“I’m not a technical person” is perhaps my least favorite excuse from clients. Working in web development, and being the person who is in charge of introducing my clients to new technologies and strategies, I hear this line almost daily.
However, I can not like something but still understand it. I know what people are actually saying when they tell me they are “not a technical person.” They mean: I won’t understand this.
My clients are responding not to the message, but the messenger. They mean: this isn’t made for me. This format does not have me in mind. It’s for someone else. Give me something personalized, and I’ll listen.
This past month I attended Evergage’s 2017 Personalization Summit, which was all about Machine Learning. During the event, I found myself thinking about the “I’m not a technical person” excuse and what it says about how web visitors perceive digital ecosystems. People select experiences that are personalized to their needs. Self-selection is an act of efficiency in a world overflowing with content, variety and competition. Categorization is the means by which most people find what they’re looking for quickly. If you know who you are as a consumer, you’re more likely to find the product that has you in mind.
The inverse of this is: if you don’t know how to describe what you’re looking for, you probably won’t find it. That’s a lot to leave up to a visitor. A better version of this process is a site that doesn’t ask a person to laboriously self-describe themselves over and over again with each visit, and instead simply knows what to do. In other words, the site personalizes the experience to each person.
“Personalization is the direction the internet is heading,” writes Karl Wirth in his new book (of which attendees received advanced copies at the Summit), One-to-One Personalization in the Age of Machine Learning. I agree. Expecting someone to sift through your site, and then doing nothing with the data you collect, seems irresponsible. Instead, Evergage puts forth a world in which a site (or any other marketing channel) can accurately personalize itself to fit a person’s needs based on their behavior, in real time.
This is cool. This makes sense. When I explain how Evergage works to a client, I’m never met with “I’m not a technical person,” because marketers dream about this sort of interactive, personalized experience.
Attending the Summit gave me a lot of ideas about how I can better help my clients provide those personalized experiences. At a morning breakout session “Designing Personalized Experiences for Your Brand,” I got a bit distracted and outlined a campaign for one client that would provide messages with a personalized call to action to certain users, funneling towards a lead generation form. At my next session, “Unveiling the Keys to Great Segmentation,” I refined this campaign to a segment based on a user’s visit frequency over a set time, and to match against the global goals of the site. At a session later in the afternoon, “Testing and Attribution Analysis,” I put together a framework for testing against the goals I’d designed my campaigns around.
I spent my entire day like this, flitting between paying attention and jotting down ideas for my accounts. Along with some new strategies, I left the summit with a much better vocabulary for talking about machine learning and personalization, which was my main reason for attending. It was a major success for me, and one that I hope to channel to my clients.
And, all that aside, there was a magician! A real life, actually magical magician. I can’t tell you how he did what he did, though. I’m not a magical person, after all.
Ryan La Sala is the Digital Account Manager with OHO Interactive, an Evergage partner and digital agency with a focus on higher education, content strategy, and user research. As part of the Client Services team, Ryan works with his clients to optimize their digital ecosystems and elevate their online strategies.
[Editor’s note: General availability of the book, One-to-One Personalization in the Age of Machine Learning, coming soon!]