Data for Design

Using Data As Part Of A User Centred Design Process

The Definition. User-centered design (UCD) is a framework of processes (not restricted to interfaces or technologies) in which the needs, wants, and limitations of end users of a product, service or process are given extensive attention at each stage of the design process.

When I started out as a web designer, I had no real understanding of what user experience design (UXD) meant, or even that it existed as a term. I was led into the industry through my passion for both e-commerce and graphic design.

As an entry level designer I realised I spent all my time diving into analytics to discover what I could about users of the site. I was really trying my hardest to undertake UX design without even realising I was doing so.

As my career has progressed I managed to move a lot closer to UX design and begun to undertake user testing as part of my design process. This is where my fascination with UXD & UCD really began and where I started to understand that analytics data can only be fully understood when the user provides context and true qualitative insight.

In this article I want to share a few things I’ve learnt along the way into how to use both the web analytics and user testing data throughout the design process and as part of continuous learning and improvement cycle to create the best possible products for your customers.

The Quantitative Insight

Quantitative insight can be gained by using analytics in the form of statistics, figures and reports to collate trends and patterns on user behaviour. Data leaves assumptions behind and provides us with facts.

In God We Trust, all Others Must Bring Data. W. Edwards Deming

Data is insightful. All data however, needs context and needs to be validated with qualitative insight, from your users. You can collect all the data in the world, but in the wrong hands, assumptions will be made and you won’t know what to do with it.

Data is like garbage. You’d better know what you are going to do with it before you collect it. Mark Twain

Diving into the analytics and quantitative research can often be a can of worms and will more than likely throw up more questions than you get answers. It’s important to try to stick to the specifics and try to focus on certain areas that are of the most significance.

The data you hold will then be more actionable and you will be able to use your findings to make decisions and to influence design.

Facts Do Not Cease To Exist Because They Are Ignored. Aldous Huxley

You cannot ignore data. Data rings true, it can help you get your point across. It can prove right or wrong and can enable you to be able to act upon your findings.

With the above said, it’s important to communicate data in a simple and understandable way to effectively to help get your point across to different areas of the business and senior stakeholders. When doing so however, the importance of backing up this qualitative insight with input from users must be stressed, the what must be framed with the why.

It’s important to balance between the quantitative data you have collected and use qualitative data through user centric research to not only validate your findings but to also either reinforce them or prove them wrong.

The Qualitative Insight

Qualitative insight is the best way to creating user centric designs and can be gained through many varying methods of data capture. There really is no substitute for one on one time with your users, however user testing doesn’t need to be so costly of time, money or resource. Insight can be gained through remote, online user testing, gaining voice of customer insight through surveys and questionnaires and so on.

You Are Not Your User And You Cannot Think Like A User Unless You’re Meeting Users Regularly. Leisa Reichelt

Having been involved in many user testing sessions both in-person and remote I have never once failed to be completely surprised by something that is said or done. Users will always be completely irrational and highlight problems, it’s all part of the test and learn cycle.

No matter how much user testing you do, you will never fail to be surprised, however you will also never be able to answer every single question or cater for all users. It’s important to stick to what’s most important for you, whether that be designing for personas or answering specific questions.

Not Everything That Can Be Counted Counts, And Not Everything That Counts Can Be Counted. Albert Einstein

Qualitative user research techniques provide invaluable insight that go far beyond the analytics. It’s important to test and validate at every stage of the design process. Then to continue to iterate and re-evaluate once a product has been shipped. Your first solution will almost certainly not be your final solution.

When People Talk, Listen Completely. Ernest Hemingway

One of the best pieces of advice I’ve ever heard used in the context of conducting user research is the above quote. No matter how proud or attached you are to a design, forget it, it’s useless unless you listen to the voice of the customer. Listen to their feedback and understand it to be able to shape your design progressively.

In Conclusion…

I’ve only scratched the surface here, although hopefully that has shared some insight. Using data can highlight the importance of key issues and can provide key insights. You can use it to influence and shape your designs. Though you must always ensure you are testing and validating with your users. Although you will never be able to design to suit the needs of every user, you should use personas and key demographics to help you target your designs. Once your product is live you must implement data and user research as part of a continuous test and learn cycle to keep improving and learning about your product.


