
(e.g.| websites, apps, social media) can be a strategic
weapon to gain competitive advantage (Gibbert et
al., 2002). Web analytics (WA) helps companies to
acquire this knowledge through the measurement,
collection, analysis and reporting of Internet data
(Web Analytics Association, 2010).
Although, this promise is not being successfully
delivered, as the digital world is developing faster
than the capacity to measure it (Bughin et al., 2008).
There is a lot of WA issues cited in the literature:
Online metrics not aligned with the business
strategy (Kaushik, 2009).
Technical analysis of click stream on the
websites not considering the customer as the
center of the analyses (Kaushik, 2009; Arun et
al., 2006).
A lot of web metrics inflating reports
increasing the struggle to achieve business
insights (Stern, 2010), (Arun et al., 2006).
Lack of qualitative data resulting in
difficulties to take decisions (Bughin et al.,
2008; Kaushik, 2009);
The necessity of integration of online and
offline data to improve results of corporate
endeavors as campaigns and new products
(Bughin et al., 2008; Shankar & Yadav, 2010).
To address these points, this study aims to
develop a comprehensive approach of web analytics
(WA). The first step was a literature review of WA
as well as related concepts. Multiple case studies
125
Luis Cruz de Oliveira C. and José Barbin Laurindo F..
A FRAMEWORK OF WEB ANALYTICS - Deploying the Emergent Knowledge of Customers to Leverage Competitive Advantage.
DOI: 10.5220/0003526801250130
In Proceedings of the International Conference on e-Business (ICE-B-2011), pages 125-130
ISBN: 978-989-8425-70-6
Copyright
c
2011 SCITEPRESS (Science and Technology Publications, Lda.)
performed in different industries as automotive,
fashion and beverages contributed to analyze main
topics of this review. The result of this research was
a framework of WA to drive future analytical
endeavors.
2 LITTERARY REVIEW
2.1 Internet as a Source of Competitive
Advantage
Porter (1979) described five forces that shape the
competition, as well as, the profit expectation in a
determinate industry, a group of companies
delivering similar products or services. For a
company achieve a profit higher than the industry
average, it must have a competitive advantage. This
advantage can be translated in three generic
strategies (Porter, 1996): cost leadership,
differentiation, or a combination of the two cited
strategies in a specific market (segmentation).
Despite this traditional view of strategy, the
technology is changing some paradigms. Some
authors believe it is possible to offer a wide range of
segmented products in large scale; this mass
customization concept challenges the trade-off
argument using innovative and flexible production
process (Silveira et al., 2001).
The Internet is the best platform to integrate the
value system (Porter, 2001), its application performs
a vital role to deploy a unique and strategic position
(Oliveira, 2004). Beyond this contribution, some
authors argue the Internet performs a revolutionary
role, supporting a New Economy (Tapscott, 2001).
The 80/20 rule - 80% of the sales come from 20% of
products sold - it is not valid anymore for many
markets. The product sales curve is shifting to a long
tail design, the head of the curve is shorter, as the
middle and the tail (less sold products) becoming
more representative (Anderson, 2006).
In this segmented economy, understanding the
consumer is crucial. The online presence distributed
in websites, social networks, forums and blogs allow
users explicitly demonstrate their opinion. This
emergent knowledge encourages companies to
develop new strategies based on customer
competence (Prahalad & Ramaswamy, 2000). WA is
an efficient tool to collect and consolidate this
knowledge. In a comprehensive approach, it can
integrate the knowledge about the consumer
detected in sales history and click stream behavior
with the knowledge produced by the consumer in
blog postings and forms fulfillment.
The more flexible is the value system, the higher
is the potential of the Internet to impact the
competition. Services industries, especially
knowledge based industries are more likely to
conduct disruptive changes introduced by new
technologies (Duhan et al., 2001), but companies of
traditional sectors (e.g. Logistics and consumer
products) can also use the Internet to build
competitive advantages (Oliveira, 2004). This
potential is due to improvements in complementary
services (Lovelock & Wirtz, 2006) and redesign of
system value that could assume new typologies as
Net Values (Bovet & Marta, 2001).
