14 Things Market Researchers Need To Know About Data Visualization

Data visualization has become a part of our everyday readings, online and off. We see charts, graphs, and maps on the news or on social media every day and for researchers.

It’s important to have both knowledge of data visualization and access to the tools that make creating a chart as simple as making a pie. Here are 14 things you need to know about data visualization:

Data Visualisation – Tools and Techniques – YouTube

Key Takeaways
1. Data visualization enhances communication of insights.
2. Visualizations help reveal patterns and trends in data.
3. Proper color choices impact the effectiveness of visuals.
4. Interactive visuals engage audiences and encourage exploration.
5. Effective storytelling is crucial for impactful data visualization.
6. Combining multiple data sources can lead to more comprehensive insights.
7. Simplicity and clarity should be priorities in visual design.
8. Choose appropriate visualization types for different data sets.

Table of Contents

What Is Data Visualization?

Data visualization is the process of transforming data into visual representations. It is a technique to communicate information effectively and efficiently by mapping a high volume and high variety of data to tools that can be used to gain insights.

Data visualization can be used for a wide range of purposes, including:

Visualizing geographic information such as population density or sales volumes at a city level

Presenting product portfolio compositions across multiple countries/regions

Exploring the art of data visualization is crucial for effective market research. Dive into our guide on 14 Things Market Researchers Need to Know About Data Visualization to enhance your understanding of presenting insights visually.

How Does Data Visualization Help Research?

It makes data easier to understand. Visual representations of information can help you communicate complicated ideas with ease and clarity, whether you’re presenting a report or teaching a class.

It makes data easier to remember. Seeing something is much more likely to stick in your mind than just reading about it, so visualizations are an essential part of any educational experience, especially when learning about complex subjects like market research!

It makes data easier to share with others who might not have been involved in the project but could benefit from knowing its results like clients or colleagues at other companies that need access but might not have had as much involvement during research phases themselves (for example).

This helps spread knowledge among different groups within companies while also allowing them each to keep track of what’s being done across departments through regular updates via memos sent out via email listservs etcetera which we’ll talk more about later on another page within this book series called “How To Get Ahead When Working For Someone Else:

A Guide For Young Professionals Trying Their Hardest Not To Fail At Their Jobs Yet Again” coming soon in 2020!

1. Good Design Is Important

You’re not a designer. You may have the skills to be a great data visualization designer, but you don’t necessarily know what it takes to make good design decisions.

So, before you start creating *anything* for your research report, make sure you have a good grasp of the design process.

It’s important because design helps people understand your data by making it easier to read and find patterns in your information.

It’s also important because the good design makes people remember your data better than bad design does which means that if someone sees your visualizations twice (or more), they will remember them longer if they are well-designed than if they weren’t.

Finally, good data visualization can help people share information about your brand or product through social media channels like Twitter and Facebook as long as those channels support rich media formats.

Such as GIFs or Vines which allow users to upload animated images without needing any special software installed on their devices.

Are you struggling with lead generation in the B2B market? Discover valuable insights in our article about how to find 100 targeted B2B leads every month and optimize your lead generation strategies.

2. People Don’t Like To Read

As a market researcher, you probably know that people don’t like to read. But do you know why? Well, it’s because people are lazy and they don’t want to work hard at understanding what they’re reading (or watching).

You might ask: “but isn’t that true of all content?” Yes, but it’s especially true of data visualizations. The reason is because of the 2nd law of thermodynamics: entropy increases over time and leads to chaos in nature;

The more time passes by since something was created or published—the less relevant and useful it becomes for anyone else who comes across it later on down the line (unless there are updates).

This means that any information related to current events will rapidly become outdated after some period passes without being updated regularly (think about Wikipedia articles – how many times have you seen one change from 2014 until now?).

3. Make Your Graphics Interactive

Interactive graphics are more engaging and persuasive than static ones, which means they’re better suited for helping you communicate your insights to a wide range of audiences from the executive team to salespeople and customers.

They can also be more informative; an interactive graphic might reveal the exact number of employees in the company or highlight how many people made purchases in certain regions during a given period, rather than just using percentages or averages.

Use data visualization tools that make it easy to share your findings with others at all levels of the organization from executives down to managers and frontline employees while still maintaining control over who sees what data points.

As a market researcher, being an effective researcher involves a specific set of qualities. Learn about the 12 qualities of an effective researcher to enhance your skills and excel in the field of market research.

4. Tell A Story

You’re telling a story.

When you design your data visualization, make sure you know what the story is and how it will be told. The story might be the answer to a question or a series of answers, but more likely it’s something else a point you want to make or an action you want someone to take.

Your chart should support that goal so that when people look at it they understand exactly what they’re seeing and how it relates to their situation or needs.

If you have multiple stories within one report (for example, one about past performance and another about future trends), consider using different charts for each one of them so that readers can easily distinguish between them and find what they’re looking for at first glance.

5. When You Are Making A Presentation, You Are The Star Of The Show

When you are making a presentation, you are the star of the show. According to research by Harvard Business School, people remember 20% of what they hear, 35% of what they read, and 65% of what they see.

The way information is presented has a huge impact on whether or not it sticks in someone’s memory.

6. The Less Text, The Better

This is a rule that should apply to all forms of writing and communication. The data visualization you’re creating should be self-evident; you shouldn’t have to explain what it is showing or not showing.

If you are struggling with this concept, take a step back from your project and ask yourself: What would happen if I removed all the words from this chart? Would someone still be able to understand it?

7. The Simpler The Better

As a market researcher, your primary goal is to understand consumers and their behaviors. To do this, you must tell stories with data. You have a lot of information at your disposal: surveys, interviews, focus groups, and more.

As you collect this information, it’s easy to get caught up in the excitement of all that data and start throwing everything at the wall to see what sticks.

