Utilizing Social Media to Understand People

Utilizing Social Media to Understand People

Utilizing
Social Media
to
Understand
People
by
Josh Gunkel
Ben Smithee
Tom Brailsford
3.30.11

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Utilizing Social Media to to Understand People
Utilizing Social Media Understand Consumers

The purpose of this document is to present the findings of Hallmark’s Social Media Research Team,
in conjunction with their collaborators. It will provide an overview of key concepts and learning, as
well as a more detailed provision of how to utilize social media as a research tool.

Social Media as a New Data Source
For Understanding People
At its heart, Market Research can be characterized as “listening” to the market/consumer. Though
many different tools and techniques have been used, the fundamental objective has been to un-
derstand people. In this context, it is important to recognize that even though a lot of things differ
about it (some of which will be discussed in this paper), social media represents a new source of
data from which we can try to understand our consumers and people in general.

There have been many articles, white papers, books and blogs written on the topic of Social Media,
and specifically on the topic of Social Media Research (SMR). Various forms of nomenclature fill the
pages, and most of the content revolves around high-level thoughts and theories. This paper will
attempt to answer the questions:

• What is social media, and how are people using it?
• How can social media data be used to understand consumers?

Social Intelligence
When social media data is used (blogs, communities, social networks, etc.) by research analysts and
others to understand people, it is often called Social Intelligence. In the Forrester Research report,
“Defining Social Intelligence”, it is further defined as:

“The use of social media and tools to gain increased access to, and insights from,
a company’s target segment in a way that adds value and depth to the research-
er’s overall responsibility as an expert on the voice of the customer.”

We recommend analysts take a step back and obtain a foundational understanding of social media
data before pursuing social intelligence about people.

Note that throughout this paper break out boxes will be used to give:

1. Ideas of using social media data for social intelligence (denoted Social Intelligence)
2. Examples of using social media data (denoted Example)

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Foundational Components of Social Media
The generic term “social media” is often used to describe the ways in which digital tools and plat-
forms have enabled people to connect with others; publishing thoughts, ideas, needs, experiences

EXAMPLE
or anything else they choose to share. This primarily occurs
via public and/or private platforms such as blogs, social net-
works, communities and other forms of sites that contain user-
Facebook: Primarily private but increasingly public
generated content. In the public platforms, the content and
Twitter: Primarily public but has private components
behavior of participants is viewable by anyone that visits or
Blogs: Primarily public but private blogs are common
views the site. In the private platforms, content is only acces-
Communities: Both public and private communities
sible via login, membership or permission.

When people refer to social media, they are often just thinking about the sites that enable shar-
ing like Facebook, Twitter, YouTube, etc. This, however, is possibly too narrow a view. It is easy to
think of social media as a fad that will go away from this view
point, because these sites tend to come and go at an incredible
rate. Our recommended way to think about social media is to
EXAMPLE
take a step back, and think about the elements and behaviors Friendster and MySpace both had their period of leading in the
that define the social media space instead of the sites that it is social media space, but have quickly faded out.
comprised of.

Elements of Social Media
Social media platforms/sites can be broken down into four different main components (Papercliq):

Profile – Where users populate their given personal page with
information about themselves. They can fill in information
SOCIAL INTELLIGENCE
such as their name, birthdate, gender, interests, etc. Use profile information and connections to know more about
the author of a blog post or tweet.
Connections – How people and things are connected in the
social space. These connections are commonly represented Within Facebook Insights an analyst is able to see a wide range
as friends, fans, followers, likes, etc. of information about a sites’ fans such as demographics, en-
gagement trends, etc.
Content – What people create when participating in social me-
dia. Their content is the manifestation of their thoughts and

SOCIAL INTELLIGENCE
feelings as words, pictures, and videos.

Environment – Where profiles, connections, content and con-
The environment can tell the analyst a lot about the content.
versations take place. The environments can be communities,
For instance, blogs tend to be longer and more thought out
social networks, blogs, etc. Environments are often called
and reflecting back. Tweets within Twitter are shorter and
platforms or channels.
more stream of conscious.

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Behaviors of Social Media
Another point of interest surrounding social media relates to what people are doing there. What
appears to be a whole new set of behaviors within this space can be boiled down to five “real world”
behaviors that are manifested, or enabled, digitally: (paulisakson.com)

Creating – People create various kinds of digital content to express their thoughts; share a creative
talent or passion; and even review products, brands and services.

