While we all know that data is key to telling an impactful story, few understand how to use these points to spin meaningful tales that will resonate with their audience.
As marketers, we use data visualization to go hand in hand with our narrative. Data is essential, powerful, and when paired with a good story – it can be very persuasive.
Which is why we put together this interactive site made up of 85 eye-catching data visualization examples, to inspire and motivate you in your next project. Click the below image to check it out!
So how do we use data to peddle our message to those we want to reach? We’ve put together a step-by-step guide on how to do the following:
- How to gather data
- How to identify interesting stories in data
- How to curate assets (icons, photos) to go with the data and message
- How to use data visualization tools (charts and graphs) for your chosen story
- How to use design elements (such as colors or layout)
- How to provide references that bring about credibility
Ready? Let’s get started.
1. How To Acquire Data?
To start off, you have to first acquire your data. Lucky for you, there are a myriad of free resources that you can use on the web that are available for public use. Below are just some from this Forbes list to get you started, and we also shared a huge list of data databases for you dig through here.
US Census Bureau: A large resource on US citizens which covers population data, geographic data, and education.
European Union Open Data Portal: Another place to explore government data, but it is based on data gleaned from institutions in the EU of course.
Datacatalogs.org: Yet another open government data resource, except this one allows you to peer into data from the US, EU, Canada, and more.
NHS Health and Social Care Info Centre: You can find health data sets from the UK National Health Service in this database.
Amazon Web Services Public Datasets: This is a huge resource of public data, which includes the 1000 Genome Project, as well as NASA’s database of earth satellite imagery.
Google Finance: This is a database made up of 40 years’ worth of stock market data, which Google updates in real time.
Besides gathering data that’s available in the public realm, you’ll also have the need to visualize internal data (whether it’s your own or belonging to a client) for reporting and transparency purposes.
Below are a few resource examples where you can glean this data:
A tool for marketers to track and analyze user interaction on their Facebook fan pages. It helps you determine the best time of day and week to post, and to also figure out which types of content your audience would like to read. Also useful when it comes time to gathering data for your social media report on Facebook page performance.
Google Data Studio – A tool that allows you to turn your own, or a client’s analytics data, into easily digestible reports through data visualization. The reports are simple to peruse for non data-savvy folks and are easily customizable through a variety of graphs. You can even brand the reports with your logo. This is especially useful when you are gathering data on the performance of your company blog and to develop your content marketing strategy.
The below example is a Google Adwords template on data studio.
Mailchimp Analytics – A tool for marketers to dive deeper into the performance of their email campaigns, and to also learn more about their readers. It comes in handy when it comes time to crunch some numbers for your email reports, and pairs nicely with the likes of Google Analytics if you want to do more digging.
2. How To Identify Interesting Stories Using Data
Now that you have your data sets and a story you’d like to tell, it’s time to first develop a central theme and story structure.
According to Buzzsumo, you can develop a story structure and central theme using the below five core narratives:
Identify Trends:For example, are people using their PCs less in favor of tablets and smartphones? Is there a growth in online shopping behavior in a certain country or region? Trends are indicators that there is a general direction in which something is changing or developing, and it’s something you should look out for in your data.
Even a flattening trend can tell a story, like the graph on Twitter below.
Using rankings: For example, is Vienna consistently being ranked number one in the list of most liveable cities, while Vancouver is in second place? Are there certain areas in the United States that have higher crime rates than others? Rankings tell a story using data about the relationship between items on a list.
Draw comparisons: For example, how is Apple performing on the stock market in comparison to Microsoft? How much more dedicated to work-life balance is France, compared with Japan? Comparisons tell a side-by-side story between either polar opposites, or very similar things.
Using Twitter as an example again, this time we’ll compare the social network with the meteoric growth of Facebook.
Look for surprising or counterintuitive data: For example, the sale of pop tarts apparently increased sevenfold before a hurricane. Seems surprising, but if you dig deeper – it seems that in anticipation for a natural disaster, people seek out comfort foods. Data that challenges previously confirmed knowledge of what people know to be true, tells a great story.
Point out the relationship between data points: For example, the influx of bitcoin mining companies moving to Canada is leading to rising costs in energy prices for local residents. Relationships between data points tell a story by showing a connection or correlation between a number of variables – like the popularity of bitcoin and expensive utility bills.
3. How To Curate Assets That Fit?
Now that you’ve got your theme and story structure up and running, it’s time to curate the right assets, such as icons and images, to be paired with your data and message.
Jonathan Corum, the science graphics editor for the New York Times, shares a number of examples via his “Design for an Audience” presentation at the University of Copenhagen – which shows you how to use assets to tell a visual story.