But there are some simple things you can do when visualizing your findings that will help ensure the best possible outcome for any report or presentation you create and keep everyone on board!

Consumer insights are essential for shaping successful marketing strategies. Discover key considerations in our guide on things to consider when conducting consumer insights and gain a deeper understanding of your target audience.

8. Sometimes The Simplest Way To Convey Information Is The Best

Data visualization is a powerful tool that can help researchers communicate their findings in a way that’s easy for the audience to understand. But sometimes the simplest way to convey information is the best.

Let’s say your company wants to know how people feel about cold weather. You could find out what percentage of people think “cold” when they hear the word winter, or you could ask them directly:

“On a scale of 1-5, with 1 being ‘not at all and 5 beings ‘extremely,’ how would you describe your feelings about winter?”

There are two major problems with this approach first off, it doesn’t provide any context around those feelings (what were they comparing winter against?). Secondly and most importantly, it takes up more space than other options might require.

If we use data visualization instead of just writing out those results into words, we can communicate much more information in much less space! Instead of asking our respondents “How would you describe your feelings about winter?”

Create an image that gives an idea of where each item falls on its spectrum it will save us both time and effort later on when trying out different visualizations using our data set

9. You Can Convey Multiple Layers Of Information In One Visual

As a market researcher, you know that for your data visualizations to be effective, they need to convey information in an accessible way.

But what does “accessible” mean? The chart should be simple enough that it doesn’t distract from the message, but thorough enough that readers can understand and interpret the data.

There are many different types of charts/graphs out there that can help you accomplish this goal but some are better than others.

For example, pie charts are often used because they’re easy for people to understand at first glance;

However, if there’s too much information being portrayed in one pie chart then it may become difficult for readers to interpret all the different parts at once (especially if those parts don’t have clear labels).

To ensure your visualizations convey clear information while remaining easy to read and comprehend, ask yourself these questions before laying down pixels on paper (or pixels on screen):

10. Use Color Carefully

As a market researcher, you know that color can be a powerful tool. Color can convey information, it can help highlight important information, and it can distinguish between different data points.

The right combination of colors has the power to create clear visualizations that are easy for people to understand. But what about using color for more than just these things?

Using color creatively is one way to add an extra layer of meaning and clarity to your research findings, especially when you’re trying to communicate with non-research savvy audiences who won’t have time or patience for dense reports full of charts and numbers.

Here are some ideas on how you can use color in your data visualization:

11. Good Charts Are Easier To Understand Than Bad Charts

Let’s face it: not all data visualization is created equal. Some of the best-designed visualizations I’ve ever seen were done by my five-year-old daughter using Microsoft Paint and a mouse.

They were crummy looking but they had a purpose, they told me what was going on, and they made me feel smart when I interpreted them correctly.

Other times I see a visualization created by someone whose job it is to make you feel stupid by having too many things going on or using color schemes that don’t work with your eyes (neon green anyone?).

The point is that if you want people to understand your data, make sure your charting tool does one thing first make sure it makes sense! Good charts are easy to read, interpret and remember; bad ones aren’t (more on this later).

12. Build Visual Literacy In Your Organization

But before you can share your data, you first have to be able to comprehend it. For others in your organization including stakeholders and management to understand the value of your content, they must be able to understand it themselves.

This means that you need to teach them what a good visualization looks like and how they can read said visualizations as well as how they can create their visuals when needed.

Visual literacy is a skill set: one that can be learned (and taught), just like any other language or skill set.

We all must realize this so we don’t write off data visualization as something only experts should learn about or do!

13. Ask People What They Think Your Chart Means Before Telling Them What It Means

You may have heard this in your statistics classes, but it’s still worth repeating. When we present data, we tend to think our chart is self-explanatory you can see the numbers, so you get it right? Wrong!

Most people will not be able to make sense of a table or graph if there isn’t some additional context provided for them first.

So when presenting findings in a survey, start by asking participants what they think the key finding is from looking at your visualization and drill down from there until you reach the true story behind the data.

Understanding the balance between qualitative and quantitative research is crucial. Delve into our comprehensive article on the definitive guide to qualitative vs. quantitative research to make informed decisions about your research methodologies.

14. Don’t Let A Chart Tell Its Own Story If It’s Not Telling The Right One

There are certain types of data that lend themselves well to visualizations, and others that don’t. We know this, but somehow we still have to work harder than we should to ensure that the visualization is helping us make sense of the data instead of leading us astray.

Let me explain how I came up with this concept as well as a few examples where I’ve seen people make this mistake so you can avoid making it yourself!

Conclusion

After all, the goal of visualization isn’t to make your data look pretty, it’s to use design principles and tools to communicate meaning. It’s not about making you look smart; it’s about making your audience smarter.

FAQs

What is data visualization?

Data visualization is the graphical representation of data and information to convey complex concepts, trends, and patterns in a visually appealing and understandable format.

Why is data visualization important?

Data visualization simplifies complex data, making it easier to comprehend, analyze, and extract insights, ultimately aiding in informed decision-making.

What are some common types of data visualizations?

Common types of data visualizations include bar charts, line graphs, pie charts, scatter plots, heatmaps, and treemaps, each suitable for representing different types of data.

How can data visualization benefit businesses?

Data visualization helps businesses identify trends, opportunities, and potential issues, enabling them to make data-driven decisions that lead to improved efficiency and growth.

What tools are commonly used for data visualization?

Popular data visualization tools include Tableau, Power BI, D3.js, and ggplot2. These tools allow users to create interactive and informative visual representations of their data.

Costantine Edward

Costantine Edward is a digital marketing expert, freelance writer, and entrepreneur who helps people attain financial freedom. I’ve been working in marketing since I was 18 years old and have managed to build a successful career doing what I love.