Sharing – People share things they find interesting or impor-
tant with friends, family and followers. This popularly takes
SOCIAL INTELLIGENCE
the form of ReTweets, Likes, Status updates, and checking in. Looking at what people create, share, and connect with gives a
good view into what is important to them. It becomes part of
Connecting – People use social media to connect with others their digital identity.
who share similar interests, values, and beliefs. The use of
social media for marketing, advertising, market research and
other business functions has also added a new form of connectivity between brands and people due
to the added context provided by social media content (e.g. historical data, check-ins, likes, dislikes,
favorites, etc.).

Collaborating – People turn to social media to collaborate with others in the digital space, because
of the enhancements provided by many applications and channels. Users can collaborate on com-
mon tasks and work functions in a single online environment (e.g. Facebook, Wikipedia, Google
Docs, Basecamp etc.).

Consuming – People constantly consume information across all forms of social media for multiple
purposes (e.g. learning, entertainment, connectivity, etc.) through channels such as YouTube, Hulu,
blogs and Flickr.

Through these behaviors - the social space has grown beyond just being what people ‘say’. It now
encompasses where they go, what they see, eat, do, think and feel…

Types of Social Media Data
Through combinations of these elements and behaviors, the social media data begins to takes
shape. The data available can be broken into seven different types (Jeremiah Owyang):

Demographic – Who are these people who put all sorts of in-
formation about themselves on their profile pages? Depend-
SOCIAL INTELLIGENCE
Use demographic data to provide context around the social
ing on the site - information about where they live, what their
media content and content creators.
hobbies are, race, political affiliation, etc. fall into this category.

Product – What brands, products and services do they men-
tion? Specifics about these things are frequently mentioned
within content created by people online, both positively and
SOCIAL INTELLIGENCE
negatively. This is a window into how people feel about com- Specific keywords, like brands and product names, are a good
panies and the things they offer. gateway into social media data.

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Psychographic – How do they think and feel? Personality, val-
ues, attitudes, etc. are the intangible things that describe peo- SOCIAL INTELLIGENCE
ple. Before social media, understanding the psychographics of Within social media data, psychographic information can be
a person was through survey projects like Prism. Now people inferred by the words people use to describe their thoughts,
are talking about it online. feelings and actions. Try using negative sentiment as a way to
filter comments to what people are frustrated with.
Behavioral – What are people doing? Two of the common
ways to understand people’s activities through social media

EXAMPLE
are analyzing what they talk about, and looking at web analyt-
ics for online behaviors and trends.
Web analytics track what people do online. The sites they visit,
Referral – What do people suggest? These are customer rat-
how long they spend, etc. For social media data, this expands
ings or reviews. Sometimes these are on the specific site to
into # of comments, retweets, embedding videos, etc.
which the rating or review is focused (e.g. Amazon, Netflix,
Levi’s). They can also be published within the personal envi-
ronment of the author (e.g. blog post or status update).

Location – Where are they? This is behavioral data about the SOCIAL INTELLIGENCE
“now.” Location is not as widely available yet, but with the Use the location criteria within search tools to isolate posts
rise of mobile technology and GPS applications this will be an within a geographic region (e.g. search.twitter.com).
important data element in the future.

Intention – What are they planning to do? This data is a declared future state and often unreliable,
but can be a valuable indicator for understanding people’s initial motives or direction. Where be-
havioral data is about what people did in the past and location data is about what people are doing
now, intention data is about what people want to do in the future.

Who are the People Contributing
to Social Media?
It is important to note that not everybody is using social media in all the ways described above. Ad-
ditionally, there are varying levels and types of participation; Forrester describes them using their
quarterly Social Technographic Survey. Based on responses, people are grouped into Creators, Con-
versationalists, Critics, Collectors, Joiners, Spectators, and Inactives.

The Q4 2009 survey results showed 83% of US Online Adults
use social media on some level (i.e. not Inactives). Note, this
does not represent the percentage of people creating the con-
SOCIAL INTELLIGENCE
tent, because a large portion are only spectators. Over the Use Forresters free social technographics tool at
past few years that Forrester has been tracking these Social forrester.com/empowered/tool_consumer.html
Technographic profiles, the percentages have all been increas-
ing.

