Social Media Analytics: Enabling Intelligent, Real-Time Decision Making

Today, an increasing number of organizations rely on social media for interacting internally, as well as with external constituents. Using advanced and predictive analytics applied holistically via a centralized “command center,” companies can mine growing pools of unstructured data, deliver more timely and actionable insights, and better inform business and operational strategies.

• Cognizant Reports

cognizant reports | August 2013

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Executive SummaryWith more than 1.5 billion users worldwide,1 social media offers a treasure trove of information in the form of real-time, interactive communications made available through blogs, tweets, updates, images and videos. Not surprisingly, organiza-tions are growing more and more reliant on social media to understand and work more responsively with employees, vendors and customers, and bet-ter gauge the competition. However, mining and analyzing the huge volumes of unstructured data generated by social media is no easy task.

Using social media analytics, organizations can mine and decipher vast amounts of data from various social media platforms to discover customer sentiment about brands, trends, the issues customers face, the efficacy of marketing campaigns and competitor intelligence, for exam-ple. Findings can be used by sales, marketing and other functions to support more informed and timely decisions. By adding predictive analytics, organizations can more accurately forecast cus-tomer needs and behaviors, and anticipate and deal with issues before they can damage the busi-ness’s reputation.

Yet achieving this level of knowledge can be a real challenge. We have developed a framework, LAEI, that allows companies to be successful in their social media initiatives. The first step for any organization is to listen to conversations. This could be active listening using certain tools and a dedicated team for owned and earned media, or passive listening during a time of crisis. Listening helps in collecting all the data, and using the power of technology and human inter-actionsto analyze that data for business insights.

The next step in the journey is the most critical, and one where we see most customers experi-ence a disconnect. Once you have insights, it is important to use them as part of your engage-ment strategy. This could be as simple as responding back to one-on-one conversations for customer service or as complex as using the insights to drive content strategy for marketing. The last step is to integrate the social data and combine it with enterprise data to obtain the digi-tal profile of your customer.

Organizations with limited capabilities and bud-gets can pursue analytics as a service (AaaS), an emerging service delivery model that pro-vides access to third-party specialists that can

offer analytical insights – dynamically shifting the cost of owning the technology infrastructure, processes and talent from the organization to an expert partner.

Driving ForcesThe Rise of Social MediaAccording to an Experian Marketing Services study,2 U.S. consumers spend 27% of their total Internet time on social networking sites and forums. Facebook has more than 1.1 billion active users. Twitter, on average, records 58 million tweets every day. These statistics, combined with the millions of blog posts on the Internet and discussions that occur by the minute on forums and social networking sites, for example, can pro-vide a rich and growing pool of data on market trends and such things as consumer interests and perceptions. Still, data is one thing; analyzing it successfully to gain useful insights is quite another.

The Growth of User-Generated ContentMany consumers enthusiastically post their expe-riences with brands and write product reviews on various social media platforms like wikis, blogs and social networking sites. Such user-generated content (UGC) is perceived by pundits to carry more value and make brands more trustworthy than any company advertisement.

According to a 2012 Nielsen survey of 28,000 global Internet users, 92% of consumers trust recommendations from friends and family more than any other form of advertising. Seventy percent of customers place their trust in online consumer reviews – making this medium the second most trusted form of advertising.3

Marketers, too, are encouraging users to com-ment, submit pictures and videos, rate products and write reviews. However, user-generated con-tent is mostly informal, and analyzing it can be difficult – especially when trying to ascertain the rationale underlying certain comments and rat-ings, what customer posts mean, and the signifi-cance of the type of medium used, for example.

The Challenge of Unstructured DataAccording to Gartner, 80% of enterprise data – documents, e-mails, call logs, corporate blogs and the like – is unstructured (i.e., it does not fit into any traditional database).4 The proliferating use of social media data (including tweets and comments in colloquial style, images, videos,

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blog posts, etc.) is exponentially increasing the amount of unstructured data to be sorted, ana-lyzed and used to gain meaningful insights. Yet most organizations do not have the resources or tools needed to sift through and interpret the vast quantities of social media data they have at their disposal without making considerable changes to their IT infrastructure, operational processes and organizational structure.

