Exploring Marketing Technology

Category: Productivity

  • AI for Marketers: Welcome to Darwinian Hyperscaling

    AI for Marketers: Welcome to Darwinian Hyperscaling

    If AI has made you question your value as a marketer, you’re not imagining things. The tools are getting better fast, and some tasks are disappearing. But here is the good news: marketers who combine AI fluency with human judgment are becoming more valuable, not less.

    I call this Darwinian Hyperscaling: adapting your skills faster than the pace of changes in our marketing environment.

    In practice, that means three moves. Build decisions on strong mental models. Strengthen the social skills that machines cannot replace. Train your attention so you can think clearly when everyone else is reacting.

    Do those three things, and AI becomes your multiplier, not your replacement.

    Gradually, and then suddenly

    Mike Campbell, a character in Earnest Hemingway’s novel The Sun Also Rises, said he went bankrupt two ways: “Gradually, and then suddenly.” That quote aptly describes how we got to our current scary employment climate.

    Enter: Darwinian Hyperscaling. Just as the forces of environmental changes can accelerate evolutionary adaptation, the forces changing how we deliver business value will only reward those who are ready.

    The unifying strategy I recommend is to aggressively morph into a Centaur — pictured above from Greek mythology. In this essay from Cory Doctorow, he describes the Centaur and Reverse Centaur, as follows:

    “In automation theory, a “centaur” is a person who is assisted by a machine. Driving a car makes you a centaur, and so does using autocomplete.

    “A reverse centaur is a machine head on a human body, a person who is serving as a squishy meat appendage for an uncaring machine.”

    When creating and executing marketing strategies, show your employer’s AI models who’s the boss.

    Apply these three lessons to firmly graft your torso onto this powerful business intelligence, instead waking up and finding yourself resembling the rear end of a two-person horse costume!

    Lesson 1: AI models are terrible at knitting mental model lattices. Exploit this and prosper

    Before his death in 2023, Charlie Munger wrote and spoke often about collecting mental models. He freely shared how he used them with his business partner Warren Buffett.

    Mental models are logical frameworks for solving tough problems.

    Without models from multiple disciplines, you will fail in business and in life.

    — Charlie Munger

    Munger famously said, “The first rule is that you can’t really know anything if you just remember isolated facts and try and bang ’em back. If the facts don’t hang together on a latticework of theory, you don’t have them in a usable form … You’ve got to hang experience on a latticework of models in your head.”

    Case Study: The “Follow The Incentives” Mental Model

    One of Munger’s most repeated quotes also happens to be a powerful mental model. It’s one that I applied to solve a tough problem last year with the help of AI — to great success. He said, “Show me the incentive and I will show you the outcome.”

    This case study and the lesson it teaches follows a standard Problem – Complication – Solution format:

    Problem: I was asked to identify what challenges were keeping marketers — those in a specific business category — up at night. But I knew nothing about that sector, especially since it contained more than a dozen sub-sectors, each with their own unique marketing pain points. Additionally, my assignment was to match my agency’s offerings to whichever pain points were relevant for that sub-sector. This would take months of research … Before AI!

    Complication: A simple prompt, such as an expansion of “List sub-sector X’s marketing challenges and how we could solve them,” is practically an invitation to hallucinate. How do you trust the results?

    Solution: Crowdsource, in an anonymous way, the people with the most to lose if they do not intimately understand their audience’s marketing challenges. In other words, follow the incentives and learn from their findings. 

    As I was thinking about who has skin in the game in identifying pain points, I realized the following:

    • Every sub-sector has at least two professional conferences catering to its unique marketing needs. Many sub-sectors have four or more conferences. That’s a competitive environment — especially when budgets for attending conferences are shrinking.
    • If one of them programmed their conference break-out sessions in a way that attendees found unhelpful, they would go out of business. (Again, Darwinism at work!) Now that’s an incentive to get your programming right!

    I created an AI Agent that would poll each conference’s website, and capture its break-out session titles and descriptions. The Agent could then easily match the relevant ones to my employer’s offerings.

    The carefully researched break-out sessions were proxies for the marketing pain points I was seeking! 

    It worked beautifully.