In addition to these user segments, the big three social sites right now are Facebook with over 600
Million users, Twitter with over 75 Million Users, and LinkedIn with over 50 Million users (all world-
wide). About 30% of the Facebook users live in the United States and around half of them log on

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everyday (PEW). Blogs and online videos (e.g. YouTube) also hold a very large portion of the content
created online.

Social media is rich with potential for all divisions of the company, but at the same time, it is not a
silver bullet. As research analysts, it is important to ask the question:

Do we feel like we can learn about our consumer through the people who are
participating in social media and creating its content?

It should be clear that by ignoring social media data, the analyst will be missing a large piece of
consumers’ lives. Our recommendation is social media data should be considered when trying to
understand people, their actions, and their expressed thoughts and opinions.

How Social Media Data can be
Utilized to Understand People
Now that the foundational elements of social media have been described, the next step is to un-
derstand how to leverage it to obtain insights and understanding. There are three main divisions of
research activities that affect how and why you utilize social media data to gain social intelligence
(about people). They are Listening, Engaging, and Measuring.

Listening
Listening to people through social media, commonly referred to as “monitoring”, provides an ad-
ditional means of hearing what people have to say. It is also the best place to start understanding
people through social media.

Listening within social media tactically refers to searching for key words or phrases in social media
channels, and then reading/watching/listening to the responses that result from the search. The
two primary ways to search the social space are to start with the keywords, or with author cat-
egory (e.g. interest, life stage, subject, etc.). Keywords are the
easiest and most common form of searching through the data.
Starting from an “author category” will eventually become a
EXAMPLE
powerful tactic - it is currently still taking shape from a techno- Search mommy blogs to learn about moms.
logical standpoint.

Through listening within social media platforms, researchers can obtain verbatim opinions, com-
ments, and other instances of “consumer voice” that are shared on various social platforms and
communities. They can also obtain feedback on advertising, marketing and new product/service
offerings as they launch, and throughout the product/service’s life-cycle. Comments about brands
and products can be captured and analyzed to assist in product development as well as messaging,
copy development and positioning. Researchers can also develop customer groups, build profiles,
identify influencers and monitor key brand ambassadors/detractors. Not only can researchers ob-
tain the exact verbatim commentary, they also have the valuable ability to observe the conversa-
tions in the natural context in which they occur. Equally as valuable, they can observe and monitor

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for any lack in conversations around a desired topic.

As sources of content continue to increase, there are two ways to listen:

Native Listening – is listening within the specific social media channel(s), and is the most basic
form of listening. This process is extremely basic and easy to implement immediately. It is free and
requires no additional software or tools, but it does require a
great deal of time and human analysis. Common for many re-
searchers who are new to social media research - native listen-
SOCIAL INTELLIGENCE
ing is great for short/quick dives into social media data, rather Use Twitter search to search for mentions of your brand. Next
than for deep/longitudinal explorations and monitoring. search for your brand within Facebook to see what is said on
Facebook by everybody and also your friends.
Aggregated Listening – is listening to an aggregated set of so- How are the results different?
cial media channels through listening tools. These tools first
arrived as marketing, PR and advertising tools, used by com-
munications departments to monitor brand mentions for brand management needs. While there
are both free and paid aggregate level listening tools that can be used by an analyst, the free tools
tend to require much more human analysis.

Research companies such as Collective Intellect, NetBase and EXAMPLE
Nielsen have begun developing and launching their own re- Within one comprehensive listening platform, a researcher is
search-centric tools for social listening. Utilizing these special- able to listen to key conversations around designated topics
ized tools, researchers have the ability to use one central hub within Twitter, Facebook, Blogs and YouTube, rather than hav-
as a platform for listening to a broad spectrum of social media ing to listen individually to each specific platform of interest.
channels. These tools, although varying in range of costs, pro-
vide a valuable timesaving opportunity for researchers.

Though both forms of listening sound easy in theory, they can be very challenging. There is a learn-
ing curve to efficiently finding what you are looking for, as well as the ability to differentiate between
important and non-important data.

Listening, in and of itself, is a passive approach to learning from consumers through social media.
Because of its passive nature there are obvious short-comings, depending on your objective, as
you are limited to what people talk about on their own (unprompted). In situations that require
more than what people talk about naturally, a researcher can interact with consumers; this is often
referred to as “engaging”.