While the “digerati” seem to agree that social media data presents significant opportunities, few organizations appear to have the strategies, skills and tools in place to analyze the data. In fact, analyzing and applying data of all types and formats are the biggest data-related challenges in 2013 for 45% of the 700 marketers surveyed by Infogroup Targeting Solutions and Yesmail Interactive (see Figure 1).5

Advanced social analytics can help organiza-tions analyze and quickly draw inferences from burgeoning unstructured social media and enter-prise data, and convert it into actionable insights.

Harnessing Social Media Data Using the LAEI Framework

brand mention, customer feedback and discus-sions, for example. The scope of data collec-tion depends on the business purpose, such as gauging the market’s perception of a new prod-uct, monitoring marketing campaigns, creating brand awareness and performing competitor intelligence. Data-gathering tools (free or sub-scription-based) can help organizations collect customers’ tweets, blog posts, status updates, etc., in real time from various social media sites, based on pre-set search parameters. This allows companies to track and respond to indi-vidual customer updates and tweets as soon as they are received. For example, from Q2 2012 to Q2 2013, brands improved their response rates on Facebook by 143%, according to a survey by Social Bakers. The airlines industry led in social customer care by answering 79% of cus-tomer questions, closely followed by finance (78%) and telecom (75%). Dutch airline KLM is the most socially devoted brand – answering 98% of questions on Facebook at an average response time of 45 minutes.6

• Analyze: The next step involves analyzing the collected data to understand customer sentiment. However, the data will contain plenty of irrelevant information – especially if organizations use social media crawlers to find comments with brand mention. This makes it difficult to pin down what customers are actually saying.

Removing the “noise” around the data will help improve the accuracy of the analysis. Semantic analysis is an advanced data-cleans-ing method that groups large amounts of data

In our view, organizations need a holistic strat-egy for exploiting social media’s full potential. We recommend that companies build a social media analytics framework around four critical steps – listen, analyze, engage and integrate – to effec-tively use social media for intelligent decision making (see sidebar, next page).

• Listen: The first step involves identifying and collecting relevant social media data around

Data Challenges in 2013

Figure 1

Source: Infogroup Targeting Solutions and Yesmail Interactive, 2013

25%

20%

13%

12%

11%

11%

8%

Analyzing Data

Applying Data

Cleaning Data

Protecting Customer Data and Privacy

Collecting Data

Real-time Data Collection

Hiring Qualified Employees

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based on the relationship between words and/or phrases. It provides a higher level of refinement than text analytics or natural lan-guage processing tools, and exceeds other traditional methods that involve correcting typos and errors, removing duplicates and using Boolean operators such as “and, or, and no” to limit the search, for example. Seman-tic analysis goes beyond classifying customer comments into positive, negative and neutral, and provides insights into what customers think about products, including what they like and what improvements they would like to see.

The latest cloud-based tools for customer feed-back analysis support multiple languages at advanced levels – providing accurate and real-time information about various markets. For instance, Finnish retailer Kesko uses Etuma’s text feedback analysis to understand customer experiences by analyzing numerous surveys and customer feedback. This has helped the retailer identify and resolve issues related to customer dissatisfaction, enhance its ability to react to problems, and improve product avail-ability and day-to-day operations.7

Further, analyzing social media data helps organizations in the following aspects:» Customer segmentation: Using customer

demographics and other personal infor-mation collected from different sources, organizations can divide customers into

segments based on their behavioral pat-terns. Segmentation helps shed light on issues specific to each group, and address group patterns as a whole. It can be used to design marketing campaigns for each target segment. For instance, marketers can offer high-value customers greater discounts and other incentives to persuade them to stay.

» Identifying influenc-ers: Customers share varying degrees of relationships with other individuals within a group. Social network analytics allow organizations to identify the strength of these relationships and how information flows within groups. Most important, these tools enable companies to target group influenc-ers who can best affect members’ decisions. Influencers can be used to quickly bring a new service or product to market, attract new customers and prevent mass defec-tion through incentives like special offers.

Quick Take

Applying the LAEI Framework

A leading global pharmaceutical company organizing a fund-raising event wanted to monitor the Twitter conversations of attendees to understand what they thought about the company. It also wanted to moderate and display tweets manually, in real time, on a large screen during the conference. We created a federated Twitter governance tool that captured all conference-related tweets in real time – allowing multiple moderators to filter and update their feeds and display approved feeds on the screen. An additional layer for checking regulatory compliance was incorporated during the requirements analysis phase.

