With the explosion of informal networks such as FaceBook etc., social network annalysis (SNA) software tools are increasingly vital aids for generating brand-related insights concerning key opinion leaders, effective messaging, keyword connectivity and other ROI-enhancing market research measures.

1. • Cognizant 20-20 Insights
Social Network Analysis: Bringing
Visibility to Your Connections
Executive Summary A Look Back
“In the long history of humankind … those who The term “social networking” was coined in the
learned to collaborate and improvise most 1950’s by professor J. A. Barnes while he studied
effectively have prevailed.” — Charles Darwin1 social ties in a Norwegian fishing village.2 In this
study, he concluded that the intricacies of social
Our social networks consist of people we interact life can be envisioned as a set of points that can
with on a day-to-day basis, online and/or offline. be joined to form a network of relations.
We often take this group of people for granted and
don’t make the effort to understand them fully. Since then, scientists and mathematicians have
And in the world of online-only relationships, such developed this idea further as they have worked
issues are compounded, often leading to reduced to understand how people interact and form
engagement or, worse, miscommunication. In a networks. They have translated such concepts
world which has become full of online social con- into mathematical models that enable the mea-
nections (thanks to Facebook, Twitter, etc.), these surement and close study of social networks.
cyber-enabled networks play a significant role in
our lives and compel us to redefine our concep- Social Network Analysis
tions of communication and engagement. Such As with any systematic evaluation, conducting an
reevaluations require increased insight into the effective social network analysis comprises four
very nature of these networks. stages:
A by-product of psychology, social network • Defining objectives.
analysis (SNA) offers a mechanism to help orga- • Data gathering.
nizations better understand these relationships
and the strength of individuals’ network connec-
• Data visualization.
tions. It provides an effective way to analyze and • Results analysis and insights.
understand the complex networks of individuals, Defining Objectives: An analysis lacks meaning
groups, advocates and detractors by assessing until it has a stated objective. We need to
interactions in terms of strength, frequency and clearly define why we seek to understand social
other relevant factors. networks. Within a business context, some
possible objectives include the following:
In this white paper, we will bring explore SNA and
how it is used to “make the invisible visible” for • Better targeting and messaging.
building brand awareness and addressing other • Identification of brand advocates.
important business concerns.
• Impact of competition on the network.
20-20 insights | april 2012

2. However, there is much more that can be done A Simple Network
with the analysis. Some applications of the
analysis are discussed later in this paper.
Friend 6
Data Gathering: The data required to undertake Friend 1
any analysis is often bought from third-party
vendors, but in the case of this analysis there
are no vendors that collect social network data Friend 5 Self
specific to brands or organizations. Thus, the data
has to be extracted. The amount of data that can
be collected is voluminous, so it is important to
capture the right data.
Friend 2
There are two ways to capture information about
the relationships within a defined social network.
Friend 4 Friend 3
• MR Surveys: A questionnaire is designed
with the stated objective in mind and is then
Figure 1
presented to the panel — which should consist
of individuals and teams in the network. The
questions should focus on identifying the
(the individual or entity) and various vertices
relationships and information flows among
(the individual’s network) that do not connect.
the network’s elements. A few examples of
(See Figure 1.)
plausible questions are:
Key benefits of such networks include:
>> Please share the names of five people
whom you know who are aware of the brand >> Awareness information: To assess how
ABC. aware is the network about the brand.
>> How are you connected with them? >> Influence: To understand the immediate
reach the brand has on the network.
>> How did they get to know about the brand?
>> How do you discuss the brand? • Complex: These are scale-free networks where
the pattern of connections between the nodes
However, the biggest drawbacks of going the (building elements of a network) are neither
market research route is its limited reach and purely random nor purely organized. Here the
high associated costs. entities in the network can be connected to
• Web Crawlers: These are computer programs each other. (See Figure 2.)
that browse the Web in an organized and
automated manner. There is a plethora of Web
crawlers available that can either be licensed
A Complex Network
or created to suit an organization’s needs.
Utilizing Web crawlers eliminates the need for
Friend 6
expensive market research while extracting a
wide swath of information. In some situations, Friend 1
however, privacy policies and regulations force
organizations to employ both methods.
Group 2 Self
Data Visualization
Now that all the data has been acquired, why
do we need to visualize the network? A simple
answer is that visualization will heighten our
understanding of such a social network. To best
connect the elements and aid visualization, orga- Friend 2
nizations must understand the possible types of
connections:3,4
Friend 4 Group 1
• Simple: This is the study from the standpoint Figure 2
of an individual. Here there is only one center
20-20 insights 2

