Understanding your audience and considering them in your design is essential for building great visualizations. This deck will walk you through the critical steps for identifying and understanding your audience, and developing a complex visualization storyboard to share your message.

1. IDENTIFYING
YOUR AUDIENCE &
FINDING YOUR
DATA STORY
​This deck was
designed as a guide
for staff looking for
resources about
effective data
visualization for the
right audience.
Jessica Dubow
Amanda Makulec
JSI Center for Health Information,
Monitoring & Evaluation
September 2014

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​“By rethinking the way we use data and understanding our
audience, we can create meaningful stories that influence and
engage the audience on both an emotional and logical level.”
​ –Daniel Waisberg, Analytics Advocate for Google

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+ Data
Visualization as
Storytelling
+ Examples
+ How to Tell a
Good Story
+ Why Your
Audience Matters
+ Know Your
Audience
+ Audience
Engagement
+ Author Driven vs.
Reader Driven
Storytelling
+ Human Centered
Design
+ Brainstorming
+ Brainstorm
Procedures
+ Methods: Post-it
Notes
+ Methods: Web
Based
TABLEOF
CONTENTS
+ So What?
+ Collecting and
Aggregating
Data with Viz in
Mind
​Introduction ​Finding Your Data
Story
​Identifying Your
Audience
​Storyboard
Development
01 02 03 04
Pages 22-28Pages 12-21Pages 6-11Pages 4-5

4. 4|
Introduction:
So What?
​Data visualization allows you to present large quantities of
information as easily consumable and retainable bits. Visual data
grabs attention and is more memorable than long-form reports,
something increasingly important in fast-paced business
environments where adults have shorter and shorter attention
spans and in an age of information overload.
​Data visualizations tell a story through illustration, rather than
narrative explanation. As the designer, you make choices to
highlight content by using size, color, and other visual tools. The
story you tell and how much you guide your audience towards
conclusions, or how much you leave open to their interpretation,
depends on the context of who your audience is. A data
visualization is meaningless if not designed to connect with
your target audience.
​As the designer, you must identify the points that you want to
make, identify your key audience, and create the clearest
visualization that conveys that message to that audience.
​Unsure how to proceed? Never fear, you’re in the right place.

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Collecting and
Aggregating Data
with Viz in Mind
​Before you start framing your data visualization for the right
audience, you have to find content to work with.
​In some cases your data may be given to you, but in others you’ll
have to make decisions about which data to use and where to find
it. As you flip through this slide deck and consider what story is
right for what audience, you may also want to consider what data
is right for that narrative and for that audience. Do you want
generic or specific data? How reliable are your sources?
​The Data + Design eBook offers guidance on collecting and
preparing data with an end-goal of creating effective
visualizations. If you’re new to data visualization, it may serve you
to read through the book to get a better grasp of the entire
process before beginning to design.
​This slide deck continues with the assumption that you already
have your data and now need to determine the most effective way
to present it.

6. Finding Your
Data Story
DataVisualizationas
Storytelling
Examples
HowtoTellaGood
Story

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Data Visualization
as Storytelling
​According to data analyst Susie Schoppler, the primary goal of
data visualization is always to promote action. Data visualizations
explain and facilitate understanding too, but with a purpose.
​Dell Executive Strategist Jim Stikeleather agrees that storytelling
with data begins with finding the meaning in your data story:
​ “You are competing for the viewer’s time and attention, so
make sure the narrative has a hook, a momentum, or a
captivating purpose. Finding the narrative structure will help
you decide whether you actually have a story to tell. Along with
giving an account of the facts and establishing the connections
between them, don’t be boring.”
For Schoppler, the kind of story you tell affects the platform you
choose. Infographics may be more useful for persuading your
audience towards a point of view whereas dashboards leave
interpretation to the audience, enabling discovery and actionable
insights. Your chosen platform may also be affected by your
audience.
For example, according to Pew Research Center, 95% of young
people ages 18-29 regularly watch short online videos whereas
this drops to 50% for adults 50 and older. An animation may
therefore effectively target college students but not effectively
disseminate information amongst older adults.
Think of your dataviz message as a
thesis statement that you need to
summarize in a few concise sentences.
Your ability to create a compelling,
well-organized visual argument is
much greater if you begin with a clear
and focused message.