Engaging
Engaging represents the act of interacting with people in social media environments. Within the
context of this paper, engaging represents the interaction of the researcher with consumers/oth-
ers within social media. This interaction could take place as asking questions, making comments,
answering questions or other ways of contributing to any conversation. This interactive research
functionality adds a vast amount of additional opportunities and risks for researchers. Engaging can
take place in both brand- and consumer-initiated conversations.

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Brand Initiated – In this type of engagement, the original conversation is initiated by the brand as
a comment, blog post or question posted to a social media site. Users then interact with the brand
in their responses. This type of engagement is useful for obtaining feedback on specific materials,
questions or ideas that the brand may have when seeking consumer opinions.

Researchers Should Note: Topics or questions posed are generally public, and must therefore be
very careful and purposeful in the kinds of questions, topics and materials that are posted.

Consumer Initiated – In this type of engagement, the original conversation is initiated by the con-
sumer in the social media environment, and then the brand engages in potential follow-up(s). These
types of conversations are not restricted to brand-owned pages and channels.

By engaging the consumer in additional in-depth conversations and interactions, the researcher is
able to uncover additional context and understanding (insight)
about the consumer and their wants/needs/preferences. SOCIAL INTELLIGENCE
Engaging is a valuable tool for companies, including their re- When an analyst finds a conversation about a topic of interest,
search division. However, it is not as easy or clean cut as it they have the option of engaging in that conversation in order
seems. Engaging moves the researcher into the realm of Pub- to dig a little deeper. For instance, the analyst can enter the
lic Relations, Customer Care or other communications-related conversation by saying something like, “Thanks for the feed-
roles. Researchers may not necessarily be trained in these dis- back, we are always trying to make our products better. Can
ciplines, and thus should exercise extreme caution when de- you explain more about why you feel that way?”
siring to engage with consumers in public spaces. Before you
engage with consumers here are some of the things you should consider:

• Have you been trained/know the corporate social media guidelines?
• What are your objectives for engaging?
• Who else within your organization should be aware of your efforts?
• Where do you want to engage?
• Engagement is about relationship, are you planning an ongoing effort or a one time interaction?
• What kinds of incentives will be required?

Measuring
The third major division of social media research revolves around measurement. Researchers ex-
amine various metrics around social media conversations and look for key indicators and patterns
that inform research, marketing, and other business decisions.
Within social media measurement there are two categories:

Conversational Measurement – is measuring the words and
SOCIAL INTELLIGENCE
Mentions: How many times is a term mentioned? How does
phrases expressed in social media. The most common forms of that trend change over time?
conversational measurement are number of mentions, senti- Sentiment: Are comments positive, negative, or neutral in
ment trends, themes, and sources. tone? How does it change over time?
Themes: What themes characterize the conversation around
Behavioral Measurement – is measuring the behaviors or ac- the topic of interest? Note this is a more complex text analysis
tions taken by people (# of shares, # of comments, check-ins, and more likely on paid tools.
etc.), and is often closely tied to web analytics. Sources: Where are the mentions? Facebook, Twitter, blogs?

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Social media measurement is the next frontier being explored by both companies and social media
thought leaders. There are many great resources available discussing this field, such as The Social
Marketing Analytics Report (Altimeter Group), Web Analytics 2.0 (Avinash Kaushik), and Social Me-
dia Metrics (Jim Sterne).

Key Attributes and Paradigm Shifts
Key Attributes
As stated earlier, social media primarily enables in-person interactions in a digital realm. However,
there are new and unique attributes of social media that should be noted from the perspective of
trying to understand people. Some of key attributes of social media are:

• Self-selecting/Opt-in – Participants who create social media content must opt-in or choose to par-
ticipate. They may or may not represent your target consumer. They do not necessarily constitute
a “probability sample” of the population. Also, the researcher is not establishing the topic and
controlling the conversation, but rather listening to whatever is posted.

• Not recall-based – Recall data is known to be the least reliable source of data. Recall is usually
the result of some stimulus (question, prototype) that can affect what the respondent recalls (due
to priming). Social media data is less subject to recall biases and errors, as it usually represents
comments and observations made “in the moment” or shortly thereafter.

• Longitudinal and Instance-based – Whereas focus groups provide instance-based feedback/in-
sights, and bulletin boards can provide longitudinal-based insights - social media research can
obtain both formats within a single channel (e.g. Twitter, Facebook, Linkedin, or Youtube). There
is a constant stream, or flow, of social media data continually being created.