    I was even able to confirm, talking to colleagues who knew sample industries intimately, that the pain points indeed rang true.

    … All this research and matching, accomplished within an hour or less, for each major business category.

    The takeaway: Only automate where an AI model cannot fail you. The workflow behind the Agent should be based on one or more mental models you employ to the task. Be the Centaur.

    (By the way, don’t ask me to share the actual output. That is the property of my employer at the time. But the methodology? That’s as open source as Munger’s freely-shared wisdom.)

    Action: Make a study of mental models

    You cannot go wrong by starting with The Great Mental Models.

    Six years ago when Farnam Street Publishing announced it was producing this volume, I eagerly pre-ordered it. It did not disappoint. 

    Lesson 2: Improve your social skills

    In 2017, a working paper called The Growing Importance of Social Skills In The Labor Market, concluded that those workplace skills are far more important in this century than in the 1980s and ‘90s. That finding may seem counter-intuitive to you, especially if you are old enough to have worked in teams at that time, as I have. Its findings, controlling for education, demographics, and region, include the following:

    • Workers with higher social skills enable their teams to specialize more efficiently, generating larger productivity gains
    • Social and cognitive skills (being productive across many workplace tasks) are complements: The wage premium for social skills is higher for workers who are also cognitively skilled

    If you wonder how the growth of AI since the paper’s publication has changed the dynamics, I have news for you. Yes, AI has made your ability to do more workplace tasks (what the paper calls cognitive skills), but these new cognitive skills must be paired with the cohesion you encourage within your teams by demonstrating excellent social skills. 

    Last year in my personal blog I posted about how AI has reshuffled the recipe for career success, citing Professor Scott Galloway. He listed his 3 human skills that make you irreplaceable in an AI world. The third of those skills?

    Connection.

    I’ll quote heavily from Professor Galloway below, since he provides plenty of specifics [all emphasis is his]:

    “AI can summarize, analyze, and even write with fluency. What it can’t do is care. It doesn’t build trust, show emotional investment, or make someone say “I want that person in the room.”

    “That’s why, in an age optimized for competence, connection is the real premium.

    “Connectivity means showing up with warmth, curiosity, and follow-through. It’s being the person who brings the group together, who makes others feel smarter when they work with you, or more confident because you’re on the project. When others see that your heart’s in it, they trust you’ll go the extra mile, pay attention to the crucial details, and take personal responsibility. That trust is hard to earn and impossible to automate.”

    Action: Consider finding a coach 

    If the person described above does not align with what people think of you, find out how you can move closer to that professional leadership style.

    For inspiration, I strongly recommend Brené Brown’s latest book, Strong Ground: The Lessons of Daring Leadership, the Tenacity of Paradox, and the Wisdom of the Human Spirit. This was my introduction to Ms. Brown and I’m now a superfan!

    Lesson #3: Practice mindfulness meditation

    I’ll bet you weren’t expecting that one! 

    I may be biased, because I started meditating in my 20s, and when I lived in Milwaukee I was an active member (and OG webmaster!) of the Mindfulness Center of Milwaukee. But it turns out mindfulness is the only reliable antidote to AI-induced cognitive decline, a malady described by two Wharton scholars: Thinking—Fast, Slow, and Artificial: How AI is Reshaping Human Reasoning and the Rise of Cognitive Surrender.

    To be clear, their paper described the problem, not the solution. It was cognitive neuroscientist Dr. Sahar Yousef who posits mindfulness as the remedy. At last month’s SXSW conference, she and Section CEO Greg Shove shared research on AI’s cognitive effects on university students.

    I was surprised / not surprised to learn from them that “Mindfulness is the only cognitive protector. Of all the traits measured, only one showed a protective effect against both cognitive dependence and AI companionship reliance: the ability to be fully engaged in the present.”

    Other academics would agree. In Yuval Noah Harari’s 21 Lessons for the 21st Century, each of the first twenty chapters describes a different challenge facing us. 

    I won’t lie. Reading it was a rough ride. I recognized each of the many challenges he described in detail, either facing us today or swiftly approaching. 

    Reading each progressive chapter, I felt like Hemingway’s Mike Campbell, realizing during a meeting with his accountant that he would soon be very, very insolvent. I wondered: What solace could Harari leave me with? How was he going to help me handle the onslaught, including that of machines thinking for us, making us gradually unfit to reason for ourselves? 