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Examples:
Graphs & Maps
Florence Nightingale
shared many of her
visualizations with
Parliament.
Her evidence that more
soldiers died from
preventable illness than
battle wounds best
targets policy makers to
prevent these deaths by
allocating more
resources and training
health workers.
Two famous data visualizations are John Snow’s mapping of
the 1854 cholera outbreak and Florence Nightingale’s diagram
of causes of death in the Crimean War. Both are simple to
understand without much health background and work for
different audiences.
John Snow’s map allowed
him to identify the point
of origin for the outbreak
and react effectively by
preventing drinking from
the pump.
It was useful to him as a
physician and could have
also influenced policy
makers to improve water
sanitation systems or the
public to seek other
sources of water.

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Examples:
An Infographic
This infographic on cancer
would best serve a general
audience without much
background knowledge
because it covers basics. It
would not serve someone
illiterate because it is text
heavy nor someone with any
background in cancer.
The data is simplified by
visuals so it is not
numerically intimidating.
There is not enough specific
content to target policy
makers or funders, but this
allows the graphic to engage
with a broad audience.
The infographic follows a
well-defined story: key
messages are highlighted, it
reads from left to right, and
it has a clear purpose of first
informing and then calling
to action.

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“Data is powerful.
But with a good story,
it’s unforgettable.”
—Daniel Waisberg, Google

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How to Tell a
Good Story
​Your credibility is very important to your data story and how your
audience interprets it.
​For Jim Stikeleather that means being as objective as possible. He
says that even when using data visualization to persuade, you
should avoid bias by allowing your data to do the work rather than
adjusting it to say what you want. Don’t censor your data, and be
careful to keep your design elements from accidentally
compromising the integrity of your content.
​Consider the three purposes of data visualization from DataViz:
› Communication or understanding: Is the visualization
presenting known inforamtion to an audience or revealing
unknowns?
› Audience: Is the visualization intended for public dissemination
(general audience) or a more specific technical audience?
› Interaction: How is the user able to interact with the
visualization?
These will be covered in greater depth in the following sections.
Image Source: http://thenonfictioncartel.com/crowdfunding-tips-to-live-by-the-importance-of-storytelling/
Ask yourself:
› What do you know?
› What does it mean?
› Why do you believe it’s
important?

12. Identifying Your
Audience
WhyYourAudience
Matters
KnowYourAudience
Audience
Engagement
AuthorDrivenvs.
ReaderDriven
Storytelling
HumanCentered
Design

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Why YourAudience
Matters
​If you think about data visualization as storytelling, then you
realize you need to tailor your story to your audience. The
illustrations, words, and delivery are different when speaking to a
child versus to an adult. Similarly, when speaking to an executive,
statistics are likely key to the conversation, but a business manager
might find methods just as important.
When you tell the right story to the right audience, and are able to
identify data points that resonate with an audience and encourage
them to start a conversation, you increase your story’s share-ability
and give it the chance of going viral. One such example is Hans
Rosling’s Joy of Stats series on health and wealth, which has
millions of views on YouTube and is one of the most popular TED
talks of all time. Rosling’s animated presentation is able to connect
to a general audience without much global health background
through an innovative data visualization.
Complex technology-driven visualizations aren’t required to tell
stories effectively. Hand drawn graphs and pictures, job aids, and
other tools can be highly effective at connecting with an audience
– one great example is the My Village, My Home immunization
tool used in India to strengthen routine immunization programs.
Regardless of the platform you choose, if you are able to connect
to your audience then you will be part of the conversation.