• Self-recording/Archival – Conversations, both public and private, within the social media envi-
ronment are automatically recorded and stored in perpetuity in the digital realm. Conversations
with people in traditional research methods are only recorded if desired, and are generally only
available to permission-based viewers/listeners. The public conversations that take place within
social media frameworks are automatically archived and available for others to consume at will.
This creates an interesting blend of liability and value to researchers and brands. Should some-
thing take a negative turn during conversations with people/respondents in the social realm, it is
available for public viewing. Additionally, on the opposite end of the spectrum, researchers are
able to capture insights and conversations that they have missed in the original real-time format.
They are able to “go back in time” to utilize the archived and searchable content in their findings
and analysis.

Paradigm Shifts
In addition to possessing several key attributes in regard to its utilization in market research, social
media data has been the impetus for multiple paradigm shifts in the marketing, advertising, com-
munications and market research industries:

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• Data Transparency – Social media data is, in general, public and accessible to anybody. This
includes being visible to all divisions within a company, and other businesses.

• Data Ownership – Traditionally, there has been a clear understanding of who owns particular
consumer data. For example: sales data is owned by the retail department, focus group data is
owned by research, email open rates are owned by the marketing group, etc. This is different for
social media data due to the data transparency described above. As of now, No department or
group really “owns” social media data.

• Blurring Boundaries between Research and Other Divisions – As a result of the transparency of
the data and lack of clear ownership, what remains “in-bounds” or “out-of-bounds” for a division
is blurred. Even more importantly, roles that used to be reserved for each division have now
blurred as well. Within social media, any of the divisions can utilize the same data. When it
comes to engagement, the consumer often does not clearly distinguish between whom they are
talking to when they talk to somebody from a brand or company. Everybody is speaking on behalf
of the brand. This can create new challenges for traditional research personnel.

• Control of the Environment – The researcher previously controlled as many aspects of the listen-
ing environment as possible (e.g. recruiting based on specific screening criteria). Social media
data generally comes uncontrolled, unedited, and unsolicited.

• Blurring of Qualitative and Quantitative – The once separate worlds of qualitative and quantita-
tive research are further blurred by the influx of social media data. The potential and possibil-
ity for both qualitative and quantitative researchers to utilize social media data is evident, and a
valuable benefit.

• Shrinking Space between Brands and People – Social media has “leveled” the playing field for
both consumers and brands. Individuals creating compelling or “sticky” content, have the ability
to equally-compete for attention with any other media sources. Share of voice is no longer solely
a function of size and budget expenditures.

• Re-thinking Sampling – Social media data may not always accurately reflect the targeted con-
sumer. In addition, for given topic or source, a disproportionate amount of content may be gener-
ated from a subset of contributors. This goes against the traditional researcher paradigm to find
a representative sample of the target market.

• Influence – Because of the disproportionate contributions of some authors, the notion of influ-
ence becomes an added dimension for researchers to consider. This idea is expanded upon in the
Peer Influence Model in Empowered by Josh Bernoff. Social media data will be more beneficial
to exploration and learning applications instead of projections because of this notion of influ-
ence.

• Relationships are the Ultimate Sources of Insights within Social Media – As response rates con-
tinue to decline for research efforts, the ways of encouraging respondent participation are evolv-
ing. The Market Research Executive Board suggests the way to gain participation is now based
upon how you can add value to the consumer. This is more than just reimbursing them for their
time via incentives. Social media research ventures into the realm of building a relationship
with consumers and adding value to their lives.

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Social Media Data in the Research Landscape
Due to the characteristics of social media data already discussed, it is fair to ask where this kind
of data and analysis fit within the market research landscape. When should it be considered as
an appropriate analysis tool? Is it better for some things than for others? Does it replace existing
analyses? All these, and other questions about the influence of social media data on the research
profession are beyond the scope of this paper. As with other new sources of data in the past, i.e.,
POS, online communities, it will take time and experimentation to learn how and where to best use
this source of consumer data.

Of the three various uses of social media data explained above (Listening, Engaging, and Measuring),
Listening and Measuring are the most immediately applicable to the research function. When the
objective of the researcher is to understand people and gain insight into their lives, Listening will
be the most useful social media activity. When the objective is to measure a marketing campaign,
product launch, or other similar assessments, Measuring will also be an important use of social
media data.

