Skip to main content


What is your brand's "Fast Car?"

  If you watched the Grammy Awards last Sunday, you saw an audience moved by Tracy Chapman and Luke Combs performing a duet of "Fast Car." Or dial up the YouTube and watch her 1988 performance at Wembley Stadium where the unknown artist was asked to fill time when Stevie Wonder's set was delayed by a technical malfunction, and watch that song quiet a massive and restless crowd. Why? Because "Fast Car" touches the marrow of our universal human experiences and needs. It's an example of the power of truly understanding people, and the risk of not. Recently, pundits and politicians have been scratching their heads, puzzled why people don't agree with the data that shows the strength and resilience of the economy. To me, this is just another example of not seeing the people behind the data (in this case, the daily reality of working-class people and towns that Tracy Chapman wrote about). Empathy is a powerful tool for marketers to better understand people

Can Marketing Save Humanity?

In 2003, the philosopher Nick Bostrom proposed a thought experiment called The Paperclip Maximizer , a provocation designed to show the risks associated with AI that is not in tune with human values. An AI is programmed to maximize the production of paperclips, producing as many as possible, optimizing procurement of all raw materials needed to achieve its goal, over time converting the entire planet into paperclip manufacturing facilities, before identifying and solving the final obstacle standing in its way — humans. Can AI be engineered to integrate fundamental human values in its decisioning, giving weight to our sense of fairness, of right and wrong? But what are these values, and who defines them for the world?   Judeo-Christian or Islamic values? Eastern or Western?   Those of G20 Nations or developing countries?   Generational values?   As AI optimizes trade-offs to achieve its task, how will it know the decisions that are best for society? I believe marketers will soon begin

What Marketers Can Learn from "The Big Short."

The Big Short is more than a story about the 2007 mortgage crisis - it’s a cautionary tale about the peril of not understanding the human context behind data.   Mark Baum, the investor played by Steve Carell, had his team gather first-hand insights to uncover what the raw data was hiding from others. They went out and talked to people on the front lines — the shady mortgage brokers; the compromised ratings agencies; the “nightclub” worker who owned five homes; the father who had dutifully paid his bill yet was about to lose his home — before deciding to short the Collateralized Debt Obligations that would soon turn toxic.  They invested the time to understand the human context — behaviors, motivations, beliefs. What purely data-derived assumptions do we have about customers.   Do we understand how they feel and why they do what they do?   This is the question I’ll be posing to students as I share the Rehumanize platform during my upcoming university lectures at California State-Fuller

Rehumanizing Artificial Intelligence

The news media has been abuzz with hand-wringing reports about how ChatGPT will undermine academic integrity.  However, the Artificial Intelligence genie is out of the bottle. AI is happening. It will scale. Its applications will extend to many aspects of daily life, including education. (Microsoft is banking on this, having just invested $10B in OpenAI, the red-hot AI lab behind ChatGPT.)  Every minute we spend romanticizing how things used to be is time we’re not designing ways to harness change.  We heard similar laments years ago when students started using Google Search instead of the encyclopedia; when parents began tethering their kids with mobile phones; when social media became an addictive currency. Over time, we learned to harness something positive from each – access to knowledge; safety; a generation of creators – while remaining vigilant about their dark sides.  Even before ChatGPT, the quality of writing seems to have been deteriorating for decades, at least within the c

Let's rehumanize marketing!

Every new marketing model seems to move farther from a fundamental truth – there’s a human on the other side of the screen. We can sense this growing chasm in marketing's increasingly de-humanized vocabulary – addressable markets, cohorts, targets, segments; we can sense it in blunt, one-size-fits-all multicultural definitions and generational tags. Despite being awash in data and analytics that tell us what customers did, most companies don’t fully understand why their customers behave the way they do.    A Harvard Business Review Analytical Services study found that just 23% of executives believe their organization understands their customers’ motivations. (Even if this has doubled since 2019 that's still not great.) Customer Experience, or CX, comes closest to embracing a human-centered truth. Yet here we are in 2023 and CX remains siloed in many organizations.  Being human-centered is not about going analog. Far from it! Data and marketing technologies have given us super

Will this be your first recession rodeo?

In a previous article I referenced Mark Twain’s quote, “history doesn’t repeat itself, but it often rhymes.”    If true, then this is a poem about marketing in a recession by reflecting on lessons which I will attempt to freshen... Ok, no more poetry. I recently revisited the WikiBranding articles I wrote during the 2008-2009 meltdown that spotlighted best practices from a range of marketers.   It struck me that  those of us who guided businesses through The Great Recession can  share  lessons we learned with managers for whom this downturn might be their first.  (Bob Barrie, Stuart D’Rozario and I had just co-founded BD’M; learning how to navigate the recession was not a choice!)     Who decides if we’re in a recession?     Spoiler alert:  the consumer decides.   News stories about the economy lead us believe we’re in a recession – the “R-word” is having its moment.     Economists might say otherwise, based on their often used definition of a recession, i.e., two consecutive quarters

We are the supply chain problem.

We can’t go a day without hearing, or sharing our own story, about a seemingly simple purchase that is taking eons to arrive, an impatience that has heightened in a next-day culture. In casual conversations we hear people cite the cause as having something to do with lazy workers, politicians, Russia’s aggression in Ukraine, or myriad other heard-then-repeated explanations. Turns out, we are the problem: Our business models, our disconnected systems, our labor practices, our personal shopping choices. We are the forces straining the system. That’s why this WSJ video is so fascinating . It starts with the sobering truth, that global demand is greater than what supply chains can handle. From there it unpacks the thorny thicket of disconnected problems raging through the system – i.e., through factories, ocean shipping, ports, trucking, and distribution centers – all made worse by rapid changes in DTC business models and the resulting shift in consumer shopping behavior. And, spoiler al

Are EVs in the dial-up phase?

Several comments on my x-country EV roadtrip travelogues questioned whether the growth in the charging network can possibly keep up with increasing EV sales ( a question also posed in this CNBC article ). This is where the lesson from Moore's Law comes in handy: We should expect battery capacity and range to increase exponentially, concurrent with network growth. There was a time when the internet was shiny and new that we connected to it via dial-up. (If you're old enough, you'll undoubtedly remember the noises your modem made and how loooooooong it took to connect!) Back then we had no clue about the next-gen technologies – connectivity accelerants such as Broadband, Bluetooth, WiFi – that would soon emerge and radically change how we'd access the web. The point? It's risky to predict the future based on today's technologies and infrastructure.