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

 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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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

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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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