Emotional Modulators: Color, Language, and Other Design Elements

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En provenance du cours de University of California, Davis

Research Report: Delivering Insights

23 notes

University of California, Davis

Research Report: Delivering Insights

23 notes

Cours 4 sur 4 dans Specialization Market Research

You have completed all the hard work of conducting your internal, secondary, and primary research. You have analyzed all the data and are able to formulate insights and recommendations based on your research proposal. But what is the best way to present your findings and be able to make a decision? In this course, you will discuss how to incorporate a story in your marketing presentation to help you capture the attention and gain support of stakeholders and business leaders. You will choose the most effective analytical method for delivering your insights and the best presentation method for your given audience. You will incorporate data visualization best practices and use tips and tricks when presenting to your various levels of decision makers and stakeholders.

À partir de la leçon

Getting Started & Synthesizing Findings and Deriving Insights

You’ve gathered your data from qualitative and quantitative market research. Where do you go from there? At this stage, you will need to synthesize your findings and derive valid and actionable insights that will help to solve the business problem. In this module, you will be able to find the story in the data and shape it to contribute to a compelling market research presentation. You will be able to synthesize the data, select the appropriate tools to analyze your product or service and determine how consumers view your market. You'll be able to evaluate Market Positioning and Market Segmentation; you will see how to use Conjoint Analysis to compare the relative value of product features or attributes, and Perceptual Maps to help tell the story of consumers in your market and provide actionable comparisons. You will also define terminology and essential concepts that will equip you to be conversant and more confident in the market research field.

A Design Checklist of the Who, What, Why, and How7:44

Start with your Stakeholders3:52

The Art of Storytelling (Past, Present, and Future)3:27

Storytelling and the Human Brain5:28

Emotional Modulators: Color, Language, and Other Design Elements8:24

False Narratives and Data Storytelling6:51

Rencontrer les enseignants

Robin Boyar
Founder, thinktank research & strategy
UC Davis Division of Continuing and Professional Education
Ashwin Aravindakshan, PhD
Associate Professor, Graduate School of Management
UC Davis

[MUSIC]

Welcome back.

Our previous lesson focused primarily on using structural elements

to weave emotion into your data story.

Now, while structural elements like the three Cs,

provide the framework, color and language choices can heighten and

reinforce the emotional tone of a data story.

That's what we'll be focusing on in this lesson.

There are three visualizations in your resources.

If you haven't looked at them already, please do that before continuing.

After this lesson, you will be able to explain how color and

language choices can heighten the emotional tone of a data story.

You'll also be able to distinguish between structural elements and

emotional modulators and explain why to use each.

Let's get started.

Hello, again.

The decisions that you make about color, language and various other design elements

can have a profound impact on the way your data story is experienced and interpreted.

Think about your design checklist.

Does the presentations esthetic approach support or undermine the tone, tenor and

content of your story?

For example, a dated story about a serious and

somber subject will generally have a more muted palette, while a more lighthearted

topic could be presented with brighter more saturated hues.

Although the symbolic meaning of colors varies by culture, effective and

targeted colors selection can reinforce and intensify the message being conveyed.

For example, in many cultures, black can be suggestive of death.

In Minard's March the return flow of the decimated and

dwindling French army is shown in black.

That said, in other cultures,

it's just the opposite with white rather than black filling that symbolic function.

This just underscores the point that to really connect with your intended

audience, it's important to know a little bit about them.

Shortly, we will see an example of how color is variously employed

in the data stories about gun deaths.

Like color, language and specific word choices

can exert a strong influence on the experience of a data story.

For example, what are the words that you use in your stories title, and

in say, story points captioning, to describe a particular set of statistics?

Are they shocking, or surprising?

Or not described with words that are charged with obvious emotion and

judgment as undercurrents?

As with so many things,

more is not necessarily better when it comes to descriptive language.

For example, coming on too strong in language choice can sometimes undercut and

evoke a counter reaction in your audiences from the one that you intend.