Data for Design was originally published in uxdesign.cc – User Experience Design on Medium, where people are continuing the conversation by highlighting and responding to this story.

from uxdesign.cc – User Experience Design – Medium https://uxdesign.cc/data-for-design-f33fd7419cc8?source=rss—-138adf9c44c—4

Designing Charts — Principles Every Designer Should Know


Designing Charts — Principles Every Designer Should Know

Let’s talk about charts. Any designer who has worked on a project that requires some kind of data visualization knows that it can be an extremely difficult (and rewarding) design challenge.

I’ve been designing complex, data-heavy web and mobile apps for the past 15 years so I work with charts on a daily basis (see what I mean on Dribbble). Therefore, I want to share some of the design principles I use to build aesthetically pleasing and functional charts that users love.


Use a familiar chart type

As a designer it can be a fun exercise to experiment with unique and strange chart types, such as a Streamgraph, but users shouldn’t have to learn how to read the chart you just invented. In most cases you should use one of the more common charts: area, bar/column, line, or pie/donut.


Add no more than 5 slices to a pie chart

As a general rule of thumb, if you really need to use a pie chart, try to keep the slices at five or less. The more slices in the pie chart, the more difficult it’s going to be to show the user a meaningful story. You’ll end up having to come up with goofy solutions to show the labels and make hover interactions work. Honestly, it’s usually easier just to avoid it altogether by using a different chart type.


Order the data series

Unless you’re working with dates, you can greatly improve the readability of the chart by sorting the series either ascending or descending. This applies mainly to bar/column charts.


Avoid 3D charts

3D charts serve absolutely no practical purpose (unless you’re in VR maybe) — they don’t even look good.


Don’t use randomly generated colors

Some charting frameworks will randomly generate data series colors. These algorithms rarely assign colors that both fit with the overall color scheme and provide enough visual distinction between data series. It’s best to come up with your own color scheme. Make sure you have enough colors for all the data series that could potentially be on the chart.


Trend lines are usually a distraction

Trend lines always seem like a great addition to a chart, but the truth is that they rarely provide anything the user can’t already see with the existing plotted data. If you decide to add a trend line, at the very least allow the user to toggle it off.


Don’t depend on tooltips

Think of tooltips as providing supplemental or expanded information. In other words, a tooltip shouldn’t be the only way a user can see the plotted value.


Don’t include a legend when it’s not needed

When you only have one data series, rather than adding a legend that takes up space, simply use the chart title to indicate the data that’s plotted.


Only use grid lines when it’s helpful

Grid lines can be helpful in guiding the user’s eyes from an axis label to the data point. However, grid lines usually aren’t necessary on simpler charts. When you do use grid lines, it’s important to decide if you need them on both the x-axis and the y-axis. Many times you only need it on one or the other.


Use real data in your chart mock ups

Designers have a tendency to create the most beautiful version of a chart possible without any regard to the real data that it needs to handle when it’s actually implemented.

This can cause endless headaches for the developers trying to build this thing you designed, and even more importantly, you haven’t even verified that the chart design will be practical in a real life situation.

The best solution is to create two versions of the design. The first version shows the chart in a state where the data is perfect, (i.e., optimized for purely aesthetic purposes). This design can be used for your portfolio and to present to potential clients. In the second version, use data that the chart is likely to display when it’s actually implemented. This is the design you can hand off to developers.

This looks nice, but it’s not real data. Source: https://dribbble.com/shots/3203320-Map-Dashboard

Lastly, there are always exceptions

As a designer it’s your responsibility to use your best judgement and creativity when designing around data. However, data can be complex and creating a meaningful story around that data isn’t always cookie cutter.

You might find that the data you’re working with doesn’t play well with some of the principles outlined above — no problem, it’s ok to break the rules sometimes. The important thing is that you test your designs against real world situations.


You can find my charts on Dribbble and Twitter.

And don’t forget the heart if you found the article helpful :)


Ryan Bales is the Founder & Creative Director at Bync.com. He has over 15 years of design experience with an emphasis on data visualization and designing for data heavy SaaS apps.