Humans of New York: Stories by Brandon Stanton, 2015
A bit of a departure from the data and design research books on this list, but nonetheless a great read! Stanton goes into the back stories of the best posts from his wildly popular Tumblr of photos of ordinary people. The qualitative researcher in me loves these anecdotes about what gets people out of bed in the morning and makes them tick.
Just Enough Research by Erika Hall, 2013
Hall, one of the founders of Mule Design, takes on design research, which I find interesting for its notable differences from and similarity to market research. She’s just so smart – I recommend following her on Twitter and if you’re in the Bay Area, don’t miss her April 29 Workshop Research Together.
The Signal and the Noise by Nate Silver, 2012
You may remember Silver from his groundbreaking polling analysis during the 2008 presidential election. In this book, he talks about how we can make better and more accurate predictions based on the firehose of data that is now available to us. I’m interested in the pivots that Silver and his colleagues at Fivethirtyeight.com need to make in their methods during this hotly contested election cycle, when traditional polling has become less and less reliable.
The Long Tail by Chris Anderson, 2006
A former editor of Wired Magazine, Anderson makes the case that mass markets for consumer brands and products have fragmented and shifted toward a landscape of small niche brands and markets. Technology has enabled consumers to find bespoke products and brands that suit them better than one-size-fits all mass brands, and that has made for some interesting economic shifts.
Freakonomics by Steven Levitt and Stephen Dubner, 2005
Another classic focused on economics, but with a twist. Levitt and Dubner sifted through the data to delve into questions of race, child rearing, crime, and politics. A standout chapter is the one that traces a dramatic drop in crime in the 90’s with the legalization of abortion, resulting in fewer children born into poverty. A really interesting take on how (sometimes controversial) correlations can be made from quantitative data.
Do you have any book recommendations for me and my team? Let me know in the comments!