This article gives analysts some tips on how to formulate meaningful insights derived from careful planning, organizing, and contextualizing of available data from various social media channels.

1. Social Media Analytics:
Contextualizing Data for Meaningful Insights
Virginia B. Bautista, Quality Control (QC) Team Lead
iSentia Brandtology
February 2014

2. Figure 2
Providing online intelligence is a serious business. Analysts constantly deal with tons of unstructured data waiting
to be discovered, interpreted and communicated. At first glance, the contents of social media conversations seem
nothing new – similar types of voices surface on a daily basis: complaining, complimenting, announcing, liking,
sharing, asking, seeking advice, or simply commenting for the sake of commenting. Many times, social media
chatter seems more like noise than conversation, and hence, does not warrant any attention.
The challenge for analysts is how to avoid simply dumping data on PowerPoint slides. How can analysts translate a
huge amount of data to actionable insights? How should they frame stories to guarantee that companies would
make logical decisions using online intelligence? The secret is with the context, and with big data, context is big
deal.
This article gives analysts some tips on how to formulate meaningful insights derived from careful planning,
organizing, and contextualizing of available data from various social media channels.
How to Contextualize Data for Meaningful Insights
Making Relevant Comparisons
The amount of buzz about a brand
will not make much sense without
relevant comparisons. For
example, if Brand A garners 1,758
buzz on December, what does that
mean? Its significance can only be
explained with proper
comparisons, so we also look at
Brand A’s Share of Buzz (SOB)
compared with its competitors
and compared against the entire industry. If the closest competitor
has about 4,000 buzz, then Brand A is quite behind (Fig 1). If the
industry buzz is more than 20,000, then Brand A is nowhere in
consumers’ minds (Fig 1 and 2). In short, the number of buzz alone,
without an analysis of the brand’s competitive and industry
positioning, does not yield anything meaningful.
Figure 1

3. Figure 4
Figure 3
Figure 5
Analyzing Trend
Certainly, discovering consumer insights for
the current month is good (Fig 3). Looking,
however, at top conversation themes about
a brand or industry throughout the last 3 to
6 months or from the previous year to date
is a smart move (Fig 4). Through month-on-
month, year-over-year or year-to-date
analysis, analysts can help companies
predict the next big thing in the industry. By
understanding the key conversations in the
past and the
current events that
trigger buzz,
companies are
certain to make
informed decisions
for the future.
Correlating Key Social Metrics
Having the largest SOB against industry
competitors is not a reason for a company
to automatically rejoice. For proper
context, Social Buzz could be correlated
with Social Sentiment and Social
Engagement.
The most favorable market position would
be to have the largest SOB, and the
highest net sentiment (Figure 5). A lot of
netizens talking about a brand could be an
indication of the need for prompt action if sentiments are negative. Equally important is the
engagement vis-à-vis buzz. Is the buzz concentrated among few voices? How many people like, share
or comment on Brand A’s social media posts? Which particular posts across brands’ social assets
resonate the most with fans or followers?

4. Figure 6
Analysts should be able to identify the top
themes, the key positive and negative
sentiment drivers, especially those that
need Brand A’s attention, and the type of
posts that are likely to lead to high
engagement. The findings may not
highlight causal effect, but correlational
relationships between and among buzz,
sentiments and engagement could be
established for deep dive analysis.
Analyzing Channels
At times, what netizens say is
as important as where they
share their views. Instead of
simply finding out the top
channels where Brand A is
mentioned, analysts should
contextualize by looking at how
social media conversations on
particular channels start, and
how other netizens react to the
points raised by the thread
starter. Examining and
comparing top channels across
competitors and in the industry could also bring new perspectives. For example, is Brand A discussed
in major industry channels where most netizens exchange their views on top brands and issues? In
channels where netizens compare and contrast brands, insights could also be extracted based on co-
mentions and frequently cited attributes within the industry (Fig 7).
Discovering Patterns in Social Asset Performance
Aside from listening to social
media conversations, analysts
also have to be adept in
observing how brands and
their competitors make use of
their social assets, e.g. on
Facebook, Twitter, Sina Weibo,
etc. Among the aspects that
could be unveiled include:
Figure 7
Figure 8

5. Figure 9 Figure 10
Figure 11
How does Brand A fare compared with its competitors in terms of fan size and growth?
Which Facebook posts are likely to gain high social engagement? (Fig 8)
At what time do Brand A and its competitors post updates on its social assets?
At what time are the netizens most likely to comment on or retweet the brands’ posts? (Fig 9 and 10)
How often and how soon do Brand A and
its competitors respond to consumers’
posts/inquiries on its own social assets?
(Fig 11)
What is Brand A’s shelf life and half-life?
The insights to these questions could help
companies make informed decisions on
the best time to post on their social assets, on how often to post updates, and on how soon to respond
to consumers’ queries, etc. Without knowledge on how best to use social assets, getting the message
across would seem impossible.
Identifying Key Opinion Leaders or Influencers
In many instances, the choice of
comments or insights to highlight
depends not only on the relevance of
posts, but also on the sources of buzz. Is
the netizen a key opinion leader (KOL) or
influencer in the industry? How does that
KOL impact engagement rate of Brand A’s
posts? Identifying KOLs provides
companies a basis in deciding whether to
engage KOLs or not, for what purpose,
and how it could be effectively done.

6. Decoding Native Language
Netizens do talk to each other using their mother tongue. Extracting
insights without decoding native languages including local jargons, can
lead to misleading findings. Analysts are ideally native speakers of a
particular language who can read between and beyond words and can
make sense on whether the netizens are being sarcastic in their posts,
or if they are sincere. With language context, companies are assured
that analysts consider critical factors distinct to a language, e.g. local
expressions and tones in the formulation of insights.
Adding Business Sense
With so many
conversations going on
in real time across
various social media
channels, choosing the
right insights to highlight
is crucial. Analysts have
to be aware that insights
are meant to be utilized
in businesses’ success in
the industry. With clear
understanding of how
businesses work and
how various industries
operate, combined with
knowledge in related fields like marketing, business development, branding, public relations (PR),
advertising, public governance, and customer service management (CRM), analysts could add business
sense in how they collect essential information to translate to actionable insights. By wearing a
‘business hat’, distinguishing useful insights from mere noise could be less tricky.
Zooming in on Demographics and Psychographics
For insights to be utilized effectively for well-targeted marketing efforts, zooming
in on demographics or psychographics vis-à-vis key metrics like buzz and
sentiments is a useful strategy. Information on netizens’ demographics including
age, gender, location, etc., and psychographic descriptions including values,
attitudes and behaviour can provide a lot of opportunities to target the right
market segment.
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