Flag

We stand with Ukraine and our team members from Ukraine. Here are ways you can help

Home ›› Business Value and ROI ›› 6 Key Questions to Guide International UX Research ›› Five Steps to Storytelling with Data

Five Steps to Storytelling with Data

by Dominic Quigley
4 min read
Share this post on
Tweet
Share
Post
Share
Email
Print

Save

We’re surrounded by more data than ever, and as the mountains of information continue to grow, storytelling techniques can help designers make sense of it all.

In the pre-digital era, data was a subject for mathematicians and scientists. Now, one way or another, we can’t escape it.

Our constant use of online services not only relies on data, we are also a continuous source of data, generating information about all aspects of our lives.

Whether it’s data about the human body—thanks to the rise of wearables—our energy consumption at home, or data tied to our personal finance: we’re creating mountains of data, and now we need to find ways to make sense of it.

The rise of personalized data is poised to be a hot topic as companies seek to deliver real benefits from the information gathered on consumers. The challenge for designers lies in finding a way to reduce the complexity posed by such vast amounts of data and give data a human shape.

Data has to be accessible to the average person. It also has to provide the user with actionable insight in a way that is meaningful and accessible. This is where the true power of design can really make a difference: by using visualizations to help people navigate the confusing world of data we can improve lives.

Data visualization has come a long way since its formative days as the basic pie chart invented over 200 years ago. Now, thanks to the huge upsurge we’ve seen in data and the discourse around its usage, a new design language is emerging that is elegantly simplifying the big data mess into beautiful and meaningful visualizations.

So regardless of whether you’re bringing shape to data on health and wellbeing, shopping habits, or in editorial, Fjord has identified five core principals to follow when embarking on a data visualization challenge:

1. Understand the Source

Make sure you know the data you’re working with. This is the crucial first step in making sense of data. You need to understand the bigger picture: Why has it been collected? What value does the organization put on it? Who is the user? How can it be used to greatest effect? This insight will lay important foundations for the creation of a visualization that’s both meaningful and human.

2. Identify the Narrative

Good data visualization is so much more than a beautiful picture, it tells a story that can be understood by anyone. It’s therefore essential that you identify the story you want to tell first and then use the data as way of bringing that story to life.

For example, we recently helped mobile operator 3 Sweden become more customer-centric and transparent by re-designing the often-confusing monthly phone bill. Instead of continuing to present their customers with an incomprehensible list of numbers, they wanted to create something much more helpful and transparent.

Good data visualization tells a story that can be understood by anyone.

The result is My 3, an app that lets customers see their usage data in real-time so they know exactly where they are with respect to their plan. By using data visualizations we have been able to create a beautiful and innovative way to give customers access to their data that also demonstrates 3’s commitment to customer care.

3.Define the User Experience

Ensure you use data to guide but not dictate the overall experience. Data should act as a backdrop of understanding and learning that allows the user to create his or her own experience. It’s also worth exploring ways to deepen the insight you can share with the visualization and give people the flexibility to interpret the data in the most meaningful way to them. After all, an experience that delights is an experience that people will remember and use again and again.

4. Simplicity Rules

Data visualizations exist to inform the user, they’re not an excuse to overload someone with information they don’t need to know. As a designer, it’s your role to focus on simplicity, taking complex or disparate information and making it tangible, understandable, and, importantly, more human. Remember, where simplicity reigns, the user understands.

5. Avoid Reinventing the Wheel

Try to tap into existing behaviors and understandings around data visualizations. It will make your design more accessible to a broader range of people. There’s a reason why the pie chart is so widely used: people understand what it shows. There’s an innate elegance in designing visualizations this way, as they’ll have a greater impact and be immediately understood.

A Design-Led Approach

Good data visualizations are not only masterpieces of design, they are valuable tools helping us to interpret previously inaccessible content as something much more meaningful and actionable. As increasing numbers of organizations wake up the power and potential in their data, design will play an even bigger role translating something confusing into something that helps people. The trick is to take a design-led approach that puts the user first and focuses on simplicity in order to create an experience that never ceases to delight.

post authorDominic Quigley

Dominic Quigley, Focusing on visual design, UI design, and the experience, Dominic is a key member of the Fjord London team. Over his 15 years experience he's worked with a wide range of clients including financial services, retail, telcos, property, travel and transport and technology brands. Dominic has led transformative projects at Fjord by leveraging key insights and strong experience in a wide range of design principles to bring to life innovative multi-channel, multi-context services. Fjord is part of Accenture Interactive.

Tweet
Share
Post
Share
Email
Print

Related Articles

Article by Eleanor Hecks
8 Key Metrics to Measure and Analyze in UX Research
  • The article outlines eight essential metrics for effective UX research, ranging from time on page to social media saturation
  • The author emphasizes the significance of these metrics in enhancing user experience and boosting brand growth.

Share:8 Key Metrics to Measure and Analyze in UX Research
6 min read

Repetitiveness, complicated setups, and lack of personalization deter users.

Article by Marlynn Wei
​6 Ways to Improve Psychological AI Apps and Chatbots
  • Personalized feedback, high-quality dynamic conversations, and a streamlined setup improve user engagement.
  • People dislike an overly scripted and repetitive AI chatbot that bottlenecks access to other features.
  • Tracking is a feature that engages users and develops an “observer mind,” enhancing awareness and change.
  • New research shows that users are less engaged in AI apps and chatbots that are repetitive, lack personalized advice, and have long or glitchy setup processes.
Share:​6 Ways to Improve Psychological AI Apps and Chatbots
3 min read
Article by Josh Tyson
Meet the Intelligent Digital Worker, Your New AI Teammate
  • The article introduces the concept of Intelligent Digital Workers (IDWs), advanced bots designed to assist humans in various workplace functions, emphasizing their role in augmenting human capabilities and enhancing organizational efficiency.
Share:Meet the Intelligent Digital Worker, Your New AI Teammate
3 min read

Did you know UX Magazine hosts the most popular podcast about conversational AI?

Listen to Invisible Machines

This website uses cookies to ensure you get the best experience on our website. Check our privacy policy and