2.2 WA Definition
According to Web Analytics Association (2010):
WA is the measurement, collection, analysis and
reporting of Internet data for the purposes of
understanding and optimizing Web usage
For Waisberg & Kaushik, 2009: “Web Analytics
can be defined as the act of increasing a website’s
persuasion and relevancy to achieve higher
conversion rate”. This conversion rate is the website
capacity to convert visits in business goals as sells
and leads.
Both definitions empathize the WA role to
improve usability performance, focusing on the
website interactions or online campaigns to increase
the audience, but they do not mention the WA
contribution the synergy between offline and online
initiatives. This is a relevant gap, because offline
sales driven by online actions plus online sales
driven by offline efforts are representative (Bughin
et al., 2008).
The WA industry started in the middle 90s with
the founding of companies such as Webtrends,
Omniture and NetGenesis. These companies
developed software to collect and analyze the user
click stream (Web Analytics Association, 2010).
Perhaps, this beginning explains the focus limited to
quantitative data generated by websites (Arun et al.,
2006).
This qualitative data can be collect in interviews,
focus groups or any interaction that allow the
researcher to explore the consumer reasons. It is
being usual to analyze blog posts, where users talk
about products, services and brands. The buzz
monitoring is a way to explore the consumer’s
opinions to reach a deep understanding of the
customer and optimize results (Sterne, 2010).
Some concepts can deeper the WA impacts on
business:
Web mining: the application of data mining
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techniques to discover costumers patterns
(Zhang & Segall, 2010);
Web Semantics: it is a knowledge
representation based on some kind of ontology
with a fixed vocabulary and typed relations
used to analyze web 2.0 data (Berendt, Hotho
& Stumme, 2010);
Web Personalization: It utilizes web data
generate through user interactions with the site
in order to deliver a personalized webpage
(Eirinaki & Vazirgiannis, 2003).
Concepts as competitive intelligence (Tarapanoff
2004), customer knowledge management (Gibbert et
al., 2002) and the cooption of customer competence
(Prahalad & Ramaswamy, 2000) have not directed
relation with WA, but they can contribute to extend
its boundaries, because they can increase the value
of WA to strategic planning.
3 METHODOLOGY
In order to understand the application of WA
concepts, this research analyzed three case studies
representing different industries: automotive,
beverage and fashion products. The companies’
selection followed the following criteria:
To be a significant player in its industry;
To compete in global markets;
To investment high amounts on online
presence;
To conduct WA studies in some instance.
These case studies must contribute to discuss the
following topics cited on the theory revision:
Usability;
Conversion of visits in business actions;
Buzz monitoring;
Competitive intelligence;
Marketing campaigns optimization;
Integration of online and offline initiatives
Results generated through online actions (eg.:
sales, forms filled, leads).
A semi-structured questionnaire (Yin, 1991) was
elaborated to cover these topics. Following the
research protocol, this questionnaire was applied in
interviews with business executives in charge of
online efforts and technical professionals that
developed the online presence.
Despite the fact of only one case covered all the
topics, the research application showed which topics
are more valued by the business executives.
These analyses resulted on a WA framework to
support future studies in this area.
4 CASE STUDIES
As a comprehensive approach of WA is not usual for
online efforts, the combination of the three cases
was crucial to produce a complete vision of WA
concepts.
Competitive intelligence and usability were
found in all cases. Analyses of conversion were
mentioned in two cases and the other themes were
found only in one case.
4.1 Automotive Industry
The company analyzed on this case used market
researches to measure the audience on the Internet of
the whole market, as well as, the audience of each
concurrent website. The metrics monitored were
unique visitors, average time spent on site, visits per
person and conversion of visits to leads.
