When we think of analytics, we think of marketing campaigns and funnel optimization. Analytics can seem a little overwhelming, with so many charts and lots of new features. How can we use analytics for design insights?
The best thing about analytics is that they can show us what people do on their own. The worst thing is that analytics don’t tell us much about context, motivations, and intent. Like any kind of data, there are limitations. But that doesn’t mean analytics aren’t useful. Working with analytics is about knowing where to look and learning which questions you can reasonably ask. Read More
This is the first edition of my new column, Data-Informed Design, which will explore the use of data to inform UX design. Data, in many different forms, is changing how we think about ourselves and the world. And, for better or worse, it is definitely changing our experience with technology—from great new mobile apps that we can use to monitor our health to incremental improvements on our favorite Web sites to those annoying ads that follow us everywhere.
In my column, I’ll describe how to use different types and sources of data to create better user experiences and how to achieve some balance—so data isn’t driving decisions. There are three key topics that I’ll cover:
Starting at a high level, I’ll look at why you would want to use data, some misconceptions around data and UX design, and discuss a process for incorporating any kind of data into your decisions.
Then, I’ll move on to considering various data sources such as analytics, A/B tests, social-media sentiment, and various types of quantified data from UX research.
I’ll also describe how to use and analyze data, including metrics and measurement frameworks, as well as presentation tips and visualization tools.
Algorithms drive the stock market, write articles—but not this one—approve loans, and even drive cars. Algorithms are shaping your experience every day. Your Facebook feed, your Spotify playlists, your Amazon recommendations, and more are creating a personalized window into a world that is driven by algorithms. Algorithms and machine learning help Google Maps determine the best route for you. When you ask Siri or Cortana a question, algorithms help shape what you ask and the information you receive as a response.
As experience designers, we rely more on algorithms with every iteration of a Web site or application. As design becomes less about screens and more about augmenting humans with extended capabilities, new ideas, and even, potentially, more emotional awareness, we need algorithms. If we think of experience designers as the creators of the interface between people and technology, it makes sense that we should become more savvy about algorithms. Read More