    The title of his final, twenty-first, chapter: 

    Meditation.

    Action: Learn more about mindfulness

    I started my own pursuit of meditation with Jon Kabat-Zinn’s Full Catastrophe Living. It still holds up!

    He is professor emeritus of medicine at the University of Massachusetts Medical School, where he was founding executive director of the Center for Mindfulness in Medicine, Health Care, and Society.

    I read the book shortly after it came out, to cope with chronic pain and the depression it caused. He taught me that meditation, removed from Eastern dogma, could do truly miraculous things to our minds. 

    That includes thinking clearly and strategically in stressful business situations. 

    The introduction of the book explains the meaning behind its title (hint: it’s from a classic musical). I think you’ll agree, we need all the skills we can find to face and overcome today’s occupational and societal “catastrophes.”

  • The Intelligent Enterprise: A Book Review

    The Intelligent Enterprise: A Book Review

    I’ve been blogging here for nearly 20 years (don’t go digging — I’ve learned a lot about writing and MarTech since my tech consulting infancy), yet I’ve never before posted a book review. And with this precedent comes a major disclaimer: Vincent Yates and Jason Goth, the authors, are leaders within my employer, the global consultancy Credera. So this could smell of log rolling, or worse. But I’ve always posted what I sincerely thought at the time. Conversely, I’m not stupid. If they had conceived a truly ugly baby I may be whispering that opinion to my colleagues, but certainly not posting it here. What follows are the objective reasons you should buy and read this book. It’s both excellent and timely.

    Enterprise leaders are hungry for information on how they can adopt artificial intelligence (AI). They are also, if they’ve earned their positions in the C-suite, allergic to glowing citations of easy success. I’ve read lesser business books that suffer from something called survivorship bias — the tendency to elevate success stories while diminishing the more frequent failures. David Ogilvy put it well when he talked about the need for perseverance, but especially also caution, when running a business. He was reported to have said, “The road to success is dotted with many tempting parking spaces—and strewn with the bodies of pioneers.”

    The authors address this head-on, by describing attempts at investing in AI that failed to take into account all the elements needed for success. One example: I was thrilled to see a section about the need to incorporate design thinking. Nothing kills a new technology more surely than workers who are overlooked in its design and roll-out, who then quietly circumvent or sabotage that investment.

    I also found it refreshing that they mentioned Gartner’s hype cycle, where inflated expectations by an enterprise inevitably lead to a trough of disillusionment. 

    Practical Advice for Avoiding Regret

    I should mention, since I focus on MarTech on this blog site, that the most successful implementations of AI aren’t related to marketing at all, unless you count customer service in that category. In my own experience, and within the pages of the book, it’s primarily the many back office processes that AI can profitably automate. These aren’t necessarily the most sexy applications. But they tend to make the greatest impact on an enterprise’s bottom line. 

    Speaking of the bottom line, I loved the list of the many often unanticipated costs of owning and operating an AI solution. Headlines everywhere talk about the easy path to positive ROI (see above: survivorship bias), but data hygiene, ongoing model improvements and smart governance — to name just three — come with ongoing costs that need to be considered up front. 

    AI is not set-and-forget.

    Speaking of governance, I loved seeing the section on AI safety. The book talks about how AI is basically “a brain in a jar” (ick!), but with this power comes risks of unintended consequences. Guardrails are essential. I recently wrote in my personal blog how important this is overall, especially at a nation state level.

    I need to also call out the clarity of the writing. This book excels at bringing a blindingly complicated technology within the grasp of the enterprise leader. It was an actual pleasure to read.

    One Small Quibble

    It’s a truly small knock on the book, but the quote that begins it, one in praise of learning from the wisdom of others via books — ostensibly by Socrates — is most certainly a fabrication, like the many howlers attributed to Albert Einstein or Ghandi. A quick search for the origin of the quote using Copilot (thank you, AI) indicated there is zero evidence of this sentiment in the writings of Plato, Xenophon, or other contemporaries of his. What’s more, although he certainly valued learning from others, he preferred the Socratic method (speaking of log rolling!). 

