Paul & Monica- The Integration of Social Media Content into Competitive Intelligence Modeling4

19i am scip Vol. 3 | Issue 2 | July 2016
THE INTEGRATION OF
SOCIAL MEDIA CONTENT
>> The Integration of Social Medial Content Into Competitive Intelligence Modeling
INTO COMPETITIVE INTELLIGENCE MODELING
Monica Angelova & Paul Santilli

communication (as Web sites for social networking
and microblogging) through which users create online
communities to share information, ideas, personal
messages, and other content (as videos)” 1
For CI applications, this is rather bland. But there are some
valuable nuggets here, “creating online communities to
share information, ideas, and other content.” This is really
where a CI professional can “exploit” the usefulness of
SoMe and to harness the power for real CI applications.
Similarly, McKinsey suggests that, “social media should
help companies overcome some limits of old-school
intelligence gathering, which typically involves collecting
information from a range of public and proprietary
sources, distilling insights using time-tested analytic
methods, and creating reports for internal company
“clients” often “siloed” by function or business unit.”2
This is helpful, but it is not necessarily detailed enough
to provide direction and clarity on incorporating a
methodology to include in the model of a CI practitioner.
To be really useful to an organization, one has to go
beyond this “theoretical academic” application and move
towards an ideology of creating an environment that
successfully implements SoMe techniques to gather the
rightdata,realtime,thatleadstomakerecommendations
used to ultimately grow an organization’s revenue –
anything less than that is simply unacceptable!
In academia, the need to establish sound Social Media
relation with CI has also been noticed. According to
Ruben Arcos, Professor from Rey Juan Carlos University,
Spain, “The information and communication technology
revolution challenges organizations of all kinds,
including those focused on the gathering, analysis,
and dissemination of information, knowledge, and
foreknowledge for decision making. All sectors and
industries, including the traditional ones, are challenged
and need to adapt to this new digital era that also brings
great opportunities to those that recognize them at an
early stage. From the perspective of a customer-focused
organizations Social Media brings great opportunities
for listening, understanding, engaging, anticipating with,
and satisfying the needs of customers and prospects. It
also entails big challenges for evaluating the information
and interactions coming from Social Media user’s
accounts. Establishing sound Social Media information
evaluation processes is key to avoid misinformation
Practically everyone today uses Social Media (SoMe)
in some way, shape, or form. Facebook has 1.5 Billion
subscribers, Twitter has 500 million registrations,
LinkedIn has 450 million users, Instagram has 400 Million
active participants - and they are all growing in size,
capability, and global presence. People claim that
SoMe improves their social awareness on issues, keeps
them in touch with friends / colleagues, and provides
them immediate feedback on their views of issues,
products, services, and even on global events. But ask
any Competitive Intelligence (CI) professional if they
think SoMe is important to their environment, the answer
would be that it is certainly important, but many have
not yet figured out how to harness the real value from
the capability and user community.
Unfortunately, many of us CI practitioners still live in
an era where we collect data, analyze the data, and
make recommendations based on “batch processing”–
this process is done in “batches” of information that
takes weeks / months to process and analyze before
any recommendations can be made. Unfortunately, the
subsequent actions being taken on this data is now many
months out of date and may or may not even be relative
to the issues first identified.
We live in a world addicted to “immediate gratification.”
The internet has brought that phenomenon into existence
– any information you want is immediately available at
the touch of a button. Having to wait more than a few
seconds for an answer to a question is unacceptable
in both social and professional applications. Certainly
revolutionary and world changing, but the real value
is how to harness that information so you can make
revolutionary decisions within your organization “real
time.”
Harnessing the power of SoMe into the CI methodology
is key in processing analytics “real time,” leveraging
off of an internet-based infrastructure, and ultimately
staying ahead of the game in delivering timely industry
and market-relevant actions for your organization.
