1. 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
2. cognizant reports 2
Executive Summary
With 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 Forces
The Rise of Social Media
According 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 Content
Many 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 Data
According 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,
3. cognizant reports 3
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
4. cognizant reports 4
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.
5. cognizant reports 5
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%morethanothercustomers,revealsaBain
& 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 Shop
A 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
6. cognizant reports 6
• 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 Analytics
Social 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.
7. cognizant reports 7
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 Service
Analyzing 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.
8. cognizant reports 8
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 Forward
To 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
Footnotes
1
“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/
9. cognizant reports 9
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.
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