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How UX design can help make sense of Big Data

(Tech News) UX design is not always understood for the full potential it offers, and the industry’s approach to Big Data my untangle that ball of yarn.

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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):

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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.

“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.

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.

The American Genius is news, insights, tools, and inspiration for business owners and professionals. AG condenses information on technology, business, social media, startups, economics and more, so you don’t have to.

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3 Comments

3 Comments

  1. elijahmay

    October 20, 2014 at 1:44 pm

    Phenomenal

  2. Tinu

    October 20, 2014 at 1:51 pm

    That really IS fascinating. What a useful article. Thanks AGBEAT.

  3. Pingback: How UX Can Add Value to Analytics | UX Design | Posts about UX, UI, IA, design strategy, data analytics, and more UX ramblings

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Tech News

Chatbots: Are they still useful, or ready to be retired?

(TECH NEWS) Chatbots have proven themselves to be equally problematic as they are helpful – is it time to let them go the way of the floppy disk?

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Man texting chatbots leaning against a brick wall.

All chatbots must die. I’d like to say it was fun while it lasted, but was it really?

I understand the appeal, truly. It’s a well established 21st century business mantra for all the side hustlers and serial entrepreneurs out there: “Automation is the key to scaling.” If we can save time, labor, and therefore money by automating systems, that means we have more time to build our brands and sell our goods and services.

Automation makes sense in many ways, but not all automation tools were created equal. While many tools for automation are extremely effective and useful, chatbots have been problematic from the start. Tools for email marketing, social media, internal team communication, and project management are a few examples of automation that have helped many a startup or other small business kick things into high gear quickly, so that they can spend time wooing clients and raising capital. They definitely have their place in the world of business.

However promising or intriguing chatbots seemed when they were shiny and new, they have lost their luster. If we have seen any life lesson in 2020, it is that humans are uniquely adept at finding ways to make a mess of things.

The artificial intelligence of most chatbots has to be loaded, over time, into the system, by humans. We try to come up with every possible customer-business interaction to respond to with the aim of being helpful. However, language is dynamic, interactive, with near infinite combinations, not to mention dialects, misspellings, and slang.

It would take an unrealistic amount of time to be able to program a chatbot to compute, much less reply to, all possible interactions. If you don’t believe me, consider your voice-activated phone bot or autocorrect spelling. It doesn’t take a whole lot to run those trains off the rails, at least temporarily. There will always be someone trying to confuse the bots, to get a terse, funny, or nonsensical answer, too.

Chatbots can work well when you are asking straightforward questions about a single topic. Even then, they can fall short. A report by AI Multiple showed that some chatbots were manipulated into expressing agreement with racist, violent, or unpatriotic (to China, where they were created) ideas. Others, like CNN and WSJ, had problems helping people unsubscribe from their messages.

Funny, shocking, or simply unhelpful answers abound in the world of chatbot fails. People are bound to make it messy, either accidentally or on purpose.

In general, it feels like the time has come to put chatbots out to pasture. Here are some helpful questions from azumbrunnen.me to help you decide when it’s worth keeping yours.

  1. Is the case simple enough to work on chatbot? Chatbots are good with direct and short statements and requests, generally. However, considering that Comcast’s research shows at least 1,700 ways to say “I want to pay my bill,” according to Netomi, the definition of “simple enough” is not so simple.
  2. Is your Natural Language Processor capable and sophisticated enough? Pre-scripted chatbots are often the ones to fail more quickly than chatbots built with an NLP. It will take a solid NLP to deal with the intricacies of conversational human language.
  3. Are your users in chat based environments? If so, then it could be useful, as you are meeting your customers where they are. Otherwise, if chatbots pop up whenever someone visits your website or Facebook page, it can really stress them out or turn them off.

I personally treat most chatbots like moles in a digital whack-a-mole game. The race is on to close every popup as quickly as possible, including chatbots. I understand that from time to time, in certain, clearly defined and specific scenarios, having a chatbot field the first few questions can help direct the customer to the correct person to resolve their problems or direct them to FAQs.