The below visual, which features mammal tracks discovered on a rock slab in Maryland that appeared to be from dinosaurs can be looked at as an example.
What Corum did was take small related icons added on an image of the rock slab, used a relative scale, and tried to create a story around it. He also used colored silhouettes of the dinosaurs that might have made those tracks to further illustrate the story.
In another example, Corum uses a map to show the intensity of the drought in the western areas of the United States. This example also shows how to use clear and concise labeling to pair with assets to tell a story.
You can also consider being creative and merging your data visualizations with your subject matter. For example, if you are presenting on the essential nutrients in coffee – you could turn your pie chart into a cup of joe.
4. Which Charts and Graphs Are The Best Fit?
Your charts and graphs will play a key role in helping you present your data, so it’s best to get acquainted with them. Of course, not every graph will serve the same purpose, so let’s look into the purpose of each chart/graph and what they’re best used for.
Dot chart: They’re efficient, give more details, save on pixels, and you can really highlight the most important point of your story if you use different colors.
How can they be used? As the simplest of all statistical plots, dot charts are useful for small to moderately sized data sets and are most helpful in highlighting clusters and gaps, as well as outliers.
See the below example from the University of Buffalo.
Pie charts: Easy for non data-savvy folks to understand, can pick up on data comparisons at a glance because it represents data visually as a fractional part of a whole. Pie charts are at their best when there are less slices as too many pieces of data will render it less effective.
How can they be used? Pie charts are best used when you are trying to represent pieces of data that make up an entire category. For instance, the market share of each of your direct competitors within the visual marketing arena.
Line graphs: Similar to bar graphs, line graphs can be used to track changes over short and long periods of time. They are typically more nimble than bar graphs and are helpful in representing when smaller changes exist.
How can they be used? Line graphs can be used to compare changes over the same period of time for more than one group. So for example, comparing the weather in St. Louis throughout the year, whether it’s high or low temperatures.
Check out the below example from Sophia.org.
Bar graphs: Consisting of two axes, bar graphs are especially useful in comparing data among a handful of categories at a glance, and can run horizontally or vertically.
How can they be used? Bar graphs are typically used to show big changes in data over time, for example comparing electricity costs in cities across North America.
Area graphs: Area graphs is like the sister graph to line graphs. They can also be used to track changes over time for one or more groups. It would make more sense to use an area graph to track changes in two or more related groups that make up one whole category.
How can they be used? For example, you can use an area graph to compare the energy-related co2 emissions in Arizona vs. Massachusetts.
5. Design Elements To Know When Presenting Data
Perhaps you’ve done some reading the importance of design elements when creating visual projects, such as typography, layout, and visual hierarchy – but exactly how does it play out when you need to present data?
According to the data visualization checklist from Stephanie Evergreen and Ann Emery, here are some things you need to consider:
1. Layout: Pay attention to proportions. Your readers should be able to take a ruler, measure the length or area of your graph, and find that it matches the relationship in your underlying data.
Your graphs should be free of any decorative elements, although you can use graphics, such as icons, that serve to support interpretation.
2. Colors: When it comes to your color scheme, make sure that it is intentional. It should either your organization’s or client’s brand colors.
Be aware of how your use of color can direct the eye. Pieces of data that are considered supporting or less important, should be in muted or grey colors.
For example, in the below data visualization – the creator has chosen to use green only in the chart to represent his data – which works to focus attention on the graph.
Consider hierarchy when it comes to your text. Your titles should be the largest in size, followed by subtitles, then your labels, and finally – source information. The larger the text, the higher in importance. Your text should be horizontal only, and in 9 points (if in print) and 20 points (if on screen).
Data Design Do’s And Don’ts
According to an ebook that HubSpot published on data visualization design, here are some of its key “do’s and don’ts” when it comes to data design
- Do use icons to improve comprehension and eliminate the need for too much labelling
- Do visualize your data in a way that makes it easy to compare values
- Don’t use more than six colors in a single layout as it can scatter attention
- Don’t use 3D charts as it can skew the perception of your data visualizations
Don’t Forget To Cite Your Sources
So there you have it, a top to bottom guide on how you can gather data and tell effective stories with it. It goes without saying, but is worth mentioning, that you should cite your sources in an appropriate way.
Things to consider listing out for your data visualizations would be:
- The author
- Dates of data generation
- Date of access
- Where the data is housed
- The publisher of the data
- The URL
Other than that, you’ve got all the basics here and are well on your way to becoming a storyteller of data.
In Piktochart, we have a myriad of charts and graphs under ‘Tools’ which makes it easy to visualize your data. Have a look and let us know what you think!