Data as the “new oil”: How data visualization increases the value of your app

Frank Zinghini

Founder & CEO

Today’s business landscape is constantly shifting due to new technologies and, more recently, the mass collection of data from the Internet of Things. This is particularly true when we look at the mobile application market, as apps collect an enormous amount of data. But success requires more than just data collection.  

It demands interactive data visualization—the visual presentation of data (think charts and graphs) as opposed to endless lists of numbers and statistics. Users get more value out of an app that incorporates data visualization, a value that is passed on to the business in several ways.

Why bother? The benefits of data visualization

Improved user engagement

App users have come to expect that data will be presented in a visually appealing way. No one wants to spend time sorting through results or searching for important data points. Users want important information and trends to jump out at them.

As social media continues to serve as a primary mode of communication, pictures and .GIFs make images one of the most common ways to send and receive information. But data visualization is about more than just the visual presentation of data—it is about presenting data in a meaningful way. Data visualization allows users to quickly digest information and identify patterns and trends.

An app that tracks your monthly spending can use data visualization to quickly show you that you’re spending way too much money on certain items without forcing you to manually scan your daily and weekly spending. A visual presentation lets you easily identify areas in which you are overspending, and lets you judge the value you receive from the expense. You may love your coffee, but a quick image showing that 10 percent of your income is going towards your daily java may make you rethink your coffee allowance.

Mint lets users track their spending while providing other money management features such as budgeting, tracking money across multiple accounts, and bill reminders. Areas where you are overspending are quickly identified through charts and graphs, so you can make immediate adjustments. Data visualization makes it easy for Mint users to access the information they need and use it to make informed decisions.   

Better interaction with data

Interactive charts and graphs allow users to extract more information from data. Hundreds or even thousands of data points can be correlated and presented to the user in one image. Adding interactions—for example, displaying more information when a user hovers over a point on a graph—makes it even more valuable.

Interactions can provide more opportunities to give users much more detail than they would otherwise get.  Athletes using an app to collect data from a fitness wearable might hover over different time intervals to obtain information on heart rate. Clicking on a point in the chart may open a window that contains detailed information on that particular workout, or provide weather information, or any number of other different variables. All of these can help inform decisions for future workouts, so the athletes can optimize performance.

The Fitbit app is a great example of how data visualization increases user interaction. Users can log workouts and sleep habits and see the impact on their day, and can see how their performance and output increase over time.

This type of data analysis in the app encourages users to interact with and use the app more. Increased interaction leads to loyal users who recommend the app to others.

Increased conversion rates

When users engage and interact with your app more, conversion rates increase. Not only do more customers download your app, but it becomes easier to get customers to complete in-app conversions, decide whether to upgrade to a paid version, make in-app purchases, or provide valuable feedback.

If we look at the Fitbit app again, the ability to visually share information with friends encourages other users to download the app. Attractive and interactive visuals entice friends and family to join.

Improved app lifecycle management

A successful app is always evolving to better serve end users. App designers and developers can see how users are interacting with the visual data graphics and use this information to make improvements.  Analyzing which visuals are most used and how users interact with them can serve as the basis for future iterations of the app.

A chart that is rarely accessed can likely be removed. Graphs that receive the most user interaction should be displayed more prominently upon launch and should be the focus of design improvements so they are easy to view and understand.

Now what? Best practices for data visualization design

Be selective

There may be more than one way to visually present data to users. Weigh the options and determine which approach will add the most value to users. Think about your user audience and what they are trying to achieve in order to make the best decision.

Test the User Experience

The User Experience (UX) is the most important element when it comes to data interaction. What happens when a user clicks or hovers over a visual? Do other elements on the page block their view? Issues such as this should be tested across devices and operating systems to make sure all visual displays are easy to read and interact with.

Clear and simple design

Keep labels and titles to a minimum. If a user will intuitively know what data is presented on a graph, there is no need to clutter the visual with extra words. This is particularly important for mobile apps, where screen space must be maximized.

Keep fonts simple (and, most importantly, legible) so they do not distract the user. Use colors that contrast each other so it is simple for users to distinguish between various statistics.

Optimize the visual display for mobile devices

Use a responsive and adaptive design so the visual display of data varies based on the device being used and how it is being used. For example, a chart should show less information when being displayed on a smaller screen size. The hidden information can be displayed when a user hovers over a certain point in the chart, increasing data interaction while also providing all pertinent information.

Users should be able to use standard touchscreen controls, such as swiping and zooming in to interact with charts and graphs. Be sure to take advantage of these features.

Order the data properly

Data should be placed in a way that makes sense depending on the use case. Sequential order of highest to lowest (or vice versa) is appropriate in many cases. Group like data elements together so they are easy for the user to find.

Embrace iterative design

Do not expect to develop the best data visualization design in the first release of your app. While user testing and UX design are very important, you should expect to make modifications to your data visualization approach throughout the life of the app.

Once you have a working model that will be valuable to your clients—something we like to call a Minimum Valuable Product (MVP)—release it to market. Then you can gather feedback from users and make updates to further improve the data visualization techniques.

Use data visualization tools

There are tools on the market that can make adding data visualization to your app easier. Examples include Plotly, Chart.js, and Raw. A review of these and other data visualization tools can help you decide which ones are right for your next project. If your design and development team is not well-versed in data visualization, tools are an easy way to wet your feet so you can better understand the value this technique brings to your app.

Data has great power in the app world if it is put to good use. The visual presentation of data in meaningful ways helps users pull additional knowledge from information, and it does this in ways that save users time and hassle. When users learn from your app and use it to make informed decisions, your app becomes integrated into their routine. Usage, downloads, and conversion rates increase, making data visualization good for the user and good for your bottom line.