DEFINITION IS KEY
So where to begin? Well, it is probably best to identify
the general definition of what SoMe is:
Merriam-Webster defines it as “forms of electronic
The Integration of Social Medial Content Into Competitive Intelligence Modeling <<

According to Tina Bundgaard, Corporate Market
Intelligence Manager at Rockwool International, “Social
Media as an integrated part of the intelligence function
and work is only starting to fly amongst larger Danish
companies.” Bundgaard shares that in Denmark they
are still relying on more traditional information sourcing
channels, without knowing how to fully exploit the
Social Media possibilities. While companies use Social
Media for branding, customer relations and posting, it
is still limited, Bundgaard says, “for Market Intelligence
functions, it’s a highly unexploited field both in terms of
obtaining competitor information as well as sourcing
information in general.”
Lastly, Arcos from Spain sums up, as stated before
(Arcos 2015), “Social Media Intelligence can provide
both companies and public institutions with analysis
and recommendations in order to plan, execute, and
evaluate their strategic communication campaigns.
Listening, capturing and communicating the attitudes
and opinions of publics toward organizations are
commonly recognized activities of the PR function.
When conducted under an anticipatory logic or by using
competing intelligence, PR can detect problems early as
well as point out opportunities for business, non-profits,
and governmental agencies. Some companies are using
in this environment, to detect and counter campaigns
against our brand and reputation. Organizations that
produce sound open source intelligence analysis rely
on systematic systems to evaluate the reliability of their
sources according to different criteria. Social Media
Monitoring and Intelligence needs to establish similar
processes.”
GLOBAL IMPLICATIONS
Globally, the situation with integrating business and
social media research is common in many places
worldwide; there has been some identification on steps
that need to be taken within various country parameters
in order to properly integrate them. However, there are
specific country implications that can require a different
methodology. For example, according to Christophe
Bisson, PhD, President of the Internationally Accepted
Marketing Standards, “Further researches on Social
Media Intelligence in Turkey need to be done to evaluate
their practice levels, thereby allowing them to make some
improvements for competitive purpose. Furthermore,
there is no text mining working yet for Turkish language
in spite of recent improvements. Therefore, sentiment
analysis is done manually.”

supporting primary research studies and creating
actionable recommendations based on the
triangulation of sources
supporting data when you are unable to make an
actionable recommendation and need additional
information
supporting primary research tracker studies where
the data collection methodology has been changed
or respondent profile has been altered
The examples are numerous, with the outcome to be able
to clearly analyze the enormous amounts of data to
arrive at the desired result. However, the reality is that
there is much information available online which needs
to be synthesized in a systematical manner. As a result,
intelligence professionals tend to ignore the power of
Social Media and thus ignore valuable data.
ANALYTICS PROCESS
Realistically speaking, it will be a challenge for all
companies to be fluent at integrating Social Media
content into their research. However, there is a tested
approach of how to successfully leverage social media
for analytical and CI purposes in particular. There are 3
steps you should take in this approach:
Identify the question(s) that you are trying to
answer and based on those questions identify the
needs that you are trying to fill.
Determine the sources of information that you are
going to use, e.g. which Social Media channels are
you going to be collecting the information from?
What other sources of information such as various
professionals blogs and forums are you going
to study? (This may include either existing SoMe
channels, or new access areas that you can develop
to generate content useful to your analysis.)
Synthesize and organize the information in a
structured and meaningful way. After processing
the data, it needs to be carefully analyzed and
the information needs to go through a process
of triangulation with other sources and primary
studies. Based on that triangulation, actionable
recommendations can be made.
social media for detecting new needs and launch new
products to satisfy those needs. Social Media Intelligence
can drive business and product innovation.“
Subsequently, even though global requirements might be
similar at a high level, regional and country integration
aspects can have varying entry points, multiple
maturation levels, and require different implementation
and integration methodologies to fulfill the objective.
Therefore, one has to be cognizant of these issues in
order to be successful at maximizing SoMe usage and
realizing an effective return on investment.