They are difficult to program within the expansiveness of the human mind and human language, though, and a lot of people find them terribly annoying. It’s time to move on.

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Get all your digital organization in one place with Routine

(TECH NEWS) Routine makes note-taking and task-creating a lot easier by merging all your common processes into one productivity tool.

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A desk with a laptop, notepad, smartphone, and cup of coffee settled into an organized routine.

Your inbox can either be your best friend or your worst enemy. Without organization, important emails with tasks, notes, and meetings can become a trash pile pretty quickly. Luckily, there are a lot of tools that aim to help you improve your efficiency, and the latest to add to that list is Routine.

Routine is a productivity app that combines your tasks, notes, and calendar into one easy-to-use app so you can increase your performance. Instead of having to switch between different apps to jot down important information, create to-do lists, and glance at your calendar, Routine marries them all into one cool productivity tool. By simply using a keyboard shortcut, you can do all these things.

If you receive an email that contains an actionable item, you can convert that email into a task you can view later. Tasks are all saved in your inbox, and you can even schedule a task for a specific day. So, if Obi-Wan wants to have Jedi lessons on Thursday, you can schedule your Force task for that day. Likewise, chat messages that need follow-up can also be converted into tasks and be scheduled.

To enrich your tasks, notes can be attached to them. In your notes, you can also embed checkboxes, which are tasks of their own. And if you have tasks that aren’t coming from your inbox, you can import them from other services, such as Gmail, Notion, and Trello.

To make sure you can stay focused on the events and tasks at hand, Routine makes it easy to take everything in. By using the tool’s keyboard-controlled console, you can access your dashboard to quickly see what tasks need to be addressed, what’s on your calendar, and even join an upcoming Zoom session and take notes about the meeting.

Routine is available for macOS, iOS, web, and Google accounts only. Overall, the app centralizes notes and tasks by letting you create and view everything in one place, which helps make sure you stay on top of things. Currently, Routine is still in beta, but you can get on a waitlist to test the product out for yourself.

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Tech News

The paradox of CAPTCHAs: Too smart for humans vs AI?

(TECH NEWS) AI is catching up to our cybersecurity technology and often tricking humans too — so what’s next for CAPTCHAs and the internet?

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Person using phone with laptop to verify CAPTCHAs and code.

We’ve all encountered it before: The occasional robot test that feels impossible to beat. If you’ve felt like these tests, also known as CAPTCHAs, have gotten harder in the last couple of years, you aren’t wrong—and the reason is as ironic as it is baffling.

Simply put, AI are just as good as—and often better than—humans at completing CAPTCHAs in their classic format. As machine learning and AI become more advanced, the fundamental human attributes that make consistent CAPTCHA formats possible become less impactful, raising the question of how to determine the difference between AI and humans in the future.

The biggest barrier to universal CAPTCHA doctrine is purely cultural. Humans may share experiences across the board, but such experiences are typically basic enough to fall victim to the same machine learning which has rendered lower-level CAPTCHAs moot. Adding a cultural component to CAPTCHAs could prevent AI from bypassing them, but it also might prevent some humans from understanding the objective.

Therein lies the root of the CAPTCHA paradox. Humans are far more diverse than any one test can possibly account for, and what they do have in common is also shared by—you guessed it—AI. To create a truly AI-proof test would be to alienate a notable portion of human users by virtue of lived experience. The irony is palpable, but one can only imagine the sheer frustration developers are going through in attempting to address this problem.

But all isn’t lost. While litmus tests such as determining the number of traffic cones in a plaza or checking off squares with bicycles (but not unicycles, you fool) may be beatable by machines, some experts posit that “human entropy” is almost impossible to mimic—and, thus, a viable solution to the CAPTCHA paradox.

“A real human being doesn’t have very good control over their own motor functions, and so they can’t move the mouse the same way more than once over multiple interactions,” says Shuman Ghosemajumder, a former click fraud expert from Google. While AI could attempt to feign this same level of “entropy”, the odds of a successful attempt appear low.

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