More than 6,000 conversations were monitored and moderated during the conference. The tool helped identify the top tweets, trending topics and what key opinion leaders were talking about. More important, it enabled the company to identify key influencers, and understand attendees’ sentiments of the company. The exercise increased attendees’ engagement levels, as evidenced by their heightened Twitter activity. It also created a buzz and user-generated content on social channels, which had a posi-tive impact on the brand – resulting in the company raising US$70,000 — a substantial increase over the US$50,000 it had targeted.

Social network analytics allow organizations to identify the strength of these relationships and how information flows within groups. Most important, these tools enable companies to target group influencers who can best affect members’ decisions.

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Tools such as Klout8 can be used to gauge a person’s online influence based on their responses to social media posts.

• Engage: Customers who are engaged with companies through social media spend 20% to 40% more than other customers, reveals a Bain & Co. study of more than 3,000 customers.9 Analyzing social media posts provides a deeper perspective on trending topics, hot brands and the type of content that is being shared, for example. This kind of analysis can be used to drive relevant content posts on channels like Twitter, Facebook, Instagram and blogs, and propel content shares.

Predictive analytics can also be used to under-stand what would interest customers, and the ideal time to publish content to “sweeten” con-tent performance. For instance, Adobe Social predicts engagement levels and proposes the best time to post content on Facebook in order to improve content engagement and interaction.

• Integrate: This stage involves integrating unstructured data across the organization with enterprise structured data to obtain a 360-degree view of customers. To achieve this, organizations must integrate their social media platforms with their existing master data management (MDM) systems. Once a customer’s social media data flows into the organization, the MDM hub can search to determine whether the customer profile already exists within the enterprise data-base. If so, it can automatically add relevant social media data to the master customer file. It can also update customer profiles whenever changes are made in source systems to reflect the latest customer information.

Integrating social data with the MDM hub offers multiple benefits by enabling com-panies to:» Create digital profiles of customers to

uncover various types of relationships and influencers.

» Provide insights on customer activity across social channels.

» Pull user location data as soon as cus-tomers update their location, using the check-in feature on social media sites. Sales can use this information to reach out to customers who are on the move and

ready to purchase, and direct them to the nearest stores.

» Gain insight into customer spending hab-its, improve location-based services and identify locations for real-world marketing campaigns.

Social Media Command Centers: The One-Stop ShopA social media command center collects relevant conversations in real time, and then analyzes them to provide insights about customer senti-ment, brand performance and the competition, for example, to inform decisions across various functional areas within the organization. Compa-nies such as Dell, Cisco and Gatorade have imple-mented social media command centers primarily to listen and respond to customer conversations quickly.10

By combining data visualization tools, social media platforms and analytics, command centers allow organizations to monitor relevant online chatter in real time. This information can be used to quickly reach out to customers and support them in suitable ways, thus helping to secure their loyalty. For instance, T-Mobile uses a social media command center to prevent customer churn. Auto companies are employing these centers to predict recalls. General Electric has a command center to help the company quickly locate power outage areas and repair electric grids.11

Real-time monitoring can help adjust content based on hot topics, make on-the-fly changes to marketing campaigns and design content to improve customer engagement, for example. The latest tools allow companies to add data from other systems, such as customer relationship management (CRM), and configure data visual-izations for smartphones, PCs and other mobile devices, apart from large television screens.

Social media command centers have also been employed by sports organizers and non-profit organizations. The organizers of the Super Bowl, for example, launched a social media command center in 2012 to enhance the experience of the estimated 150,000 fans who visited the game site in Indianapolis. In this case, the center pro-vided information about safety and service. The command center used keyword-based monitor-ing and geo-targeting of the Indianapolis/Indiana area across major social media sites12 to identify

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• Marketing: Organizations can no longer rely on analyzing yesterday’s customer chatter to devise today’s marketing campaigns. Social media analytics helps marketers cope with fast-changing customer preferences through real-time marketing. By discovering trending topics, marketers can quickly hone tweets and social media updates to align with hot topics, stay relevant and drive customer engagement. Companies such as Dell and McDonald’s use social media analytics to listen to customers in real time and adjust ad campaigns and con-tent on the fly to resonate with social media users. In fact, based on social media feedback, Fifth Group Restaurants decided to tone down one of its Mexican dishes made with chilies, in spite of an internal debate.14 Marketers can also use image recognition technologies to see what images are being shared by customers and their impact on sales, for example. (See sidebar, next page).

