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The Key Ingredients for Awesome UX


Now that we know a bit of history about UX (Part 1), and that we understand how our brain processes information (Part2), let’s move on to the process of UX, and understand why data is important in UX design and decisions.

Now that we know a bit of history about UX (Part 1), and that we understand how our brain processes information (Part2), let’s move on to the process of UX, and understand why data is important in UX design and decisions.

<h3>UX and Data<h3>

We talked about different levels of processing information and why understanding these levels is important for UX designers. Another big chunk of the UX process is understanding data.

A vast majority of UX decisions made are based on data, and good design is always driven by data. Data gives us insights into behavior, helps uncover issues, and fixes existing problems. Data can help us confidently predict user behavior and explore new opportunities, but it can be very challenging as well.

Every company collects vast amounts of data about their customers, their behavior, and their patterns every single day. The biggest issue with this data is that, oftentimes, it becomes just interesting numbers that lack any actionable insights. How do we make sense of it? Asking the right questions is the key—what are the problems we want to solve, and which metrics do we need to benchmark and track in order to address these problems?

<h3>Types of Data<h3>

Generally speaking, we have two types of data: Quantitative and Qualitative.

Quantitative data is anything that can be measured by numbers. Much of today’s data flows from analytics platforms—how many website visitors did you have, how did they get there, how many people clicked on a given button, what is the conversion percentage, how many abandoned their shopping carts, and so on.

Even the most organized sets of quantitative data don’t answer all the questions about UX: how did the product make them feel? Why did they take a specific action—or not? What were their expectations and were they achieved? This is when we need Qualitative data.

Qualitative data is collected through interviews, surveys, usability tests, etc., which can also be measured. System Usability Scale (SUS) and Single Ease Question (SEQ) are some of common usability testing techniques.

Generally, what people say they do and what they actually do is very different. When we compare online studies vs. in-person interviews and tests we see substantial differences in how people perceive products and services.

It’s crucial to look at both qualitative and quantitative data to make well-informed design decisions.

<h3>UX Process<h3>

UX process can vary from company to company or from product to product, but generally, the very first step is identifying issues. Once the issues are known, the next step is to articulate the purpose—what are we trying to achieve, and is it an issue worth solving? What measure do we need to increase or decrease?

We need to critically evaluate those issues and if they have a real purpose. There are plenty of products today that “solve” problems which don’t really need solving.

Third, successful UX processes examine analytics and big data. What is the user’s behavior, where do they come from, how many convert and how many don’t, how many click A and how many click B, and so on. Once there is an established understanding of some data averages, we can start looking at potential causes of the problem we identified. That’s when interviews and usability tests are conducted to discover how people are actually using the product, how it makes them feel…frustrated and annoyed if your product sucks, or happy and amazed if your product is great!

Having looked at big data and identified potential causes, we move on to first iterations—low fidelity mock-ups and wireframes, followed by early testing to validate our hypotheses. We do as many iterations as we need, followed by more testing, depending on the complexity and time we have. Once we are happy with the result, we move onto visual design (probably a few more iterations there) and finally development.

This is, of course, a quick and simplified overview of the UX process.

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