    In fact, Plato wrote that Socrates thought writing things down instead of memorizing them led to a lazy or weakened mind, particularly in terms of memory and genuine understanding. As a relatively new technology, he was suspicious of writing.

    “Employ your time in improving yourself by other men’s writings, so that you shall come easily by what others have labored hard for.” — Almost certainly not Socrates

    Like I said, a small quibble. As a leader, you will “improve yourself greatly” by reading it and taking heed of its advice. Unlike that fallacious quote, The Intelligent Enterprise is the opposite of AI slop.

  • Why I love Adobe’s Content Supply Chain solution (and you should too!)

    Why I love Adobe’s Content Supply Chain solution (and you should too!)

    I’ve loved Adobe Workfront for many years, and even posted here four years ago with this news: Adobe to buy Workfront: A big win for marketing throughput. As a primarily customer data wonk, you might be surprised that I’ve fawned over this workflow tool. But data is data. And these two experiences from early in my career helped me understand the value of democratized data to accelerate sluggish production processes:

    1. While working at my very first marketing firm I used a then-new technique to boost the pace of print production by 20%
    2. A short time later I helped my brother, who founded and led a precision machined parts factory, to completely rethink how products are produced, greatly improving revenue and profits.

    The technique that unlocked these improvements was the same for both. It was a workflow optimization approach called the Theory of Constraints, as described in the worldwide best selling business book, The Goal.

    My older brother, Brian, was a brilliant business operator. He has sadly passed away, but not before telling me that The Goal was “The best business book I’ve ever read.” That’s extremely high praise, if you talk to anyone who worked with him.

    Join Me At Adobe Summit

    In keeping with a theme I started with my last post here, Going to Adobe Summit? Here’s one reason I’d love to connect with you there, I’ve co-written an eBook that resurrects the thinking of a business leader whose lessons may be overlooked by modern marketers. That would be a shame.

    In this eBook, I examine the innovations of The Goal‘s author, Eliyahu M. Goldratt, through the lens of solving the vexing challenge of Content Supply Chain. It turns out the data coming out of Adobe Workfront is perfect for using the Theory of Constraints to identify and fix workflow bottlenecks.

    I invite you to see for yourself. You can download this free eBook here.

    And if you’re attending Adobe Summit, seek me out. I’d love to talk about this important digital marketing tool and the concept that can turbocharge it.

  • Adobe to buy Workfront: A big win for marketing throughput

    Adobe to buy Workfront: A big win for marketing throughput

    Workflow management is often an afterthought. That’s a big mistake, especially when it comes to marketing execution. The late Eliyahu M. Goldratt told us this in his books from nearly forty years ago, starting with The Goal, and especially its follow-up ten years later, It’s Not Luck.

    Those books are ancient business history, yet this proven competitive advantage continues to go ignored by most enterprises. I know. I’ve seen it in my many years of digital marketing consulting. But things are starting to change. What’s more, I consider Adobe’s announced plan to purchase Workfront as a sign that this progress is accelerating.

    Let’s face it: Workflow management isn’t sexy. But following the adage of You can’t manage what you don’t measure, the pace of executing your marketing strategy can stall if you aren’t identifying and fixing constraints in the pipeline. That’s where Workfront shines. But first, a little more about how we got here.

    The Theory of Constraints

    Goldratt initially created his Theory of Constraints (TOC) because Western manufacturers were quickly losing ground to the Japanese makers of cars, televisions, and much else. At the time he maintained that improved throughput was a secret weapon for the modern manufacturer … and marketer. (He looked at several categories of workflow in his books, and devoted It’s Not Luck to marketing effectiveness.)

    Speed-to-market — what Goldratt called throughput — reduces inventories, stabilizes costs, and helps a brand prevail over less-nimble competitors. Out of Goldratt’s work (along with others of his ilk) came entire categories of TOC-driven productivity, most notably modern logistics.

    Let’s look at a common marketing example:

    It’s a competitive no-no to take many weeks between conceiving a campaign and its execution, using a tool like (in this example) Adobe Campaign. But constructing campaigns in Campaign is hard work! There are so many skilled hands that must touch the work product, in sequence or in parallel — doing everything from copy writing and photography to graphic design, data science, coding and quality assurance (QA) testing.

