Affinity mapping (or affinity diagraming, po-TAY-to po-TAH-to) is an exercise that finds underlying themes and trends in research. The map at the center of this exercise is tactile, easy to edit, and oftentimes the largest physical artifact you’ll show a client. Depending on its scope, you could see the map stretch across an entire hallway or room, truly showcasing — if nothing else — an impressive quantity of paper that’s been dedicated towards serving the client. If you decide to make a map at home, you’ll need a wall, sticky note collection and pen, as well as a buddy to keep you from going too crazy moving pieces around by yourself. Here’s a photo of pal, Jason Caragan, demonstrating how it’s done during a recent client project.

Good form, Jason

Wow! That’s a fun and colorful post-it collection, but what does it all mean?

For details on the specific insights THIS affinity map produced, you can follow this link. Jason, Joanna Yuanjing Guo, and I were able to walk away from this map a little wiser because 1) every one of the sticky notes in the photo above contained one of the following:

and 2) we didn’t conclude our mapping after our first round of categorization. Affinity maps require multiple perspectives and patience. We can only call our map successful if we’ve moved its pieces around enough to develop a new picture. In other words, while our first round of groupings might categorize “apples” with “oranges” because they’re both fruits, we need to continue shuffling these pieces until more hidden insights emerge.

If this sounds a little crazy, it’s because it is. I’m certain many of the conspiracy theorists in my inner circle could be experts at affinity mapping. I could easily point to Charlie Kelly’s deranged Pepe Silvia diagram as an affinity map that should have asked for more input from others, but this post will probably be more successful if we analyze a case that actually follows mapping steps correctly. Join me as we head back in time to 1991.

*time travel music*

Step 1: Assemble data and categorize

Silence of the Lambs features a team of FBI agents struggling to uncover the identity of wanted serial killer, Buffalo Bill. Had the FBI hired a UX designer in 1991, they might have identified the subpar affinity map at the core of their investigation as the cause for this struggle. Agent-in-Charge Jack Crawford has excelled at assembling newspaper clips, autopsy reports, and graphic victim photos, but he’s done a poor job moving these pieces around to uncover hidden insights. When we’re first introduced to the FBI’s Behavioral Science Unit, they’ve done little aside from connect the obvious: What do his murders have in common? He skins them. The victims are obese white women. Bodies were found in this area in West Virginia. etc. etc.

Jack Crawford proudly displays his mediocre Buffalo Bill affinity map

Step 2: Ask for input from others and recategorize

Crawford recruits the untested Clarice Starling for the case, and the two of them provide us with exchanges that simulate the benefits of sourcing outside opinions on your affinity map. In the exchange below, Starling offers many insights Crawford probably already knows as a tenured FBI agent, but also includes one he might not.