3. A Complete Network how this knowledge can be leveraged to guide
marketing decisions.
Hosp 1 Keyword Connectivity Analysis
Nodes of a network need not comprise only
Doc 1 people but can include anything (e.g., technology,
Patient keywords, etc.).
Doc 2
The beauty of network analysis is that it can be
applied to any network with suitable modifications.
Friend 1
In a keyword analysis, first a network mapping is
created to understand how the various keywords
are linked (based on their associated connota-
tions) to a brand. Based on this mapping, various
messages can be created to suit the needs.
Friend 2 Web MD Key Opinion Leaders Identification
If the information flow in a network is understood,
Figure 3
questions can be raised, such as who would be
the best person to influence; who can be easily
The benefits of such networks include: identified, etc.
>> Individual satisfaction and network-level A solid understanding of network connections,
performance.
interests and engagement levels allows organiza-
>> Identification of opinion leaders and influ- tions to identify central nodes of influence that
encers. can be leveraged as key opinion leaders (KOLs).
>> Success of community for the brand. Communication and engagement can be directed
There are many third-party freeware tools that toward KOLs and the viral power of their connec-
can be used for data visualization. An exhaustive tions will allow messages to move to the intended
list of these can be found here on Wikipedia. audience.
An example of data visualization for a complete Competitive Intelligence
network is illustrated in Figure 3. This patient- Any relevant information that can be derived
centric flow of networked healthcare about a competitor is important. In today’s world
A large network information can be utilized to where there is an abundance of freely available
public information, insights can be derived
that is relatively understand how marketing campaigns
on consumer sites can be leveraged to identify what the competition is doing. For
apathetic about to influence targeted prescribers. example, if the analysis is intended to identify
a brand will also various positions which an organization has
Results Analysis and Insights created for a particular brand (Chief Technical
not contribute to SNA examines interpersonal networks Officer, etc.), this can provide an idea of the orga-
the social capital and value exchanges. Here, we gauge nization’s plans for that brand. Platforms such
of the brand. and use certain attributes to better as LinkedIn can be used to ascertain this. This
understand the potential of marketing data can then be consumed with other secondary
to a network and to gauge ROI. Some research information — such as annual reports,
of the attributes include: etc. — to understand the intent of the organiza-
tion or brand.
• Strength of relationships.
• Information capacity of the network. Measuring Social Capital for a Brand
The combination of a network’s strength along
• Rate of flow or traffic across the network. with the network members’ engagement and sat-
• Distance between network points. isfaction are the key elements that contribute to
• Probabilities of passing on information. a brand’s social capital. A small network, even if it
consists of highly engaged and satisfied members,
Practical Applications does not carry the viral strength to generate much
The next section explores business applica- social capital for a brand. By the same token, a
tions that exploit insights gathered via SNA and large network that is relatively apathetic about a
20-20 insights 3

4. brand will also not contribute to the social capital generated, which in turn can be used to calculate
of the brand. By understanding the followers and the ROI.
those connected to these followers, organizations
can deduce how consumers feel about the brand Conclusion
and how their interactions can be leveraged to Knowledge has always been gained through
maximize the brand’s social capital. networks, but in the past there was but one link
to these insights. In today’s fast-paced global
Social Network ROI business environment, these links have increased
The ROI of a social network is fundamentally tied as the number of informal networks has exploded.
to the cost of forming its requisite social capital. As a result, it becomes imperative to demystify an
Before computing the ROI, organizations must individual’s network/s to gain substantial benefits.
assess numerous parameters such as “network Social network analysis provides a means to
relevance,” “brand engagement,” “network explore and understand existing networks and
engagement,” etc. and then allocate a weight at the same time help organizations evaluate
to each parameter to compute a score. This and derive value from existing and emerging
score can be used to compute potential revenue networks.
CASE STUDY: Applying Social Network Analysis >>
The following hypothetical scenario is designed to provide a taste of social network analysis.
• Situation: A large consumer brand wishes to increase sales and enhance its brand image. The brand
wants to use social media as a channel in its consumer marketing plan. To successfully implement and
manage a social media campaign, it wants to first identify key opinion leaders and quantify network
size to estimate reach and impact of the social campaigns. This information will allow the brand to
engage with leaders and their network, which will generate positive buzz in the market.
• Challenge(s): With a consumer base that runs in the millions, the brand needs to determine the most
efficient way to make sure it has current and accurate customer information. While the company has
information linking sales to demographics and a “consumer VIP” program, very little information is
known about what drives consumers to purchase or how the brand’s products are perceived in the
market.
• Approach: To meet these objectives, the company did the following:
It started by collecting information about customers who like the brand and have been engaged on the
brand page of its social Web presence (Facebook). Based on their level of engagement, network reach,
demographics and product satisfaction, a survey was launched to better understand unmet customer
requirements, needs and perceptions. The survey focused on collecting the following information:
>> Brands and competitive products they have used.
>> Time associated with the brand.
>> Last use of the brand.
>> Primary medium of shopping/contact.
>> Main points of satisfaction around products.
>> How they shop for other brands.
Later a process was developed to segment the network. This allowed for the addition of various weights
to the aforementioned parameters and helped to determine the proximity of the customer to the brand in
the network. The proximity also governed the advocacy of the customer to the brand. This approach was
further used on an ongoing basis to evaluate if a key opinion leader had moved down the pecking order.
Once a deeper level of understanding was acquired around key opinion leaders, the brand was able to
quantify the impact that key opinion leaders had on the brand’s sales.
20-20 insights 4

