You can't skip steps in business, or you'll miss key fundamentals and building blocks that later steps require. Generalization requires the opposite. Generalization tends to require parallel thinking and learning - you sample a little of A, a little of B, etc. all the way across the discipline, and the value you add is being able to find connections and parallels among the different samples. Then when you find the areas where great value could be unlocked, you bring in specialists. Serial and parallel thinking don't co-exist well in our brains. We tend to lean towards one side more heavily than the other. For example, you will find very few folks who are talented bakers that are parallel thinkers; baking demands both precision and serialization. Even where you put the yeast - on top or on the bottom of your dry goods - can make a huge difference in a simple loaf of bread. Likewise, you will find very few folks who are talented artists that are serial, paint-by-the-numbers thinkers.
The most skilled painters can visualize the entire image all at once in their heads, and then make it manifest in ways that we can't even see until it's done. Why does this myth of the T-shaped person endure in marketing and small business? The reality is that most of the time, mediocrity is sufficient to get the job done. A press release doesn't need to win a Pulitzer. A banner ad doesn't need to be able to exhibit at the Met. The backing track to your 25-minute sales demo doesn't have to compete against Metallica. Thus, you can be minimally competent in much of the basics of marketing while still being good at something, and be labeled a T-shaped person. That's the hope of hiring managers - someone whose work output in most areas is good enough, and in an area needed most, stellar: The T-shaped person ideal output.
So why am I talking about the demise of the T-shaped marketer? Because AI is eating away at the concept rapidly. The current generation of AI models produce mediocre output. Natural language generation produces some pretty rough first drafts. Today's music generation models are good enough to produce inoffensive backing tracks and elevator music that won't upset anyone. Image generators can spin up thousands of boring ads in one shot. In other words, AI in the current generation is outstanding at mediocre output. Which means that concept of the T-shaped marketer is an endangered one: The end of the T-shaped marketer As the line of mediocre output from AI advances, it will do more and more of the mediocre work, the stuff that everyone can do to some degree. That line advances a little more each year; three years ago, natural language generation was in a sorry state of affairs. You wouldn't even consider using machine outputs for final product. Today, machines can write the same bland press releases humans can, with the same average level of quality. Three years from now? Those machines will probably crank out better blog posts for online businesses than the average person.
So what does this mean for you? No matter where you are in your career, focus on being really, REALLY good at something. Being okay at a whole bunch of things is an eventual recipe for unemployment, because the machines are well on their way to being okay, being good enough, being "I can live with that quality". Machines are still quite a ways off from being able to create masterpieces, create content that evokes real emotion, that conveys a sense of spirit. Find something that you really love doing in marketing, and make it your slam dunk. Good enough isn't good enough any more.
The next round of agency research data trends is focusing on developing insight on the measures that are being adopted by independent agency owners, as well as the expectations of staff returning to the workplace, whether it is on a virtual, part-time or full-time basis. In today’s workforce, a big salary isn’t all it takes to win over employees. Aligning with people’s values is critical, especially among younger generations. Most of the agencies that we speak to are reporting a talent crisis that is limiting their opportunity to take advantage of potential growth in a revitalized economy. Competition for mid-level talent has never been higher, and stories of staff leaving because they were offered double their salary by a competitor of the agency are commonplace. Smart agencies are realizing that they need to develop new strategies to attract and retain the best talent. The agencies that are not prepared to transform their employees working experience and future opportunities risk becoming irrelevant, as they may fail to attract the top talent that create super competitive agencies.
One of the challenges of data-driven strategy is that as data changes, so must our strategy change. If our data indicates that a previous decision is now incorrect, we must change with it - even if we’ve already set a course based on a previous decision. Data-driven strategy also inherently means adopting an agile mindset to go with it; if your data changes and you don’t, then you’re not data-driven. It’d be like your maps app telling you to change the way you’re going because of a crash or a traffic jam and you refusing to make that change, willfully ignoring the data - and paying the consequences for it. Why would our data change so substantially? Most of the time, it’s because the macro environment changes. When the pandemic started and the world locked down, changes in our marketing data were inevitable. Even smaller environmental changes make a big difference. If you started a podcast 10 years ago, you might have been discouraged by the relatively small audience for your "little radio show".
Here’s a real-life example. I’d been doing a daily video show since March 2018, a riff on Marcus Sheridan’s book They Ask, You Answer. My show was simple: You Ask, I Answer. Every weekday, I’d answer a question in 10 minutes or less on my YouTube channel. Each show would also be posted on my blog along with an automated transcript. I looked at my Most Valuable Pages analysis in December of 2020 and saw that things weren’t great. These shows were barely showing up at all in terms of what content converted on my site: November 2020 Most Converting Content Look how many of those URLs aren’t even in 2020, much less in the month I was creating and promoting content. Not great. So I put the show on hiatus in mid-December, and then in early January I announced it wasn’t coming back. I switched back to traditional blogging. It’s been a month and a half. What’s happened? January-February 2021 Most Converting Content Nice. Recent content is showing much more conversion capability; more than half of the top 25 pieces of content were published in the last 30 days. Even more important, the conversion volume is up substantially, almost double what it was in November of 2020.
Now, how will I know if things have changed? By looking at this data regularly and frequently - looking for signs of content conversion slowdown. If recent posts suddenly start dropping out of the top 25, then it’s time to dig in and find out why - and perhaps pivot again. I loved doing a daily video show. It was fun. It was entertaining. It was a way to creatively express myself in a rich media format. And it didn’t convert. The data told me to change, and I believe in being data-driven, so I had to make a change, even though I was emotionally invested in the status quo. And I’ve reaped the rewards for it - more conversions, more recent conversions. I don’t know why what I was doing wasn’t working; all I know is that it wasn’t working, and I had to make a change. Take a look at your own data, especially on pet projects you love and ask if the data supports you continuing as is, making changes, or discontinuing. Then ask yourself if you’re data-driven. If you are, and your data tells you to change, you must change.
The workplace is changing for marketers and sales professionals, it's up to you to evolve and adapt to keep up or stay ahead of the competition.
