Best Data Visualization Techniques For Better Data Story Telling

The beauty of data lies in translating it into digestible information. When adequately mined, data helps you understand customer persona, campaign analytics, and pretty much improve your bottom line. Yes, data is life! And one way to get a full grasp of it is by visualization. To visualize data, you’ve got to have a good grasp of data visualization best practices. If you don’t know where to start, you can start by taking a close look at some of the best data visualization examples.

Let’s face it, looking at some numbers or sketches is an easy way of knowing what the data is all about. Different data Visualization techniques like graphs, charts, and design elements can pretty much help you process information quickly and efficiently.

Data visualization is a systematic way of interpreting data using visuals. Looking up data using tools like charts and graphs is much easier than the tedious work that goes into reading up a bulk volume of texts.

Here’s the thing, the human brain understands visuals better than text. Yes, the brain tends to retain information displayed using visuals. And if you can take advantage of this, you would be able to process more information in no time without losing sweat.

Here comes the big question — what are data visualization best techniques, and what are some data visualization examples to help you get started. You need to be aware of the awesome visualization library which can help you to create amazing visualizations.

Well, you will discover all these and more in this guide. Let’s dive right in.

Data Visualization Best Techniques

Whether you are preparing for a sales pitch, a presentation, or anything in-between, data visualization helps to get the message across. It’s an easy way of enhancing your audience experience, and possibly compel them to take the desired action.

The primary aim of data visualization is to help your readers make sense of the information displayed. You are not the primary focus — focus on delivering top-notch value to your audience.

Here are some data visualization best techniques to help you get started.

1. Data visualization is audience-specific

Knowing how to create data visualization is not enough, you must understand who your audience is. A solid understanding of your target audience coupled with a sleek creating tool could be the difference between a not-too-good work and a heroic job.

You should have your audience in mind while creating data visuals. This way, you get to create a work that is fully understood by your audience.

2. Keep your data clean

Before translating your data into visuals, the raw data set has to be kept clean. Data cleaning pretty much entails everything that goes into sieving out inaccuracies or anomalies in a data set. If left unclean, inaccuracies in a data set could alter your results in the long run.

3. Choose the right chart

The wrong chart type not only leads to data misinterpretation but also breeds confusion. To get the most out of the popular data visualization, you’ve got to choose the right chart. This way, your audience gets to easily understand the data displayed on the chart.

4. Layouts should be represented using predictable patterns

The human eyes are wired to recognize indicators. When indicators are easily identified, you would easily pinpoint vital information. To make sense out of your data, the pattern should not be random or complex. The issue with random patterns is they are not easily understood.

All in all, it would be best if you use predictable patterns that make sense to the audience. And sequential or numeric data representation is possibly the best technique out there.

5. Properly label the data visualization

Charts are one of the best ways of identifying patterns in data. But if you want to take it a step further to pinpoint specific values in a given data, then you’ve got to use labels.

Let’s say you are presenting some findings or showcasing an experimental setup, labels will help give an overall overview of the system — figure can’t do that. You’ve got to use captions alongside the figures — where the caption explains the figures. Aside from the explanation of the figure, captions provide additional information that would be helpful in the interpretation of the entire system.

6. Tell data stories using attractive colors

Colors add spice to your data visualization — it’s a vital piece of the entire system! With colors, you get to easily communicate your data to your audience. For instance, in creating categorical data, distinct color is used for each category, while different shades of a single color can be used for sequential data.

7. Choose the right data visualization tool

Typically, visualization tools help the user identify relationships (or correlations) between data. This way, the user gains meaningful insights from such data. Here’s the thing, making sense of a large volume of data is no easy feat! But with the right visualization tool, you can pretty much make meaning from any data set.

Yes, regardless of how complex a data set may be, visualization tools help you to see patterns and trends from such a data set. By exploring these patterns, business leaders get to pay more attention to what’s important. Also, it helps them to focus on relevant areas that would likely drive more business growth.

That’s not all…

Data visualization helps you to easily identify errors. If you identify any wrong actions or trends, you would quickly remove them from your analysis without losing sweat.

Here comes the big question — what’s the best tool to help you achieve all these and more.

Well, ChartExpo is your best shot! Yes, ChartExpo is a best data visualization tool that provides an in-depth analysis of sales, marketing, and product reports. Regardless of your industry, ChartExpo will help you pinpoint trends in your reports. This way, you would direct your energy and focus on things that would yield more profit.

8. Study your findings and insights

By now, you probably know that data visualization helps you identify data correlations — that’s good, but it’s not enough! You have to take an extra step by studying your findings and drawing meaning from your insights.

Knowledge gotten from these insights helps you to readjust your focus, and direct your energy to things that would help you achieve your business goals.

Furthermore, these insights help you to gain a better understanding of customer behavior. An understanding of customer behavior helps you to refine your already existing products or create new ones to suit your target customers.

Studying your findings and insights is arguably the most important data visualization best practice.

Now you have a good grasp of the data visualization best techniques, here are ideas for better data visualization.

Ideas for better data visualizations

Hyper-personalization is arguably the best way to win in today’s world. After all, hyper-personalization helps business owners target customers that best fit their interests.

