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Visualization and Personalization: Making Data Meaningful

Sarah Morgan

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At the start of 2017, our POV, “Innovation During Disruption and Change,” called out some of the shifts in technology, society, medicine and marketing that we see changing the world in which we work. Throughout the year, we’re taking a closer look at some of the concepts we highlighted in that report.

Our increased ability to gather, analyze and learn from data might be one of the greatest gifts the rise of digital has given marketers. One estimate says that by 2020, worldwide revenues related to big data and business analytics will be greater than $210 billion.

Data can be gathered on just about anything, but for marketers of all types, the goal is to understand our audiences’ attitudinal, behavioral and transactional habits so we can anticipate their wants, needs and preferences. In the pharma and healthcare settings, these insights can be particularly valuable when applied to improving the lives of people who have chronic diseases.

Visualization: Getting the Message Across

Even if you have the right data-collection tools, and the means to analyze what you gather, the information is useless if you don’t present it in a way that others can understand and learn from. Data visualization makes it easier to recognize patterns that might have been overlooked in a plain-text document. And since humans can process images so much faster than text — and because our attention spans are growing shorter every day — it makes sense to translate raw numbers into easily understandable visuals in order to literally see the “big picture.”

Marketers know the value of insights gathered from data, but how do data analytics and visualization bring value in the healthcare setting? Here are two examples:

  • In a course on data visualization at Johns Hopkins University, undergraduate students developed an app that graphed 1,000 data points to help doctors infer the cause of pediatric pneumonia cases and tailor treatment accordingly.
  • Another app used in a hospital emergency department takes patient prescription data and creates a timeline representing a year’s worth of medication history, providing a tool that minimizes medication errors in time-sensitive scenarios. 

Personalization: Making Data Work for Everyone

As we’ve said before, personalization matters. Fitness apps are a great example of how easy-to-understand data visualization can lead to behavior changes. Being able to see patterns in your sleep cycle, for example, will more likely motivate you to adjust a bedtime routine than simply receiving a phone alert that says it’s time for bed.

Data can and should be used to personalize messaging and proactively reach audiences. And the more we learn about what our audiences want and need, the better we get at providing it. Powerful combinations of information can help customers, and, by extension, brands, by making it possible to be useful assistants. Imagine a situation where your smart phone or smart watch, or even a home assistant like Amazon’s Echo, could help you manage even the smallest daily details of your health: “Good morning! Your data show that you might be coming down with a cold. There’s a Walgreens half a mile ahead, and the Alka-Seltzer cold medicine you got last time you had these symptoms is on sale in Aisle 7!” Marketers now have the ability to tailor content far more precisely than ever before. The trick, of course, is personalizing messages without crossing the line into “creepy.”

Best Practices for Data Visualization

Regardless of what you’re interpreting, following a few simple rules will help ensure your audience understands what you’re trying to tell them.

  • Make it intuitive. For example, bar graphs or histograms are often easier to make sense of than pie charts. Infographics are everywhere these days, and for good reason: they take a lot of information and make it easy to digest and, if done well, pleasant to look at.
  • Let the data tell the story. It’s true that you can pretty much make numbers say whatever you want them to, but that doesn’t mean you should.
  • Be careful with colors. In Western cultures, for example, red often connotes “stop” or “danger,” whereas green means “go,” or “safety.” Consider your audience and choose carefully when selecting colors.

Conclusion

Data is simply information: facts and figures that can be collected, processed and analyzed. The digitization of data takes us from the days of reference libraries and handwritten ledgers to a world where we can connect the dots to a degree never imagined possible. What are you doing to help connect the dots for your audiences?

 

 

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