SoMe USAGE FOR CI PURPOSES
From a CI perspective, there are 2 main ways to gather
information via SoMe for a certain subject:
1) Collect existing content already there
2) Generate content that doesn’t exist
This might include tapping into some of the already
established vehicles that are out there while also creating
new “data pull” mechanisms to generate useable
information that is applicable to your business need.
The key is to make this seamless and streamlined so that
it is process-driven, rather than an ongoing exception
management effort.
Particular examples of various scenarios when social
media research can be leveraged include but are not
limited to the following:
gathering information on competitors who have not
previously been on your radar screen
gathering information on competitors who have been
a Tier 3 competitor but are becoming a Tier 2 or even
a Tier 1 competitor and you don’t have prior research
on them
gathering information on existing competitors to
support currently existing data
gathering information on competitors who are
considered too small to be included in industry reports
supporting strategy meetings and decision-making
processes in cases of industry disruption when there
is not enough time to generate data from a primary
study
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1)
2)
3)

Crowdsourcingtechniquesthatpolllargepoolsof users
/ customers / industry stakeholders to gather relevant
information about your investigative requirements.
Various surveying tools on a large group scale that
can provide detailed information related to your
business, competitors, and industry trends.
Trolling and monitoring many existing SoMe channels
to understand market implications, the effects of
business disruptors, corporate positioning, as well
as regional and geographic implications related to
emerging markets and mergers & acquisitions.
Leveraging and becoming fluent in the capabilities
that reside in existing social media channels for both
social and professional organizations. Some of these
are readily available, while others can be customized
(for a fee) to your specific business need.
Generation of SoMe mechanisms / customized
approaches to further supplement what is already
available in SoMe channels.
Which SoMe capabilities are best in your organization?
Depends on the data you are trying to acquire and the
objective you are attempting to fulfill. Whatever the
case, there are many different tools that can be utilized
that will offer varying levels of the quality and quantity
of information that will contribute to the value and
usefulness towards your CI efforts. The challenge is to
understand which methods will yield the best results, and
to determine the appropriate structure to employ to get
the best data to supplement your CI efforts.
Given all these facts, how do we use SoMe data wisely
to the benefit of the profession and the companies which
we are supporting?
Some examples are provided, but there are many
others that are available and should be researched and
analyzed for applicability for your needs:
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still kernels of information that might prove to be useful
– therefore, one must exhaust all collection methods
available; “some data is better than no data .”
Additionally, there could be implications related to
company policy and Standards of Business Conduct, in
terms of intelligence collection methods and how SoMe
is used in various applications. This can also hamper
overall collection and analysis techniques.
It is clear that in terms of information availability,
communications, and exchanging of ideas, coupled
with the proliferation of data as a whole, the world
has gotten very small, complex, and confusing! But this
does not have to be viewed as an overwhelming and
daunting task for CI practitioners. The good news is
that there are tools and techniques out there that can
manage and organize information stemming from the
Data Revolution. Focusing on these 3 areas can be useful
in integrating SoMe into your CI methodology:
Be crystal clear in the objective and desired
outcome of your investigative effort. This should
tie directly into the overall specific CI goal for your
organization.
Evaluate and determine the best SoMe tool(s) that
can gather the relevant data, either from existing
standard mechanisms or from customized tools
and source content.
Develop a process that allows this SoMe intelligence
gathering to occur ongoing – the benefits here are
the virtually instantaneous nature of the timeliness
of the data as well as the ability to collect it in
large quantities.
Integrate this data with your current CI analytics
to complement and enrich the quality and quantity
of the information you generate in order to make
better and timelier business decisions.
SoMe should be leveraged for research purposes as it
offers abundant information which businesses need to
be aware of. From competitive intelligence to customer
insights, there is valuable information which can be
generated by carefully analyzing the Social Media
channels. Nowadays, intelligence professionals are
already discussing the mobile customer journey, the non-
Additionally, as analysts when we think of Social
Media we tend to focus textual content, as that can
clearly generate data which will assist us in making
recommendations; there are numerous tools that
automatically collect SoMe text in a short amount of
time. Keyword analysis provides a strong foundation
for verbatim coding of vast amounts of text. (Another
possible textual way to track SoMe attitudes is through
twitter #hashtags.)