• Sales: Predictive analytics, such as affinity or market-basket analytics, provides details about products that are often bought together, as well as the right combination of products and services for customers – such as a game and a movie based on the game. This informa-tion can be used for cross-selling and up-sell-ing, and customizing products and services. Customer sentiment can be used to forecast sales and revenues, and prepare in advance for any spikes in demand.

• Customer service: Social media channels can help companies identify potential customer-service issues before they spiral and inflict damage to a brand’s reputation. By monitor-ing social media for real-time feedback during a new product release, the customer service team can identify issues and proactively reach out to customers to fix glitches. Customer ser-vice can also forecast what type of problems customers may encounter during specific times and prepare accordingly.

• Competitive intelligence: In business, noth-ing can be more valuable than solid competi-tive intelligence. Social media analytics allows companies to track competitor mentions on social media, and understand how competitors are leveraging various social media platforms for brand promotion and customer engage-ment, for example. This information can be

and respond immediately to visitors who posted on Twitter, Facebook and other social media plat-forms on event-related issues. The command cen-ter staff answered attendees’ inquiries about the event, routes, parking, food, cab service, hotels, tourist attractions and emergency tips, and pro-vided real-time updates about traffic, weather, etc. The initiative was a hit, and managed to attract 50,000 fans – 10 times more than expected, and at a 3.6 to 1 positive to negative sentiment ratio.13

While numerous big brands have built their own command centers, others are undecided – fearing the repercussions of huge investments. Companies can build their own state-of-the-art command centers by partnering with technology providers, forming joint ventures, using managed services or choosing another evolving business model.

The Case for Advanced Social AnalyticsSocial media analytics has grown from simply being a tool for collecting customer likes and com-ments to an opportunity to gain critical business insights and make quick and effective decisions. By augmenting social media analytics with pre-dictive capabilities, organizations can more accu-rately forecast what their customers are likely to do. Predictive analytics involves the use of regres-sion models and advanced techniques, such as neural networks, to provide a complete view of customers and their future actions based on their transactional, social-media and other data.

The following are areas where social media ana-lytics can have a big impact:

• Innovation: Product development teams can tap into social media to understand what customers like or dislike about a brand, the

desired product features that a target demographic wants, and popular features of competitors’ products. This information can be used to fix defects in the next iteration, trigger new ideas, and also review cur-rent ideas and products in development. Most crowd-sourcing campaigns now use social media to fuel ideas

and contributions. Feedback on new product demonstrations can also provide inputs on customer preferences in various markets.

Organizations can no longer

rely on analyzing yesterday’s

customer chatter to devise today’s

marketing campaigns.

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useful for reviewing and strengthening current social media strategies. Monitoring reviews and posts by bloggers and thought lead-ers about competitive products can provide valuable inputs that can be used to enhance various functions across the organization.

Embracing Analytics as a ServiceAnalyzing social media and other enterprise data is a difficult task. Handling huge volumes of data poses a significant challenge for organizations and requires substantial investments in people, processes, IT tools and infrastructure. Other chal-lenges, such as a lack of domain capabilities and budgets, disparate databases and organizational silos can prevent organizations from effectively using social media data (see Figure 2, next page).

A partner with the ability to handle complex analytics tasks can help companies take better advantage of analytics. With process virtualiza-tion and cloud computing, opportunities now exist for cost-cutting through global sourcing via the Business Process as a Service (BPaaS)15 deliv-ery model. This can save precious capital expen-ditures (Cap-Ex) – estimated by some industry sources at up to 30% – by eliminating the cost of

acquiring expensive hardware, software and key talent through outcomes-based and consumption pricing models.

A subset of BPaaS, analytics as a service (AaaS) combines traditional knowledge process out-sourcing (KPO) and business process outsourc-ing (BPO) capabilities with more efficient, cloud-enabled ways of delivering analytical insights. This approach allows organizations to deploy analytics solutions tailored to their needs. The service can be increased or decreased as busi-ness requirements dictate, providing more flex-ibility in controlling operating expenses.