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Know Your
Audience
Your data visualization must be framed around the information
your audience already has in order to inform them, counter their
misconceptions, or update or build on their existing knowledge.
Start by asking yourself:
› Who is the data visualization intended for?
› What does the audience know about the topic?
Consider your audience’s level of:
Literacy: Data visualization allows you to share information in low-
literacy areas in the field. You can use symbols, illustrations,
animations, and other universally understood graphics.
Numerical literacy: Even educated audiences are not always
comfortable with data and math. Do they understand ratios,
complex formulas, or statistics? Or do they need data simplified?
Education/Level of Technical Expertise: Health is interconnected
with and covers many topics, from population and nutrition to
epidemiology and economics. Even people who work in and are
educated on the field of public health may not be experts in
specific areas. Simplify content and define terms for less technical
audiences but provide more detail for those with expertise.
Job Function: Consider the purpose of your data visualization. A
policy maker will want high-level results from a survey to guide
decisions. A program manager may only be interested in data
relevant to their topic and region. Funders will want to see results
compared to dollars spent. Health workers will want to know how
new information affects their priorities in the field. Academics will
want to know how data fits into existing literature.
Specifically their:
› Literacy
› Numerical literacy
› Education
› Job Function

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Know Your
Audience
Once you understand who your audience is, you must also
consider what they want from your data visualization.
Dell Executive Strategist Jim Stikeleather lists five main
audiences:
› Novice: first exposure to the subject, but doesn’t want
oversimplification
› Generalist: aware of the topic, but looking for an overview
understanding and major themes
› Managerial: in-depth, actionable understanding of
intricacies and interrelationships with access to detail
› Expert: more exploration and discovery and less storytelling
with great detail
› Executive: only has time to glean the significance and
conclusions of weighted probabilities
The level of background knowledge your audience has affects
how you present the information and the level of specificity
that they expect.
What do they want to
know?

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Know Your
Audience
Icon Attributions: Creative Commons/Noun Project
Who are you connecting to?
Once you have identified your audience, consider their context.
The same data table can mean different things to different
people.
Imagine you are part of a team of health consultants advising a
Ministry of Health on urbanization trends. What should you
consider?
Background: What data does the MOH already have? Are
they familiar with this concept and these indicators? What are
their expectations? What problems is the MOH facing
regarding urbanization?
Audience Objectives: What questions is the MOH likely to
ask? What do they plan to do with this knowledge? Are they
looking to develop new policies to respond to a growing urban
population? Are they worried about the dwindling population
in rural areas? Are they looking to encourage urban growth
or slow it down? Are they looking for international funding for
urban health programs?
Politics and Perspective: Consider the biases of your
audience. If the MOH has been working to improve urban
health but data indicates it is still a problem, will they want to
share this information? Or if urban growth has slowed they may
worry about losing funding for urban health. You need to tell a
data story that is both true and relevant to their objectives.
Consider your own biases as well. Are you willing to share
activities that have not been successful, even if it reflects
negatively? Be critical and ethical in choosing your story.

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Audience
Engagement
​In Data Visualization, Tarek Azzam and Stephanie Evergreen note
that in the present day data visualization has reached a point
where individuals can directly interact with and manipulate
the visualization, as was demonstrated by Hans Rosling’s
aforementioned famous Ted Talk.
​The internet has encouraged transparency within both public and
private organizations, especially as funding has tightened and the
need for accountability has increased. More data is easily
accessible to the public, especially as so much is generated—US
companies alone create enough content every year to fill the
Library of Congress ten thousand times. Thus, the need to analyze
“big data” is becoming more common in society. Examples of
open data initiatives include the US Government’s data.gov, the
World Bank’s Data Bank, the CDC’s Data Bank, and the
Demographic and Health Surveys Program’s Stat Compiler.
​Data visualization engages program stakeholders and the
general public by increasing their capacity to understand data
and participate in the evaluation process. Well designed interactive
visualizations place stakeholders in the driver’s seat in terms of
defining variables and interpreting results.
Image Source: http://www.gapminder.org/

