What the DMV Taught Me About Brand Trust in the Age of Algorithms
After I shifted my residency from Pennsylvania to Virginia, I put off for way too long the job of going to the DMV to change my driver’s license. When I finally went recently, it was just as awful an experience as I expected. While I did lose years off my life, I also came away with new insights about customer experience and brand trust in the age of the algorithm.

Let me set the stage. After explaining my needs (license, registration) to a greeter, I was given a ticket with the the number D72. I then went to sit among 100 or so lost souls watching a ticker go by: A31, T76, F17, H125, B7, A32 C38 … And I watched. And watched. After about an hour it dawned on me that I had not seen one “D” number go by in all that time.
I wandered around seeking an explanation for this strange D-free streak. I saw a poster that said something like, “We have a numbering system that prioritizes the various services with an employee with the right level of experience and training. We find that this is most effective process.”
So in other words, “We have a sort of secret system, and will not really explain it to you, but trust us, it works (for us).”
Rather than provide comfort, this bit of bureaucratic prose only wound me up further: What does my “D” ticket say about me? Where do I stack in the pecking order? What trade-offs are they making that are invisible to me, and that cost me precious time? Should I have gamed the system by doing things one at a time? Can I swipe my neighbor’s faster-moving C ticket? (He’s sleeping on shoulder, so really wouldn’t miss it.)
My conversation with the greeter didn’t help matters. She explained that, yes, D tickets were really slow — harder to deal with. Plus, 11-3 was the lunch hour, and therefore things get really bogged down at that time. I opined that 11-3 was more accurately a lunch four-hours, not a lunch hour, representing nearly half the day. Her silent, reptilian stare chilled my spine and sent me back to my seat.
At four hours and twelve minutes, I gave up and handed the win to the State of Virginia and went home to drink heavily.
This is where the lesson for marketers comes started to dawn on me.
None of us would ever seek to recreate such an experience. But in the age of the algorithm, analytic optimization and the coming era of AI, we run the risk of inadvertently creating similarly mysterious and unsettling experiences — and thereby undermining brand trust.
We’ve already seen some of the consequences of mysterious data working behind the curtain: consumers creeped out by odd friend recommendations on Facebook, re-targeting that haunts us like a stalking ex-, and the famous dad who learned his daughter was pregnant from the checkout clerk.
And the more analytically powerful and automated our environments become, the more potential there is to deliver experiences that make consumers scratch their heads or become uneasy. As we leverage the awesome capability of marketing technology, we’ll need to keep several thoughts in mind:
It’s OK to Keep Some Things Behind the Scenes
There may be operational realities that consumers may not understand or appreciate. If it’s an unavoidable issue, you may not need to give them all the details and risk firing them up — but use all your analytic power to let them know how to best deal with it.
DMV: Don’t tell me about 4-hour lunch zones. Help me find the best times to come, but knowing about your extended dining schedule just makes me mad.
If It Is Visible, Make It Really Intuitive
In situations where you give consumers a peek into the inner workings of the machine, present it in clear, human language. Make it a no-brainer why it’s happening, and illustrate the benefit to the consumer — not to your operations. If a front-line associate can’t explain it without sounding invasive or self-serving, perhaps you should rethink it.
DMV: Don’t just tell me you’ve figured out a weird system of Letter Tickets that works for you: help me understand how it helps us ALL get out of here more quickly.
Set Expectations Upfront
When consumers are engaging with your data-powered environment, let them know what’s coming, how to expect things will work and what your guiding principles are, especially during those first forays into AI. Context provides comfort and pre-explains what might otherwise appear mysterious.
DMV: If I’m a difficult “D”, help me understand why that is and let me know that I should take blood thinners to avoid deep-vein thrombosis while waiting in a chair.
Build — and Maintain — Trust
This is the most foundational issue. As consumers place more of their daily life in our hands, and as marketers hand more execution over to the algorithm, we need to make sure consumers trust us to make the right choices. That will mean living up to expectations, exposing our core values, and doing right by them — even when it’s not first choice for us. A good litmus test here is to ask whether a front-line employee could comfortably explain your analytics-driven action to a customer — without appearing creepy, self-serving or otherwise disturbing. If not, then maybe you shouldn’t do it.
DMV: You haven’t earned the right to have me trust your system without understanding it. Start by understanding me, and the pain I suffer with you, and then set and live up to my expectations to build a foundation of a trusted relationship.
We’re entering uncharted territory with self-driving cars, AI-driven medical diagnoses and spouse-finding apps. In order to make this all work, we’ll need to be thoughtful about how and when we expose the inner workings of this technology and how to help consumers get trust us with it.
And now wish me luck — I’m camping out on the sidewalk like an iPhone groupie so I can be first in the door at the DMV tomorrow with my dreaded scarlett “D.”
Originally posted on Target Marketing Mag
Marketing strategies to help your team get inspired to make bold moves. Join me.
Thanks to the terrific guide
I spent a lot of time to find something like this
I’m glad you found it helpful.
Thanks to the great guide
Glad you liked it!