    Non-waterfall approaches to the work, particularly Agile, are, to use a phrase that is the title of another of Goldratt’s books: Necessary but Not Sufficient. Agile in this context is no panacea.

    Achieving Spreadsheet and Email Escape Velocity

    In order to move the work efficiently, you need to get everyone out of the tyranny of email threads and shared Excel spreadsheets. Managing projects of this complexity must be handled by a platform, with automated hand-offs and reporting.

    I can hear some of you now: “We’re good. We have Jira to do that!” or “We have [the Microsoft Jira clone] Azure DevOps [ADO].”

    Yeah, no.

    Marketing involves more than technologists. It demands creatives, plus many layers of stakeholders. These folks haven’t the patience to learn the language and interconnections of those development and bug-fixing tools.

    Workfront is the industry leader in providing a marketer-friendly solution. I’ve seen it in action. It can track campaigns, A/B tests, tagging, insight generation and much more. It does something else that would have warmed Mr. Goldratt’s heart.

    Finding and Fixing Bottlenecks

    You’ll recall that the “C” in TOC stands for constraints. And a constraint is just a fancy word for a workflow bottleneck. These are the slowest stages in the path leading to a successfully delivered project. Typically, Goldratt observed, you can only see one of them at a time. That’s because if you observe work piling up at a particular step, the system upstream slows, making other, upstream bottlenecks undetectable.

    Thus the 5-step cycle that he described in his books, and is shown at the top of this post.

    Another clarification: By “exploiting” constraints, Goldratt had simply meant opening up the log jam. In manufacturing, (and frankly, also in marketing project management), that can mean things like this:

    • Doing as much QA as possible before the constraint
    • Hiring a second resource
    • Adding a second or faster machine used to do the work

    Once you’ve cleared one logjam, it’s guaranteed that will expose another. That’s just life in project workflow management.

    You can do none of the work I describe unless you have the reporting necessary to see the bottlenecks. And if you’re using manual reporting today, just realize that won’t scale as capacity increases.

    These productivity reports are where Workfront really shines. Marketing projects managed this way move through the system more smoothly and create an environment conducive to other improvements, e.g., unanticipated process innovations.

    You cannot manage what you do not measure, indeed.

    Managing Inputs and Outputs from Adobe Platforms

    All of this is why I’m so pleased that a major digital experience company has decided to buy Workfront. Arguably every platform in the Adobe Experience Cloud has inputs and outputs that must be managed by many types of roles. By eventually providing a workflow management tool to knit together this work, the value of Adobe’s cloud will grow.

    As a process guy, I’m loving this development. But let me know what you think. I’ve turned off comments, but I have an extremely “googleable” name. You can find me on social media and let me know your thoughts.

  • MindJet adds Gantt charting to its mind mapping software

    I’ve been an advocate of mind mapping for years, and have recently talked about my preference for using MindJet.com’s mind mapping product, MindManager. I even demonstrated its power, while leading a discussion about rich digital media, at an UnGeeked Conference in May. I find the system a huge time-saver. Now MindJet has upgraded their software to include a valuable way to share project roles, deadlines and milestones: Gantt charting.

    Since the 1990s I’ve appreciated the ability of Gantt charts to bring teams to agreement on project roles and deadlines. It’s an equally valuable way to show clients how any delay in supplying crucial content or sign-offs can push web launch dates out. Below is an example:

    The detail is intentionally too small to make out, because I’ve used live client details. From left to right, this chart shows the task name, and start date, end date, and duration in days. After that is the chart itself. Milestones are the green bars. Every task within that milestone must be completed before the milestone is reached and the next milestone and task set begins.

    My web development team would “own” some of the tasks, and the client would own others. At a glance, everyone knew what they needed to do and when. They also knew the effects on the project as a whole if they missed their deadline. Great stuff.

    Now, the just-released MindManager 9 includes this feature. Below shows a simple Gantt chart, from MindJet’s introductory video:

    Needless to say I’m eager to give the Gantt charting a test spin. What’s especially exciting is it takes the collaborative strengths of building a mind map as a team and fairly quickly converts that shared map into a full-blown project plan.