The company noticed through tendencies
analyzes the main player’s audience was excessively
dependent on campaign investments, so it focused
on retain the visitors through differentiate tactics as
offering free MP3 downloads of new bands and
providing services to stimulate the returning visits.
With these consistent tactics, in 2008, the company
was the first on returning visits, the average
consumer visited the website 1,5 times in a month
the second manufacturer reached 1,4. The tendency
of the unique visitors of each player's website
pointed the company analyzed as the leader on this
metric (figure 1).
Figure 1: Linear tendencies of unique visitors per car
manufacturer.
Other key metric was the perceptual of visitors
that accessed the car configuration feature, with this
metric the company could evaluate the performance
of each player and take insights to improve its
efficiency.
The automotive company analyzed the offers of
each manufacturer, so it could improve their own
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127
offers improving the conversion on the website. In
the last quarter of 2008, 47% of the visitors
configured a car on the website, the second best
conversion on the market.
This case was limited its analyses to market
researches, because of a poor implementation of
traffic monitoring tools on the website, but this
limited approach, or externally focused approach,
brought a competitive understanding of the website.
The online presence is constantly improving based
on a market benchmark.
4.2 Beverage Industry
The beverage company planned efforts to take
advantage of the strategic opportunity to increase the
relationship with the consumer on the online
presence, promoting a link with the consumer that
was limited to the retail chain.
The company used this potential in a broad range
of online initiatives: the company gave support to
local events promoted by the brand dividing the
institutional website in regional areas; a lot of co-
branded actions develop with content portals to
approximate the relationship with segmented
publics; online market campaigns associated with
offline efforts; apps on social networks to promote
the interaction beyond the website.
It was a considerable challenge to monitor this
complex online presence in order to optimize the
online investments, to do so, the company
implemented a WA approach to monitor the
different actions on the Internet.
The competitive intelligence was the cornerstone
of the WA plan. Through the parameters provided
by market researches of audience, the company
refined its business goals on the Internet and defined
marks for relevant metrics as unique visitors, time
spent on site and returning visits, but additionally to
these metrics, the company needed to understand the
reasons behind the performance of the other player’s
websites. For this reason, qualitative studies of the
concurrent sites were elaborated to understand the
complete scenario, theses studies generated a key
performance indicator (KPI) called “maturity of
online presence”.
Other relevant issue was the optimization of
online campaigns, the cost of visit generated on the
website was a metric to verify the efficiency of the
media vehicles. In only three months, focusing on
this metric the company reduced 50% the cost per
visit.
The usability of the site was studied supported
by web traffics tools as Google Analytics. A deep
analyze allowed the website managers to discover
some bottlenecks on the navigation. Despite the fact
of the website had attractive features as games and
blogs, the user hardly perceive these features on the
home page, because of the great number of
attractions published. The web designers produced a
set of landing pages identified with the source of the
visit to handle this problem, for example, a user
came from Google Search that wrote the keyword
“games” was direct to game page.
The integration of online and offline might be
the most valuable analyze for the company. When
launching a new flavor of a beverage, the company
could observe the reactions of the consumer real
time through the social media and results of online
campaign. The company watched quickly which
kind of consumers accepted the new flavor, after
that, it distributed the offline efforts as point of sales
promotions to the regions more likely to buy the
product.
The company also monitored the buzz, opinions
of the consumers posted on social media. Qualitative
researches based on a sample of consumers' blog
posts increased the understanding about the brand
attributes and consumer behavior.
Based on the cited WA applications, it is
possible to verify this company had used its online
presence as a competitive tool.
4.3 Fashion Products
The company analyzed is a Brazilian shoes producer
which brand is recognized worldwide. The
institutional website is accessed by people from
different countries, and there are a lot of
communities dedicated to its brand.
Surprisingly, the positive image and global
awareness of the brand brought some fundamental
issues to the marketing area: how to measure this
affiliation to the brand, how to measure the
satisfaction of different publics with the brand
products and at least, how to generate value of this
knowledge.
