How UX design can help make sense of Big Data

User Experience (UX) and Big Data

Big Data has become a more widely understood concept, but many companies from entrepreneurs to corporate conglomerates are failing to tap into the full potential of all of the data available or already being collected.

Charlie Claxton is the Chief Creative Strategist for UpTop, a full-service, web-based software application design firm that focuses on user experience design, conversion and mobile. He has led successful design efforts for Expedia, Amazon and Microsoft as well as growing early-stage companies and is a frequent speaker on UX design and conversion.

In his own words below, he identifies how the answer to the Big Data ball of yarn could actually be UX (user experience):

Okay, you’ve collected piles of data. Now what? How do you transform an overwhelming amount of information into actionable insights?

This is a common problem facing many businesses today. Massive amounts of data, often referred to as ‘Big Data,’ are being collected across every business sector. However, this data usually exceeds the processing capacity of conventional database systems.

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“The data is too big, moves too fast and doesn’t fit the strictures of common database architectures,” says Edd Dumbill, a data science analyst based in Silicon Valley. “To gain value from this data, you must choose an alternative way to process it.”

UX designers bring data to life

This is where the discipline known as user experience (UX) design comes into play.

UX designers bring the power of data to life by creating customized data visualizations and reporting solutions that make it far easier for companies to reach important business conclusions. These solutions, coupled with an easy-to-use data collection system, can revolutionize the way you work.

By taking the massive amounts of data you’ve gathered, distilling it and then presenting it in a visual, user-friendly way, it’s possible for a variety of people to easily digest and use the data – a major departure from the days of huge spreadsheets.

What if you could get a quick view of data trends, then dive in for more details? What about overlaying two disparate data sources into a single chart based on a constant variable? No problem – just about anything is possible when you use UX design disciplines to crunch data. An effective business intelligence (BI) reporting solution designed around the needs of its end users can create data visualizations that were previously unheard-of.

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Data input can also benefit from good UX design

Data input is another crucial factor that can benefit from solid UX design. How are you collecting your data, and more importantly, how are you getting that data into your solution?
Bad data generates bad reports; the more seamless the data entry is within the daily workflow of the people involved, the more likely you are to get great data.

The ultimate goal is to gather clean data that empowers people – data that gives them what they need to do big things, no matter what their specific role is.

Great UX design can give a company:

• Insights into the direct correlation between sales and marketing campaigns.
• Competitive knowledge.
• Sales forecasts in relation to existing quota and product mix.
• Trends regarding how people feel about key words related to a company’s product offering.

How UX can identify untapped product opportunities

Perhaps most importantly, great UX design enables businesses to identify untapped product opportunities.

An effective, UX-infused reporting solution gives people an ability to act on the data right away. It should enable the people reviewing the data to blow right past the daunting “now what?” stage and immediately begin plotting next steps.

The bottom line: UX translates data

At the most basic level, the value of UX design lies in its capacity to translate the overwhelming into the informative. It gives you the ability to make better, faster decisions by creating a clear, accurate view of your data – customized to fit your specific needs. UX design comes with a dynamic set of tools that can transform the data analysis process and save companies both time and money, which has never been more important than it is today.

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