Embrace a “data aware” approach to designing great UX
Data may seem like a trendy currency of the day, but we’ve always used data to inform design.
Data. This short word has captured the imagination of the media. Everyday another news story breaks that discusses the power of “big data,” discussing the value of data for business, data for adaptive technology experiences, data and marketing—it’s clear that data is a very hot topic and the currency of the day.
The power of digital interfaces
It might feel like using data is big news now, but the truth is that we’ve been using data for a long time in the Internet business. For the past 20 years, we’ve been moving and replicating more and more experiences that we used to have in the physical world into the digital world. Sharing photos, having conversations, duties that we used to perform in our daily work have all become digital. We could probably have a separate discussion as to how much the migration from the physical “real” world to the digital world has benefitted or been detrimental to our society, but you can’t deny that it’s happening and only continues to accelerate at a breakneck pace.
Let’s take a look at what it means for these experiences to be moving from the physical to the digital. Not too long ago, the primary way you shared photos with someone was that you would have to have used your camera to take a photo at an event. When your film roll was done, you’d take that film to the local store where you would drop it off for processing. A few days or a week later you would need to pick up your developed photos and that would be the first time you’d be able to evaluate how well the photos you took many days prior actually turned out. Then, maybe when someone was at your house, you’d pull out those photos and narrate what each photo was about. If you were going to really share those photos with someone else, you’d maybe order duplicates and then put them in an envelope to mail to them—and a few days later, your friend would get your photos as well. If you were working at a company like Kodak that had a vested interest in getting people to use your film, processing paper or cameras, then there are so many steps and parts of the experience that we just described that are completely out of your control. You also have almost no way to collect insight into your customer’s behaviors and actions along the process.
Now, let’s take the same example of sharing a photo in the digital world. Your user will take out their phone and take a photo. They may open up Instagram, apply some filters to the photo and edit it on the spot before adding a caption and then sharing it. They might also choose to share it on different channels, like Twitter or via email. The entire experience of sharing a photo has been collapsed and condensed into one uninterrupted flow and a single screen, one that you can hold in the palm of your hand. And because all of this is digital, data is continuously being collected along the way. You have access to all kinds of information that you wouldn’t have had before. Location, time spent in each step, which filters were tried but not used, what was written about the photo and to whom the photo was sent. You can also gather consumption data on the photo—how many people viewed it or liked it? Not only are you able to gather that information on just one user, but you can gather it for each and every single user. And that data is both precise as well as dynamic – so, you could get an instant understanding of how your customers’ behaviors and interactions might be changing and evolving with respect to your product and in reaction to changes you make to your product.
All this data can be really powerful, and because digital interfaces have made data collection so easy, we have to make sure we don’t fool ourselves into thinking the collection of good quality data and its interpretation is easier than it actually is. There is a danger that the ease in gathering data also makes it easer to make erroneous conclusions if the data quality is low or the data analysis is flawed.
What does this mean for you as a designer?
User-centered design and activity-data analytics are both focused on establishing effective, rewarding, and repeat-worthy user experiences for the intended and current customer base of the business. We believe data capture, management, and analysis is the best way to bridge between design, user experience, and business relevance. We call this approach a data aware approach to designing great user experiences, rather than the more commonly used “data driven,” as we believe data feeds into a creative design process; it should not drive design. We will say some more about that later in this chapter.
But first, let’s go through some of the assumptions we are making about which kind of designer you are. Given that you’ve picked up this book, we assume you’re probably interested in crafting great user experiences, and have some goals that involve changing or influencing the behavior of the users of your product or service. We assume that you are curious about human behavior with your product and that you are curious about people. We assume you are thinking carefully about who your current—and potentially new—users are. We assume you are already making observations of users and product use, even if only informally. We also assume you are trying to solve different kinds of problems and work out what works best for your users. We assume that, while you may not have a background in statistics or be a data scientist, you are interested in becoming familiar with how you could get involved with the design of experiments to test out your ideas. We believe that experimental methods and the data they yield can help you hone your craft, improve your products, and concretely measure your impact on users—and ultimately on the business. In sum, we believe that becoming familiar with the ways in which experiments are done at scale with millions of users can help you in your design practice. We believe that great design and smart data practices are key to strategic impact in any business.
Data can help to align design with business
In our view, being data aware is also a good foundation for cross-functional collaboration within your business, whether large, medium, or small; it’s an excellent way to have impact upon and create alignment between design and business goals, focusing on the critical part of any business: providing the best possible service to your customers and clients, understanding their goals and concerns, and addressing their frustrations. Being user focused and data aware means you and the people you work with should also be actively contributing to the creation of meaningful business goals that are focused on the greatest asset of any business: your users.
What this means is that we believe designing the user experience should also involve sketching out what data you will need that will help you test your design. Design the data capture, analysis, and questions as part of your design process. Be clear about the data that will best help you measure and articulate the effect of your design on your customers, and then through that to the business.
We believe this will also help you become a better designer, as you will get to test your assumptions and hone your instincts with evidence. As a designer creating an action flow, the actual data that reflect the users’ journey is sometimes not accessible to us. However, it is intuitively obvious that, as you get to know your audience better by looking at what they do and how they react to your designed journey for them, you’ll become more adept at understanding the different kinds of experiences that engage them and that don’t. You’ll also get better at understanding which kinds of things will be more or less impactful on them and will therefore show or not show in the resulting metrics. After all, one of the core reasons to take a data-aware approach to design is to be able to engage in an ongoing conversation with your customers through the data so you can create better experiences for them.
Seeing the data and designing the experiments that answer questions that make sense from a design perspective as well as a business perspective can create alignment with business partners, collaborators, and company leadership about the target audience(s) and the desired behaviors for business growth and maintenance.
In this book, we want to encourage you to inform your design decisions by specific, objective evidence: data. Data comes in many forms, it is collected in a number of different ways, and it should be used to give teams a better understanding of what customers are doing with a product. Using data in our decision-making entails that we reflect on the quality of the data, on what data is right for the decision-making setting—that we critically engage with question relevance (are we asking the right questions?), data appropriateness (does it answer our questions?) and data quality (is the data reliable? Did we lose something in data collection/curation?). It also requires we ask: would different data and/or a different analysis be more appropriate? Are we doing what is convenient rather than what is right?
Being smart about data in your decision-making has considerable advantages. Having common success metrics within your company can also help designers and the broader product team to align around common goals and to understand what kind of data is the most important to track and follow.