Organizations should seek a partner that can seamlessly marry analytics with technology, rather than a pure-play analytics services pro-vider that lacks industry-specific domain exper-tise. The key analytical component is derived from the ability to understand various business-use cases and develop predictive models capable of comprehending complex relationships and learn-ing from historical data. A qualified partner must have expertise in extracting meaningful insights from social networks and social media and per-forming complex analyses on the data. Such a

Quick Take

Image Recognition Analytics

Social networking sites such as Facebook, Pinterest, Instagram and Flickr receive and host billions of photos, with thousands added every minute. Some of the images can be of brands, company logos and products, without any text to reference them. Since traditional social media monitoring tools can only track text (such as user comments and posts mentioning a brand), marketers often do not know what customers are referring to, who is using their company’s products, or if counterfeit versions of those products exist.

Analytics with image recognition capabilities can help companies overcome this challenge and lever-age images to enhance their market knowledge and extend their reach. Advanced image analytics with pixel-level analysis is gradually gaining acceptance among large retailers and advertising agencies. Companies such as Piqora and Curalate have developed image recognition technologies for social media sites such as Facebook, Pinterest and Instagram – allowing them to identify the most popular shared images from their Web sites, the most influential individual visitors, and the traffic that an image diverts to a target Web site, for example.

A case in point: A coffee shop chain can use this technology to gather information about what its customers like and dislike; confirm the most popular shops in the chain; the number of times an image is shared and by how many people; its impact on sales; location-based knowledge and competitor infor-mation. The coffee chain can reach out to more customers, respond to user comments, engage with influencers and other prospective customers, and use images with positive comments for marketing after obtaining permission.

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partner must also be able to integrate advanced analytics with enterprise systems, and enhance business efficiencies.

As analytics processes become standardized and can uniformly be applied via cloud-enabled models (harnessing the growing clout of utility computing architectures), we believe that orga-nizations stand to benefit greatly by associating themselves with partners that have invested in such capabilities.

Looking ForwardTo experience the full potential of analytics, we advise companies to consider the following:

• Identify key areas for deploying analytics.

• Enter into relationships with partners capable of providing AaaS.

• Design a comprehensive strategy for the adop-tion and implementation of analytics.

• Develop an enterprise-wide data architecture.

• Formulate customized strategies to capitalize on unique data.

• Develop a fact-based decision-making culture focused on achieving specific goals.

• Continuously refurbish and renew the organi-zation’s analytics implementation.

Barriers to Using Social Media Data Effectively

Figure 2

n = more than 650 marketing professionals from companies and agencies across North America and Europe.

Source: Econsultancy and Adobe, September 5, 2012

0% 10% 20% 30% 40% 50%

Lack of Tracking Capabilities and Analytics

Social Data Stored in Disparate Tools

Social Analytics are Separate from Multichannel Analytics and Business Intelligence

No Budget/Lack of Buy-in from Top of Organization

Lack of Resources to Make Sense of Data

Organizational Silos/Lack of Joined-up Thinking

General Lack of Engagement with Social Media

Lack of Awareness About Opportunities

Nothing is Preventing

AgenciesCompanies

Footnotes1 “Social Networking Reaches Nearly One in Four Around the World.” eMarketer, June 18, 2013.

http://www.emarketer.com/Article/Social-Networking-Reaches-Nearly-One-Four-Around-World/1009976

2 “Experian Marketing Services Reveals 27 Percent Of Time Spent Online Is On Social Networking In 2012.” Prnewswire, April 16, 2012. http://www.prnewswire.com/news-releases/experian-marketing-services-reveals-27-percent-of-time-spent-online-is-on-social-networking-in-2012-203209121.html

3 “Global Consumers’ Trust In Earned Advertising Grows In Importance.” Nielsen, April 10, 2012. http://www.nielsen.com/us/en/press-room/2012/nielsen-global-consumers-trust-in-earned-advertising-grows.html

4 “Big Content: The Unstructured Side of Big Data.” Gartner, May 1, 2013. http://blogs.gartner.com/ darin-stewart/2013/05/01/big-content-the-unstructured-side-of-big-data/

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5 “Data-Rich and Insight-Poor: Marketers Planning to Turn Information into Intelligence in 2013.” Infogroup.com, 2013. http://lp.infogroup.com/Global/FileLib/Infogroup_Targeting_Solutions/Data-Rich_and_Insight-Poor_Survey_Findings_from_ITS_and_Yesmail.pdf

