Got it. What's Next?
I can tell within about five minutes of talking to someone which type of marketer they are. Not because I’m particularly insightful. Because the pattern has played out the same way across every technology shift I’ve worked through.
There are two types. One adapts. One doesn’t.
Type A built their career on execution. They became the person who knew how to do the thing nobody else could figure out.
Continue readingMany marketing interviews are terrible at predicting job performance.
You ask about their experience. They tell you about campaigns they worked on. You ask behavioral questions. They’ve rehearsed responses since college.
None of it tells you what you actually need to know. Can this person tell good from bad? Do they have judgment?
I’ve started using a different approach. I give them AI-generated work and ask them to fix it.
Before the interview, I use ChatGPT or Claude to create something relevant to the role. An email campaign. A blog post. Product copy. Whatever matches what they’d actually be doing.
I don’t use a perfect prompt. I use a mediocre one. The kind a busy manager might actually write at 4pm on a Friday.
The AI output is usually pretty good. Sometimes it’s 80% there. Sometimes it’s impressively wrong in subtle ways. That’s the point.
In the interview, I hand it to them and say, “I had AI generate this. Take 10 minutes and tell me what you’d change and why.”
Then I shut up and watch.
The responses split into three categories pretty quickly.
Type 1 makes surface-level edits. They fix a typo. Maybe adjust some formatting. They can spot obvious errors but can’t evaluate strategic quality.
Type 2 tears it apart and rebuilds it. They explain what’s missing, what’s off-brand, where the logic breaks down. They can articulate why the tone is wrong for the audience or why the call-to-action won’t work. These are the people you want.
Type 3 is rarer but interesting. They say, “Actually, this is pretty good for [specific use case], but it completely misses the mark for [the actual objective].” They’ve identified a fundamental strategic problem before getting into tactical fixes.
Type 2 and Type 3 are showing you judgment. Type 1 is showing you someone who can follow instructions but can’t think critically.
When I worked with companies navigating social media in the early 2010s, the best interview question wasn’t “what’s your engagement rate?” It was showing them three competitor posts and asking which one they’d model and why.
Same principle here. You’re testing whether they can recognize quality, articulate problems, and think strategically about solutions.
Research from the lending industry proves the point. When humans and AI evaluated information together, default rates dropped to 3.1% MarTech compared to either working alone. But that only works if the human knows how to evaluate what the AI is producing.
“I’d make it more creative.” (Translation: I have opinions but can’t articulate reasoning.)
“I’d run it through Grammarly first.” (Translation: I’m focused on mechanics, not strategy.)
“It’s fine, I’d probably just use it.” (Translation: I can’t evaluate quality or I’m afraid to critique anything.)
“The headline is clickbait-y but the article doesn’t deliver on the promise. I’d either change the headline to match the content or rewrite the intro to fulfill what the headline sets up.”
“This reads like it was written for a general audience, but our buyers are technical. I’d cut the explainer paragraphs and get to the specifications faster.”
“The tone is way too formal for our brand. We sound like a law firm, not a startup. I’d rewrite this entire section to sound more conversational.”
See the difference? They’re not just pointing out problems. They’re explaining the why behind the problem and proposing a fix that connects back to strategy or audience.
This also reveals something important: Are they comfortable saying “this isn’t good enough”? Because in six months, their job will involve telling AI to try again. A lot. If they can’t critique a piece of copy in an interview, they probably won’t manage AI output effectively on the job.
Next time you’re hiring, spend 5 minutes generating something with AI. Hand it to your candidate. Give them 10 minutes.
You’ll learn more than you would from an hour of behavioral questions.
I review a lot of marketing job postings. Most of them look like they were written six years ago.
“Proficient in Adobe Creative Suite.” “Experience with video editing software.” “Knowledge of HTML/CSS a plus.” “Familiarity with marketing automation platforms.”
These aren’t bad skills. They’re just increasingly irrelevant.
It’s like posting a job in 2010 that required “expert knowledge of the Dewey Decimal System” when Google already existed. Sure, librarians still needed to understand information architecture. But the actual skill that mattered had shifted completely.
Continue readingI’ve been doing this long enough to spot the pattern.
In the late 1990s, I worked at Progressive Networks, which changed its name to RealNetworks. We were pioneers and created ways for companies to navigate the shift to video on the internet. Not everyone survived. The ones who did weren’t necessarily the best videographers. They were people who understood what video meant for storytelling and user behavior and how the internet was going ot expand that audience.
Then came mobile in the mid-2000s. iPhone. Android. Suddenly everyone needed an app. I helped clients figure out what that meant for their business. Again, success didn’t go to the best coders. It went to people who understood what a pocket-sized screen changed about how people consumed content.
Social media followed in the early 2010s. Facebook ads. Instagram. Twitter. I saw the same pattern repeat itself. The tool-masters struggled while strategic thinkers adapted to what it meant to let customers suddenly have access to your executives, and the way to broadcast to millions without your PR team being involved.
Now we’re in shift number four: AI.
And honestly? It’s the same movie playing again. Just different special effects.
Continue readingI’d love to know the story why a high value url like Email.com sits unused. Surely some company has the capital to buy the url and redirect it to their own email platform. Gmail? Heck, it seems like just the thing Microsoft would do to boost traffic to Bing. Anyone know the story?
David Bayer, author and creator of “A Changed Mind,” has this simple formula I like:
Desire plus barrier removal equals desired outcome.
In plain English, most of us know what we want: more customers, more sales, more traction. But we forget the “barrier removal” part. And honestly, that’s where most marketing strategies get stuck.
It’s easy to think the next big thing will save the day. A TikTok campaign, a hot new CRM, some influencer deal. These things are cool to talk about at cocktail parties and networking events. (Plus, ad agencies will make you feel really special.) But truthfully, you don’t need another shiny object. You need to fix the stuff that’s already slowing people down.
Continue readingMost product messages fail because they start at the end. They lead with facts before earning the right to be heard. But people need something to grab their attention first.
That’s why I work with something I call the 3-30-3 Rule. It isn’t a formula carved in stone, but a useful guide. The premise is simple:
Continue readingEarly in my career, I was a tactician. Email campaigns, SEO, SEM, building landing pages, hacking together A/B tests. Whatever the job needed, I’d figure it out.
Then I got older. Took on bigger roles. Strategy became my thing. I got an MBA, which basically teaches you how to never do real work again. Just make PowerPoints and use fancy terms like “ubiquitous” and “leveraging synergies.” Just kidding. Kind of.
Then I taught at UW. Strategy-heavy, theory-driven. But not much time for learning how to troubleshoot a broken Meta ad pixel or chase down why TikTok didn’t like the file format you uploaded.
Fast-forward to a recent client gig. A small, scrappy brand with big potential. I figured with AI at my side, I could go back to being a full-stack marketer. The headlines promised that AI was like hiring a 12-person team. All I had to do was show up and prompt. Well, that’s what I thought would happen…
Continue readingTL;DR Version
Twitter used to be a platform for discovery, curiosity, and real conversations. Over time, it shifted, to a space for customer complaints, then into a political battleground, and eventually into something stranger. Today, much of what passes for “debate” is driven by bots, automated replies, and talking points that feel like they were built in a conspiracy theory factory.
Research backs this up. Bots have been responsible for a disproportionate amount of political content for years, up to 30% or more, depending on the topic. The result is a platform where real engagement is harder to find, and actual people seem increasingly absent.
Continue readingResearch in psychology and psychiatry suggests that certain types of images or visual stimuli can help individuals improve focus and reduce distractions. These images often leverage principles of attention regulation, mindfulness, and environmental design. Here are a few scientifically-backed approaches:
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