The first question was about the social media.
There are millions of consumers spread in thousands
of communities of the main social networks as
Facebook and Orkut. The first challenge is to
estimate the total amount of users on these
communities, because the total of community is
impossible to be monitored manually. Based on the
long tail concept (Anderson, 2006) and using
logarithm curve to estimate the total of users per
community, it was possible to summarize the
community users. These users were divided in three
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Figure 2: Framework of Web Analytics.
categories: members, consumers and fanatics.
After count the total of members, the marketing
managers would like to understand what their
consumers were talking about on the brand
communities. As the previous case, they used
qualitative researches based on buzz monitoring to
capture the consumers expectation.
Complementary, it was implemented a tool on
the website to report the web usage. The nationality
of the different visitors was grouped to give a clear
scenario of the site usability for the foreign public,
the majority on the website. Doing so the analysts
had being astonished with some insights.
The audience of some countries as Philippines
was higher than other established markets. It showed
some fashion trends the marketing team does not
know.
People who do not speak Latin languages stayed
less than 30 sec on the site and 85% gave up on the
first page. This problem was caused by a lack of
visibility of the idiom option button. When it was
fixed, the time spent for these publics was
normalized.
5 A FRAMEWORK FOR WA
5.1 Premises
Analysing the cases, there are some contributions to
the framework development, the case insights
aligned with the literature review produced the
following premises to the framework:
It is necessary to trace a benchmark. Among
the case studies, companies with a benchmark
optimized their online presence to get a high
level performance.
The relationship with the client must be
analyzed in each touch point with the
consumer. The beverage company was the
only case that implemented a full vision of the
consumers, consequently get more benefits
from WA than the other companies.
The online and offline communication must
be considered as part of the same customer
relationship as showed in the beverage and
fashion cases.
The WA must extrapolate the quantitative
data. The cases showed that researches based
on the consumers posts are sources of
qualitative information.
5.2 Components
These premises were adopted to create a WA
framework with six components (figure 2). Each
component supports the understanding of the
consumer’s relationship (figure 2).
Component 1 – Navigation on the Internet:
Knowing the consumers navigation behaviors must
become closer relationship between the consumer
and the brand.
Component 2 – Active presence: The efforts to
drive the user from the Internet navigation to the
company website must be analyzed from the
campaign reach to the efficiency of each channel.
Component 3 - Receptive presence: when the
user entered the company website, the conversion to
the result must be deeply analyzed.
Component 4 – Social media: The social medias
(social networks, blogs and forums) are the main
source of customer knowledge. Qualitative analyzes
A FRAMEWORK OF WEB ANALYTICS - Deploying the Emergent Knowledge of Customers to Leverage Competitive
Advantage
129
as mind maps of market themes are essential to
understand the consumers’ point of view.
Component 5 –The online results must be set
based on the strategic vision.
Component 6 – Online/Offline influence – the
WA analyzes must support the total communication
mix signalizing the impacts of online and offline
efforts.
These components must be used together to
make sense.
The most relevant contribution of the WA
framework is to set parameters for analyzes
definition. Although it is not a complete guideline,
its use may ease the link of the WA analyses with
the strategic discussions.
6 CONCLUSIONS
The literature review listed some problems related to
WA. Lack of alignment with business strategy,
limitation to quantitative data, and focus on
technical report among other gaps undermine the full
potential of WA.
The cases showed this reality; only one company
explored all the WA dimensions cited in the
literature. This problem occurs because of an
exaggerated focus on tools and technologies and
fewer efforts on conceptualization of the analyzes.
The intention of this study is to help the analysts
to set relevant analyzes and to keep on tracking of
the strategic view, but do not close the discussion
about the possibilities of WA. Future studies are
necessary to verify if the WA framework is a useful
tool to configure the right analyzes.necessary to
verify if the WA framework is a useful tool to
configure the right analyzes.
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