Within the Listening sphere, based on our analyses done to date using social media data, the analy-
ses we have seen from other vendors, and case studies in the literature, it appears that social media
is best suited for exploratory research. In each case, the primary benefit of the social media data
was to expose language used, sentiments, and stories around these various issues. It appears that
reading about people’s lives tends to generate more questions and hypotheses than it answers.
Thus, it appears that social media data is an excellent, unstructured, uncensored, and passionate
view into people’s everyday lives and feelings, that is better used for exploration than validation.

What does the future hold? Will the social media space become the research space? Only time will
tell. To the extent that expenditures for social media analysis capabilities take away from resources
for other techniques, then social media data will become a replacement for some research tech-
niques.

Conclusion
It should be apparent from this brief overview that social media data can indeed be used to help un-
derstand people and their lives. However, it is a different source of data than that which researchers
are accustomed to, and requires rethinking traditional research paradigms.

We believe that businesses cannot afford to overlook this source of consumer insight, and that its
importance and influence will only increase as time goes by. We encourage all who are seeking to
understand and have empathy for people to become versed in this data source, and consider utiliz-
ing it whenever possible and relevant. We hope this brief overview will be helpful in serving as a
catalyst for getting started.

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Appendix A: Free Access to Social Media Data
Useful free tools for general social media searches into the data

• Twitter Search | http://search.twitter.com
• Facebook Search | http://openbook.org or http://www.facebook.com
• Google Blog Search | http://blogsearch.google.com
• Aggregate Search | www.addictomatic.com
• Search top Momblogs | www.Blekko.com (type search term and /momblogs )
• Hallmark /momblogs http://blekko.com/ws/hallmark+/momblogs
• Search Public Facebook Statuses | http://youropenbook.org/
• Social Mention | http://www.socialmention.com
• Backtweetes | http://backtweets.com

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Appendix B: Social Media Research Resources
Forrester Articles
• Defining Social Intelligence – Zach Hofer-Shall (March 12, 2010)
• How to Make Social Media Data Actionable – Zach Hofer-Shall (April 28, 2010)
• How can Market Researchers get Social – Tamara Barber (Update June 14, 2010)
• Introducing the New Social Technographics – Josh Bernoff (January 15, 2010)

White Papers/Articles/Blog Posts
• The 5 Behaviors of Social Media – Paul Isakson of paulisakson.com (2010)
• Using Social Media for Market Research – MREB (January 2010)
• The 8 Stages of Listening – Jeremiah Owyang
• Quirks Marketing Research Review (August 2010)
• MRA/IMRO Guide to the Top 16 Social Media Research Questions (2010)
• Netnography: The Marketer’s Secret Weapon – Robert V. Kozinets (March 2010)
• Getting Answers without Asking Questions – InSites Consulting (April 2009)
• The Collective is the Focus Group – David Armano (January 2009)
• Listening vs Asking: Nielsen (June 2009)
• Social Listening for New Product Development – Nielsen (April 2010)
• Why Social Media Research Should be an Important Part of your Research Portfolio – JD Power
(2010)
• Seven Types of Data – Jeremiah Owyang (netbase.com/pdf/netbase_7_types_of_data.pdf)
• Social Media Metrics – Papercliq (slideshare.net/tarushijio/social-media-metrics-papercliq)
• PEW Internet (pewinternet.org)

General Social Media Resources
Books

• Six Pixels of Separation – Mitch Joel
• Listening Playbook – The Advertising Research Foundation
• Empowered – Josh Bernoff
• Groundswell – Charlene Li and Josh Bernoff
• Open Leadership - Charlene Li
• Engage - Brian Solis
• Social Media Metrics - Jim Sterne

Blogs

• Six Pixels of Separation – twistimage.com/blog
• Web Strategist – Jeremiah Owyang – web-strategist.com
• Greenbook – greenbookblog.org

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Contact Us:
Josh Gunkel
Hallmark
Twitter: @joshgunkel
Blog: curatingpixels.com
Email: josh.gunkel@hallmark.com

Ben Smithee
Spych Research
Twitter: @spychresearch
Website: spychresearch.com
Email: ben@spychresearch.com

Tom Brailsford
Hallmark
Email: tbrail@hallmark.com
Twitter: @tbrail

P a g e | 15

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