Think of it this way, if you want to persuade someone about a point

that you are making, you do want to be forceful, but you don't want to yell.

Similarly, the design of your data story should be compelling but

not yelling when making your points.

That's one reason why pre-planning is so important.

Hitting the right emotional notes with your audience involves knowing the purpose

of the story, the data that you'll be using and

the ability to empathize, at least to some extent, with potential audiences.

Now, in addition to color and

language, design elements can contribute to the emotional tone of the data story.

In Minard's visualization,

the change from a wide band at the beginning of the story into a thin

trickle of a line by the end visually conveys the dramatic loss of life.

With Hans Rosling visualization example, the movement in the bubble chart and

rapidly changing timestamp brings a certain narrative momentum to the story

that he is telling.

Now, not every technique to bring emotion to a story is equally important or helpful

and can sometimes be counterproductive for reasons that we will consider.

A great color scheme or well phrased title cannot save a story that lacks,

what are sometimes called, good bones.

That is, a well done scaffolding for the story.

FIrst, put your energy into the basics, such as what data you're going to select

and highlight, along with how you might set up your story arc.

If your story framework and structure is uninteresting, then using a lot of bright,

saturated colors for your visualizations won't help.

Imagine that you are making an action movie with a dull script.

You could add in lots of explosions and car crashes, but

the movie will still be boring.

At least to me, anyway.

Let's look at three narrative visualizations that address an emotionally

loaded topic, gun deaths.

For your consideration, I'd like to offer some comments and

questions about the following examples.

My goal is not to point to a right answer, but to have you think about tradeoffs.

What is gained or lost from how emotion is emphasized?

And what is the better alternative for emotional design for

the intended audience?

My goal is not to focus on the issue itself, but rather, how it is presented.

The references to these visualizations are in your source materials.

Let's start with language.

It's clear from the title and subtitle of this data story, The Top Killing Machine

in the USA, that this is been done in an emotionally charged manner.

For example, the word shocking is commentary by the creator.

Essentially, we're being told how to feel about this data.

My point is not if the word choice works, but that you think about the affect

the wording choices have on you and your experience of the story.

There are other very clear signals about design choices here and their signaling.

For example, the hearts on the map that indicate the number of lives lost.

For me, the emotional power of very familiar symbols can be a little tricky

to use effectively.

Although I think I understand the intent of the hearts here, for

me they tend to represent things other than lives lost.

On a more practical level, the hearts,

particularly on the eastern side, merge into each other on the main view.

That's called visual occlusion.

In this case, it makes the data hard to decipher,

while not necessarily enhancing the overall impact of the story.

Now please examine this visualization further and

come up with your own observations about it.

Now, let's look at another example of gun death visualization.

In this case,

it's an arc diagram showing lives that have been cut short by gun deaths.

What emotional elements jump out at you?

Well, for me the somber color scheme and

relatively stark design make the strongest impression.

Although the language choice is generally cut and dried, the phrase stolen years,

next to the large number is definitely an emotionally charged statement.

If I think more about it, I'll need to understand how these numbers are derived,

but the tone is immediately set by the word choice in any event.

Now, we'll look at the third approach showing gun deaths in a visualization.

Compared to the first two examples, the design choices

in this visualization are more subtle and understated, at least in my view.

That is, not to say that this example is any better or worse than the others, or

that emotion Is not still a subtext here.

For example, seeing one black dot,

in the context of all the other gray dots representing the larger backdrop of

gun deaths, has some emotional resonance, at least for me.

Again, as with most things, more is not necessarily better, but

less is also not necessarily ideal either.

If a gun story is too emphatic, it might backfire, so to speak, and

make the viewer less likely to respond to the message, as intended.

If too little emotion is evoked,

then the viewer may simply not care about the story.

Finding the right balance and modulating emotion through color, and language, and

other design choices is part of exercising your data storytelling skills.

In the next lesson, we will take a deeper look into issues of story structure.

See you next time.

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