5. Footnotes
1
http://www.brainyquote.com/quotes/quotes/c/charlesdar393305.html
2
http://www.bioteams.com/2006/03/28/social_network_analysis.html
3
Steve Borgatti, “Network Data Collection,” (2010), http://www.analytictech.com/networks/topics.htm.
4
“Social Network Analysis,” Steve Ebener, http://www.paho.org/CDMEDIA/KMC-SNA/training-sna.htm.
References
Rob Cross, Stephen P. Borgatti, Andrew Parker, “Making Invisible Work Visible: Using Social Network
Analysis to Support Strategic Collaboration,” California Management Review (2002).
Steve Borgatti, “Network Data Collection” (2010), http://www.analytictech.com/mgt780/slides/survey.
pdf.
Kenneth K.S. Chung, Liaquat Hossain, Joseph Davis, “Exploring Sociocentric and Egocentric Approaches
for Social Network Analysis,” University of Sydney (2006).
Nora Dudwick, Kathleen Kuehnast, Veronica Nyhan Jones, Michael Woolcock, “Analyzing Social Capital
in Context,” World Bank Institute (2006).
LNX Research, “Finding Key Opinion Leaders Using Social Network Analysis” (2007).
“Social Network Analysis,” Steeve Ebener, http://www.paho.org/CDMEDIA/KMC-SNA/training-sna.htm.
Steve Borgatti’s educational Website, http://www.analytictech.com/networks/topics.htm.
An intro to SNA, http://www.bioteams.com/2006/03/28/social_network_analysis.html.
About the Authors
Udit Rastogi is an Engagement Manager with Cognizant’s Enterprise Analytics Practice, working within
its Digital Analytics Center of Excellence. He has over 10 years of industry experience and specializes
in strategy, and measurement/assessment of digital marketing activities for customers across verticals.
Udit can be reached at Udit-1.Rastogi-1@cognizant.com.
Tom Jirele is a Principal and Practice Leader within Cognizant’s Multi-Channel Marketing and Measure-
ment Center of Excellence, focusing on the measurement and interaction of marketing channels to
optimize client spend. He has over 30 years of experience in measurement and modeling across the
life sciences, retail, finance and education industries. For the past 15 years he has worked in the life
sciences industry leading engagements related to promotional measurement, marketing strategy and
multi-channel optimization. He can be reached at Thomas.Jirele@Cognizant.com.
About Cognizant’s Enterprise Analytics Practice
Cognizant’s Enterprise Analytics Practice (EAP) combines business consulting, in-depth domain
expertise, predictive analytics and technology services to help clients gain actionable and measurable
insights and make smarter decisions that “future-proof” their businesses. The practice offers com-
prehensive solutions and services in the areas of sales operations and management, product
management and market research. EAP’s expertise spans sales force and marketing effective-
ness, incentives management, forecasting, segmentation, multi-channel marketing and promotion,
alignment, managed markets and digital analytics. With its highly experienced group of consultants,
statisticians and industry specialists, EAP prepares companies for the future of analytics through
its innovative “Plan, Build and Operate” model and a mature “Global Partnership” model. The result:
solutions that are delivered in a flexible, responsive and cost-effective manner. Learn more at:
http://www.cognizant.com/enterpriseanalytics.
20-20 insights 5

6. About Cognizant
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