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Revealing Unknowns Presenting Knowns
High Interaction
Private
Exploring data for patterns,
using flexible visualization tools
such as Excel, GIS applications,
Tableau, intranet Local
Information Systems
Interactive performance
management tools, providing a
series of data reports on service
delivery areas such as the
economy, health, crime, and so
on. Interactive features allow
service and performance
managers to drill deeper into
performance data
Public
Interactive online systems, for
example:
Communicating performance
or service information to
citizens online using interactive
tools, i.e. location and quality
of health services overlaid on
Google Maps
Gapminder: presenting socio-
economic trend data
Many Eyes: allowing users to
upload data and visualize in
different ways
Low Interaction
Private
Communicating interim results
of research to internal audience
Internal research briefings to
senior managers
Public
Research reports presenting
multiple views on data, i.e. Joint
Strategic Needs Assessment
(JSNA)
Communicating performance
information to citizens using
printed reports
Audience
Engagement
This table from Improving Visualization gives some examples of
when high interaction vs. low interaction data visualizations are
appropriate.

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Data is the new soil, because
for me, it feels like a fertile,
creative medium. Over the
years, online, we’ve laid down
a huge amount of information
and data, and we irrigate it
with networks and
connectivity, and it’s been
worked and tilled by unpaid
workers and governments.
—David McCandless,
Information is Beautiful

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Author Driven vs.
Reader Driven
Storytelling
​According to Daniel Weisberg of Google, data visualizations
should build story that promotes action, rather than only
facilitating data exploration. The most effective narratives
balance the story told by the author with interaction and
discovery on the part of the reader. You must decide where
your audience falls on the spectrum so that you do not distract or
overwhelm, but offer enough for the curious to explore.
​Ryan Morrill, creator of the above spectrum, says that on the
extreme left there are scientists who want raw data through which
they can develop their own conclusions. On the extreme right are
people who want to be presented with completed results,
conclusions, and analysis. They want the data to be edited down to
bare essentials so that it is approachable and easily consumable.
​Consider the time, motivation and inclination of your
audience to interpret your data visualization when evaluating
where they fall on the spectrum. Don’t cram too much
information into your visualization unless you want your audience
to spend time looking at it. If you want a clear take-away message,
consider using your headline as a quick summary.

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​By considering your audience upfront when creating a data
visualization, particularly a visual tool like a dashboard or other
interactive tool, you are implementing practices of Human
Centered Design.
​HCD places the end user of an idea or product at the forefront,
and provides a framework for iteratively testing the visualization
with your audience to make sure it resonates. It links the designer
of a tool, product, or system (in this case, a visualization tool) and
the end user through empathy, and requires the designer (or in
this case you, as the narrator) to consider the intended audience.
Using techniques from HCD (and more broadly, user interface
design) can help you understand your audience and how they
would use the visual tool you’re designing. You can learn more
about how HCD and principles of user-centered design are applied
and the tools for understanding user needs with the following
resources:
d.School “Understand”
​To Build a Better Dashboard, Get to Know Your Audience
​Dimensional Insight’s Know Your Audience
​
We’ll also unpack some of the ideation (brainstorming) techniques
from HCD in the following section.
Human Centered
Design for
Interactive
Visualizations
Image Source: http://dstudio.ubc.ca/toolkit/processes/

22. Storyboard
Development
Brainstorming
Brainstorm
Procedures
Methods:Post-it
Notes
Methods:Web-based
Tools

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Brainstorming ​Once you have considered who your audience is and what their
multiple perspectives are on defining the problem, you can begin
generating potential ways to illustrate your data story. For simple
graphs and charts, you may find sketching or playing in Excel gets
you where to go. But when you have a more complex story, with
multiple data points, creating a storyboard through collaborative
brainstorming can be very helpful.
​The initial goal is quantity and diversity of ideas by brainstorming
with team members, often including both technical colleagues
who understand the content and communications experts who
understand the audience. From their HCD ideation process,
SFMOMA developed these brainstorming procedures:
› “How Might We” Questions
› Brainstorm Rules
› Selection Criteria
​These are expanded upon on the following slide.
​Generating multiple ideas is essential as you begin prototyping
your data visualization. Some of your data visualizations will not be
as effective as you had hoped, and being able to return to a
repository of ideas helps you move more quickly to another
possible solution.

