Social Network Analysis: Bringing Visibility to Your Connections


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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.

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Social Network Analysis: Bringing Visibility to Your Connections

  1. 1. • Cognizant 20-20 InsightsSocial Network Analysis: BringingVisibility 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. 2. However, there is much more that can be done A Simple Networkwith the analysis. Some applications of theanalysis are discussed later in this paper. Friend 6Data Gathering: The data required to undertake Friend 1any analysis is often bought from third-partyvendors, but in the case of this analysis thereare no vendors that collect social network data Friend 5 Selfspecific to brands or organizations. Thus, the datahas to be extracted. The amount of data that canbe collected is voluminous, so it is important tocapture the right data. Friend 2There are two ways to capture information aboutthe 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 SelfData VisualizationNow that all the data has been acquired, whydo we need to visualize the network? A simpleanswer is that visualization will heighten ourunderstanding of such a social network. To bestconnect the elements and aid visualization, orga- Friend 2nizations must understand the possible types ofconnections: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. 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 derivedthat 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 Technicalnot 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. 4. brand will also not contribute to the social capital generated, which in turn can be used to calculateof the brand. By understanding the followers and the ROI.those connected to these followers, organizationscan deduce how consumers feel about the brand Conclusionand how their interactions can be leveraged to Knowledge has always been gained throughmaximize the brand’s social capital. networks, but in the past there was but one link to these insights. In today’s fast-paced globalSocial Network ROI business environment, these links have increasedThe ROI of a social network is fundamentally tied as the number of informal networks has the cost of forming its requisite social capital. As a result, it becomes imperative to demystify anBefore 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 torelevance,” “brand engagement,” “network explore and understand existing networks andengagement,” etc. and then allocate a weight at the same time help organizations evaluateto each parameter to compute a score. This and derive value from existing and emergingscore 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 weightsto the aforementioned parameters and helped to determine the proximity of the customer to the brand inthe network. The proximity also governed the advocacy of the customer to the brand. This approach wasfurther 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 toquantify the impact that key opinion leaders had on the brand’s sales. 20-20 insights 4
  5. 5. Footnotes1 Steve Borgatti, “Network Data Collection,” (2010), “Social Network Analysis,” Steve Ebener, Cross, Stephen P. Borgatti, Andrew Parker, “Making Invisible Work Visible: Using Social NetworkAnalysis to Support Strategic Collaboration,” California Management Review (2002).Steve Borgatti, “Network Data Collection” (2010), K.S. Chung, Liaquat Hossain, Joseph Davis, “Exploring Sociocentric and Egocentric Approachesfor Social Network Analysis,” University of Sydney (2006).Nora Dudwick, Kathleen Kuehnast, Veronica Nyhan Jones, Michael Woolcock, “Analyzing Social Capitalin Context,” World Bank Institute (2006).LNX Research, “Finding Key Opinion Leaders Using Social Network Analysis” (2007).“Social Network Analysis,” Steeve Ebener, Borgatti’s educational Website, intro to SNA, the AuthorsUdit Rastogi is an Engagement Manager with Cognizant’s Enterprise Analytics Practice, working withinits Digital Analytics Center of Excellence. He has over 10 years of industry experience and specializesin strategy, and measurement/assessment of digital marketing activities for customers across verticals.Udit can be reached at 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 tooptimize client spend. He has over 30 years of experience in measurement and modeling across thelife sciences, retail, finance and education industries. For the past 15 years he has worked in the lifesciences industry leading engagements related to promotional measurement, marketing strategy andmulti-channel optimization. He can be reached at Cognizant’s Enterprise Analytics PracticeCognizant’s Enterprise Analytics Practice (EAP) combines business consulting, in-depth domainexpertise, predictive analytics and technology services to help clients gain actionable and measurableinsights 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, productmanagement 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 throughits 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: 20-20 insights 5
  6. 6. About CognizantCognizant (NASDAQ: CTSH) is a leading provider of information technology, consulting, and business process out-sourcing services, dedicated to helping the world’s leading companies build stronger businesses. Headquartered inTeaneck, New Jersey (U.S.), Cognizant combines a passion for client satisfaction, technology innovation, deep industryand business process expertise, and a global, collaborative workforce that embodies the future of work. With over 50delivery centers worldwide and approximately 137,700 employees as of December 31, 2011, Cognizant is a member ofthe NASDAQ-100, the S&P 500, the Forbes Global 2000, and the Fortune 500 and is ranked among the top performingand fastest growing companies in the world. Visit us online at or follow us on Twitter: Cognizant. World Headquarters European Headquarters India Operations Headquarters 500 Frank W. Burr Blvd. 1 Kingdom Street #5/535, Old Mahabalipuram Road Teaneck, NJ 07666 USA Paddington Central Okkiyam Pettai, Thoraipakkam Phone: +1 201 801 0233 London W2 6BD Chennai, 600 096 India Fax: +1 201 801 0243 Phone: +44 (0) 20 7297 7600 Phone: +91 (0) 44 4209 6000 Toll Free: +1 888 937 3277 Fax: +44 (0) 20 7121 0102 Fax: +91 (0) 44 4209 6060 Email: Email: Email:©­­ Copyright 2012, Cognizant. All rights reserved. No part of this document may be reproduced, stored in a retrieval system, transmitted in any form or by anymeans, electronic, mechanical, photocopying, recording, or otherwise, without the express written permission from Cognizant. The information contained herein issubject to change without notice. All other trademarks mentioned herein are the property of their respective owners.