Let’s say you are surfing online for some exotic cars or running shoes. After your search online, you would probably start seeing Facebook ads or Google ads that show trending cars and quality running shoes. Well, that’s hyper-personalization at work — and it’s good for business!

Data used for hyper-personalization is mined from the customers, and looking at the raw data will do you no good to your overall strategy. To get the most out of such data, you’ve got to apply visualization!

Data visualization is a reliable way of translating data and adjusting various variables to have a good grasp of their effect.

Here are some techniques for better data visualization.

Scatter diagram: helps to understand relationships and distribution

In a scatter diagram, the categories of data are presented using a circle color, while the volume of data is represented using the circle size. Scatter plots are used to visualize the relationship between or the distribution of different variables.

Visualization Source: ChartExpo

From the chart above, when the price is highest extreme right in yellow color the no. of sales are lowest. Whereas in case of green dot on top left showing lowest price is having highest no. of sales.

The scatter diagram shows that the most profitable (and frequent) customers are females. But how does such insight help the business owner? Well, the business owner could opt to direct more marketing efforts into promoting products to female customers. But looking out for better ways of engaging male customers is not a bad idea.

Whatever route the business owner chooses, it should be aligned with the overall business objectives.

Treemaps — display hierarchies and compares values:

Treemaps show comparative value and hierarchies between categories and subcategories of a data set. It gives an instant sense of the most important areas while retaining details of the overall system.

To get the most out of Treemaps, you’ve got to nest color-coded rectangles inside one another, and they are weighed to show their share of the system.

Visualization Source: ChartExpo

The Treemap above shows the value of various animal categories. From a quick look, you would see that dogs are the most popular across all subcategories.

Progress Chart –Shows Comparisons:

Within a category, a progress chart shows the positive and negative differences of a fact. The change is found on the left-hand side of the chart, and it’s shown using color-coded bars, while facts are found on the right-hand side, and you get to see them as group bars.

Ideally, a progress chart helps you to observe changes happening in a system over a period, and also shows you the progress made in the attainment of a goal.

By providing a reliable way of monitoring and prioritizing your primary goals, Progress Chart helps the user draw insight that would help in making strategic decisions in the long run.

Visualization Source: ChartExpo

A quick look at the chart above will help you pinpoint the right mobile brand that is generating the most sales. The chart is divided into two sections — one section shows the previous and current sales, while a different section shows the sales margins.

The sales margin is in respect to the previous and current sales — and it shows whether the sales are tilting towards the negative or positive margin. This way, you get to easily identify the mobile brand that’s generating the least sales. When such a brand is identified, you can pretty much focus more energy on the marketing and sales of the mobile product.

Pareto Chart — Comparisons:

The Pareto Chart follows the Pareto principle which states that when several factors act on a system (or situation), a few factors will make the most impact. It’s all about identifying the most impactful factors in any situation.

If you desire to make significant progress in business, you’ve got to get your priorities straight. Yes, priorities determine how and where you will be focusing your energies — and the Pareto Chart helps you get your priorities right!

The Pareto Chart helps organize and display information so you get to see how important a problem (or causes of a problem) is. It’s a vertical bar chart that puts things in order — ranging from the highest to the lowest item. Ideally, the items in the Pareto Chart are affected by defined factors like cost, frequency, and time.

Visualization Source: ChartExpo

From the chart above, you would see that most customers are concerned about the Parking and Sales Rep. If the business owner handles these complaints, it would go a long way to boost customer satisfaction.

Radar Chart — Compositions & Comparisons:

A radar chart is made of a two-dimensional plane that compares multiple variables. Most times, the variables are three or more. Simply put, a radar chart provides visual information about three or more variables.

In a typical radar chart, there are various axes from a common central point, and these axes are uniformly drawn from one another. There are times when spider charts can be drawn from the different grids formed within the axes.

Unlike column charts, radar charts can accommodate multiple variables without creating clusters. To get the most out of radar charts, you should have four or less metrics.

Visualization Source: ChartExpo

From the chart above, you can easily see the qualities of the teachers. It’s sleek, and easy to understand. Grace is pretty much the best teacher on the chart.

FAQs:

What are the principles of good data visualization?

Some of the key principles of good data visualization include identifying the best visual, creating a balanced design, and focusing on important areas. Other principles include having a simple visual, creating interactivity, comparing parameters, and using good patterns.

What is the difference between data analysis and data visualization?

Data analysis pretty much involves bringing structure and order to a data set. It helps translate data into usable information. On the other hand, data visualization involves the translation of data using a graph, chart, or other visuals for easy interpretation and analysis.

What makes a bad data visualization?

Bad data visualization consists of bad data, wrong data visualization tools, inconsistent scales, excessive information or color, and data misinterpretation.

Wrap Up:

Data visualization is arguably the best way of translating data into usable information. To get the best out of it, you’ve got to have a good grasp of data visualization best techniques, and some good data visualization examples will go a long way to show you how data is represented using visualization tools.

Aside from promoting your brand, there are other benefits of data visualization in PPC reporting. Let’s face it, it would be quite challenging to make sense of raw data without good visualization tools. To get started, you’ve got to explore advanced tools like ChartExpo.