However, a major component of social media that is many
times ignored are the visualizations content. Besides,
a lot of the information shared on SoMe is indeed
pictorial. According to Jesse Mawhinney in the article, 37
Visual Content Marketing Statistics You Should Know in
2016,“65% of senior marketing executives believe that
visual assets (photos, video, illustrations and infographics)
are core to how their brand story is communicated.”3
What makes it complex for the intelligence professional
is that images are hard to analyze. The hardest part is
to summarize vast amounts of images into meaningful
content that would add to a CI database. While it is
not impossible to analyze such content manually, the
chances for bias in the analytics increases.
For example, there are some extremely influential
brands on Instagram (a platform which relies on pictorial
content). Video content can offer extremely powerful
competitor insights as well. Public video content can be
found online on YouTube, Instagram, Facebook etc. in the
form of sales videos, webinars, educational short clips
and more.
Determining the best method to analyze large amounts of
pictorial information is a challenge in many organizations
as automated processing tools are difficult to implement
and unreliable in capturing and segmenting all relevant
data. Further advances in this area are necessary to
further exploit comprehensive image data collection
efforts.
Lastly, many of the approaches and methodologies
mentioned here are subject to the regional and
geographical implications and restrictions that might
apply, with respect to the availability of certain SoMe
channels as well as the usefulness of the data. This can
provide further challenges to the collection and analysis
efforts. Of course, intelligence accuracy is compromised,
but shouldn’t be dismissed in its entirety as there are
1)
2)
3)
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traditional ways and approaches of collecting
data. Moreover, more and more companies
realize the need to complement the traditional
with the non-traditional and more innovative
data.
Being aware of what is available out there about our
own companies and our competition is a must. Social
Media can be used in strategy as a warning mechanism
to protect your business from competitors, to grow your
business, and to plan your business according to the
voice of the customer.
(Merriam Webster’s). Retrieved May, 2016, from http://www.merriam-webster.com/
Harrysson, M., Metayer, E., & Sarrazin, H. (2012, November). How ‘social intelligence’ can guide decisions. Retrieved April/May, 2016,
from http://www.mckinsey.com/industries/high-tech/our-insights/how-social-intelligence-can-guide-decisions
Mawhinney, J. (2016, January 13). 37 Visual Content Marketing Statistics You Should Know in 2016. Retrieved April/May, 2016, from
http://blog.hubspot.com/marketing/visual-content-marketing-strategy#sm.00016j7uww2xxeorrp321sec63hbv
ABOUT THE AUTHORS:
Monica Angelova is the Founder and Managing Director
of Intelligence Pathways. She has extensive international
experience in consulting, business intelligence and
marketing research. Her work stretches over a variety of
industries among which healthcare, media, government
procurement and IT. A proven team leader and business
development professional, Monica has built, managed
and lead teams of experts working on multinational
assignments. She has experience in consulting companies
on strategic outsourcing initiatives and thus helped the
clients to increase revenues by lowering costs. Monica
understands every detail of back office outsourcing
support and has the knowhow of implementing it on
an international scale. She holds an M.B.A. from the
University of Maine, USA.
PaulSantillileadstheBusinessIntelligenceandCustomer
Insights organization for Hewlett Packard Enterprise’s
(HPE) WW OEM Business, and has been with HPE for
20 years. He is responsible for Business and Competitive
Intelligence Modeling and Customer Insights analytics,
where he is the Chairman of HPE OEM Executive
Customer Advisory Boards worldwide. Paul also is on the
Strategic Competitive Intelligence for Professionals (SCIP)
Board of Directors and has presented worldwide on
various topics related to CI in both keynote and workshop
forums. Paul has a Bachelor’s degree in Engineering from
the University of Michigan, and a Master’s degree in
Engineering and Business from Stanford University.
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