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Brainstorming
Techniques
› “How Might We” questions: By starting questions with “How
might we…?” you narrow the focus of your question and can
brainstorm ways to solve the problems defined in the second
HCD phase.
› Amp up the good: look at the positive things your product
(in this case, the visualization you’re designing to share
your data story with your audience) can do
› Diminish the bad: think about how your product solves a
problem
› Reframe the bad into good
› Brainstorm Rules: Creating rules for brainstorming helps
everyone get on the same page.
› Defer judgment during the brainstorm. You’re going for
quantity, not quality, so evaluate ideas later. In the
meantime, encourage wild ideas.
› Build on each others’ ideas to promote positivity.
› Use selection criteria: In order to make sure you consider both
easily implemented plans and innovative but undeveloped
plans, allow each member of your group one vote of the
following criteria:
› Low-hanging fruit: ideas that would be easy to implement
› Most delightful: ideas that excite your audience
› Most breakthrough: ideas that are innovative and game-
changing

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“It is easier to tone
down a wild idea than
to think up a new one.”
—Alex F. Osborn
“Father of Brainstorming”

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Brainstorm Methods:
Post-itNotes
Brainstorming with post-it notes allows you to visualize your
storyboard and future visualization in an early stage. You can
physically shift ideas around to organize your thoughts, create
groupings, throw away what doesn’t work, and build arguments.
​Moreover, storyboarding with post-it notes also gives the process
flexibility in terms of being able to do it in any setting, whether it
be in the field or at headquarters.
​For effective post-it brainstorming, consider the following:
› Write only one idea per note so they can be rearranged
› Use colored post-its and use different colors to represent
different themes or different participants
› If you put your post-its on a whiteboard or on butcher paper,
you can draw links between notes to show multiple connections
› Encourage your team to stand up and move around so that this
is an active and engaging process. Placing post it notes on a
wall also allows everyone to participate without creating a
hierarchy of ideas.
› Leave your brainstorm posted so it can be revisited
Interested in more brainstorming techniques? Check out
Christian Parsons’ blog, Idea Drunk.
Image Sources: http://crissxross.net/wilx/2009/05/05/exploring-methodologies-for-non-linear-story-development/,
http://www.philippgoeder.com/?p=147, http://www.hotstudio.com/thoughts/no-more-brain-bashing

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Storyboarding:
Web-BasedTools
These online tools are useful for
mind-mapping and storyboarding.
They are less effective for
collaboration than the post-it
method, but may be useful if you
are working individually.
Draw.io is a free online mind
mapping tool that also
connects to your Google Drive
or Dropbox and allows you to
create simple webs and flow-
charts to brainstorm and
organize ideas.
Twine is a simple and free
downloadable application that
can organize how scenarios
unfold in a non-linear story. As
you build a flowchart, each
small scene links to another
allowing you to build a map of
possible paths.
​Storyboard That features a
simple interface and detailed
image library that serve to
structure your ideas into a
linear and concise story. Basic
and infrequent use is free; an
individual plan is $5.95 per
month.
​Wisemapping is a free and
simple tool; select a node and
use enter and tab to link your
ideas and organize them into
a web.

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Next Steps ​Once you have brainstormed ideas and begun to organize them
into your storyboard, you can begin exploring your design options
and developing your data visualization.

29. Connect
DataVizHub.co
Questions, updates, ideas, or suggestions?
Amanda Makulec | amakulec@jsi.com