6 “Socially Devoted: The Next Generation of Customer Care is Social.” Social Bakers, July, 2013. http://www.tnooz.com/wp-content/uploads/2013/07/soc-dev-q2-infographic1.png

7 “Retail Case Kesko: The Evolution of Kesko’s Customer Experience Using Etuma’s Free-form Text Feedback Analysis Services.” Etuma, July 6, 2013. http://www.etuma.com/evolution-of-kesko-cus-tomer-experience-using-etuma-feedback-analysis/#more-1509

8 Klout allows users to measure their online influence. It currently tracks user activity around seven social media sites such as Twitter, Facebook, Instagram, etc., and assigns a Klout Score, a number between 1and 100. Higher Klout Score represents greater influence.

9 “Putting Social Media to Work.” Bain & Company, 2011. http://www.bain.com/Images/BAIN_BRIEF_ Putting_social_media_to_work.pdf

10 “Examples of Social Media Command Centers for the World’s Largest Brands.” Salesforce Blog, December 5, 2012. http://blogs.salesforce.com/company/2012/12/examples-of-social-media-command- centers-for-the-worlds-largest-brands.html

11 “Social Media Command Centers Built For Brands Not NASA.” Intelligent HQ, May 6, 2013. http:// www.intelligenthq.com/social-media-business/social-media-command-center/

12 “Super Bowl First: Social Media Command Center.” Today, January 23, 2012. http://www.today.com/tech/super-bowl-first-social-media-command-center-84788

13 “Learning From a Super Bowl’s Social Media Command Center.” Social Media Today, February 1, 2013. http://socialmediatoday.com/adam-chapman/1205706/learning-super-bowls-social-media-command-center

14 “Social Media Isn’t All Marketing.” Monkeydish, June 17, 2013. http://www.monkeydish.com/ideas/ articles/social-media-isn%E2%80%99t-all-marketing

15 BPaaS refers to the provision of business services encompassing underlying IT infrastructure, platform and skilled manpower, to run specific business processes within a virtual, globalized and distributed operating model.

Bibliography• “Customer Analytics in the Age of Social Media.” TDWI Research, 2012. http://tdwi.org/research/

2012/07/best-practices-report-q3-customer-analytics-in-the-age-of-social-media/asset.aspx

• “Who’s Sharing My Brand Images? Why Text-Based Social Media Monitoring Falls Short.” Adota, May 16, 2013. http://www.adotas.com/2013/05/who%E2%80%99s-sharing-my-brand-images- why-text-based-social-media-monitoring-falls-short/

• “The Social Economy: Unlocking Value and Productivity through Social Technologies.” McKinsey & Company, July, 2012. http://www.mckinsey.com/insights/high_tech_telecoms_internet/the_social_economy

• “Adobe Social Unveils Predictive Publishing for Facebook.” BusinessWire, April 24, 2013. http://www.businesswire.com/news/home/20130423006871/en/Adobe-Social-Unveils-Predictive-Publishing-Facebook

• “Social Media Analytics Software Pulls Useful Info Out Of Online Muddle.” SearchBusinessAnalytics, 2013. http://searchbusinessanalytics.techtarget.com/feature/Social-media-analytics-software-pulls-useful-info-out-of-online-muddle

About Cognizant

Cognizant (NASDAQ: CTSH) is a leading provider of information technology, consulting, and business process outsourcing services, dedicated to helping the world’s leading companies build stronger businesses. Headquartered in Teaneck, New Jersey (U.S.), Cognizant combines a passion for client satisfaction, technology innovation, deep industry and business process expertise, and a global, collaborative workforce that embodies the future of work. With over 50 delivery centers worldwide and approximately 164,300 employees as of June 30, 2013, Cognizant is a member of the NASDAQ-100, the S&P 500, the Forbes Global 2000, and the Fortune 500, and is ranked among the top performing and fastest growing companies in the world.

Visit us online at www.cognizant.com for more information.

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Credits

Author and Research AnalystVinaya Kumar Mylavarapu, Cognizant Research Center

Subject Matter ExpertAmit Shah, Manager, Cognizant Social

DesignHarleen Bhatia, Design Team LeadSuresh Satyavarapu, Designer