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

TABLE OF 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 22-28

Pages 12-21 Pages 6-11 Pages 4-5

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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.

Finding Your Data Story

Data Visualization as Storytelling

Examples

How to Tell a Good 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?

Identifying Your Audience

Why Your Audience Matters

Know Your Audience

Audience Engagement

Author Driven vs. Reader Driven Storytelling

Human Centered Design

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Why Your Audience 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/

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-it Notes

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-Based Tools 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.

Connect DataVizHub.co

Questions, updates, ideas, or suggestions? Amanda Makulec | amakulec@jsi.com