I’ve worked with a lot of talented engineers in my 20+ years of designing websites and software. One of the things about analytics that can trip up some engineers: imperfect data, conclusions, and evidence. Analytics tools rarely provide exact answers, but this doesn’t mean there isn’t value to your customers. If your data, analytics, or … Read more
Post-truth. The 2016 word of the year. Yikes for some of us. This got me thinking about UX around data, analytics, and information, and what it means when we present conclusions or advice based on quantitative data. Are those “facts”? If your product generates actionable information for customers, then during your design phase, your team … Read more
I worked on a project with two sociologists from the Future of Music Coalition a couple years ago. They conducted the first large-scale formal survey on musicians’ revenue streams to help answer the question “how do working musicians make a living?” It was a really fantastic project funded in part by the Doris Duke Charitable … Read more
At some point, you probably visited designingforanalytics.com if you’re on my mailing list, and you might have read a cast study about one of my startup clients, Apptopia.com. Apptopia hired me to help them turn a suffering marketplace business into a thriving mobile app intelligence platform based on analytics. If you aren’t familiar with this company, Apptopia … Read more
My teapot, or rather the water heater, helps me make great tea, based on the type of tea I want to drink. It also was a reminder for me about how good design means translating quantitative values into qualitative values people can relate to: As a tea drinker, my goal isn’t to heat the water … Read more
Agile software development is everywhere. You’re probably using some form of it yourself. And, that’s probably good, assuming you’re actually delivering value with agility. These days, I constantly hear about how “shipping working code” sooner trumps everything else. When it comes to designing for analytics though, I don’t always agree. It’s hard to build and ship … Read more
When it comes to analytics products that need to show data to customers, one of the biggest misconceptions I see with clients is the believe that their trove of data is actually information, by default. Your data is not informative until it has been presented–i.e. designed–in a way that customers can inform their future decisions or actions. … Read more
It’s homework time! Let’s talk about NEST (Thermostat) for a minute. In particular, their monthly report. I have a thermostat and hot water radiators in my house (no central air). Each month, the NEST device sends me a report of how I did in terms of energy use etc. How good is this report? Hmmm. … Read more
Ah, fluff. It’s a great word, and it was actually born in its marshmallow form just a mile away in Somerville, MA. There’s even a fluff festival. A few weeks ago, we talked about the various levels of maturity that an analytics-driven product can go through, with the Holy Grail being one that delivers actionable, useful … Read more
This design “no-no” appears almost every time a new client [with a product that displays analytics] asks me to review their UI/UX. More often than not, I’m not provided with any relevant user tasks/usage contexts by which I can do my evaluation, but clients still want my opinion on what could be better, or what they’re … Read more
I hear it all the time on Quora, in real life, and from clients: “What BI tool should we use to visualize our data? Is there a good dashboard template you know of?” When it comes to designing analytics products and dashboards, templates and libraries aren’t necessarily bad, if you have spent the time to … Read more
We’ve all heard about information overload, and the paradox of choice. Don’t you love those thai menus with every type of sauce, noodle, and protein, all written out as separate dishes? “I’ll have item D132 with no water chestnuts….no, I mean the one with chicken on page 12….yeah, that one.” There’s a ton of data … Read more
When I work on products that primarily exist to display analytics information, I find most of them fall into roughly four different levels of design maturity: The best analytics-driven products give actionable recommendations or predictions written in prose telling a user what to do based on data. They are careful about the quantity and design of the … Read more