I was recently working with a group helping define a digital roadmap and growth strategy. My direct contact was a C-level leader in the organization who talked a lot about trust with their team; how important trust was and how it added cohesion to a team.
As someone observing the culture, it was interesting to note, whether discussing software implementation or advertising decision making, that that trust was a one-way street. The leader expected and asked for trust and “loyal” support, delegated responsibility well, but then did not trust the team. So the authority to make decisions wasn’t delegated to the direct reports.
As a newcomer to the environment, but with a fairly long-tail career, it was disturbing to see competent employees trying to guess at appropriate solutions. Not necessarily the solution that their experience would dictate but a solution that would win their boss’s approval. Now, I had had the luck when I was at Nike and just beginning my corporate life to have @LizDolan as a boss. And my experience with Liz as boss was very different.
I still remember Liz saying to a group of new directors, that we had been hired because we got the brand and it was now our responsibility to make the decisions that would grow it. She was clear that she was going to let us succeed (or fail) on our own because that was the only way the company could scale. She did also say that she wouldn’t fire us for making a mistake—unless we made the same mistake twice.
I really took that lesson to heart because she trusted us, I trusted her to be fair and provide the needed direction when asked for that would be both in the best interest of the company and yet would also help us newbies navigate the Nike matrix with relative savvy. When I lead I try and take that standard to heart: hire the best people you can, challenge them, guide them, and trust them. Someone I worked with years ago at a big agency left me a going away note that said in the PS “keep inspiring the f**K out of people”. It was the highlight of my time there but had come because I earned it sticking up for her research and insights all the way up to the CEO.
So when I work with someone that second guesses their team while talking about trust, I see fear, I see lots of vacillation, and I see resources wasted in bright minds floundering. But I don’t see trust being built and I do hear a lack of authenticity in the rallying cry because trust isn’t asked for it must be given.
When strategy ends at the pitch or with the brief to the team, everyone loses. It seems fairly obvious but time and again, I have witnessed teams built where the time for strategists in the workplan ends early in the engagement. This is not just an issue with a traditional waterfall approach but happens also in agile environments as well: the pivot to delivery leaves the strategic framework in the dust of a deck sitting in a folder in Box.
This isn’t just the issue with account management but with strategists themselves. Recently, I was involved in a pitch led by a senior strategist who came away saying the client didn’t want strategy because they were only interested in agile development not two months of research. We then took it as an opportunity to show how strategy could be baked into and evolved holistically into an agile component development AND how it would ladder up to the bigger brand experience.
By componentizing and integrating the strategy with the development rather than as a prerequisite before development, we can lower the risk to the client and pivot based on on-going experience research. Of course, this challenges the “deck is the strategy” approach that many consultancies take but ultimately it provides more assurance the delivered product will have adoption.
In one consultancy engagement in which I was on the client side, I witnessed a very well-known consultancy create a whole “marketing department” from scratch without ever talking to the company’s agency about how they worked with us. More than two years was lost trying to standup the resulting deck before it was tossed in the vertical file and everything went back to how it had been.
Of course, it raises the question of why strategists are more comfortable behind a screen than getting real-world feedback. And as an experience designer, it seems that we are more comfortable designing for the ideal world than the real world. In the real world of human interactions, how humans should react is often not how they actually react. Efficiency doesn’t equal efficacy when human behavior comes into play. It’s a theme I’ve embraced since a failed (in human testing) booking design for a rental-car company.
We had managed to create the entire booking form (no credit card required) into the home page—highly efficient. We took it to testing (several focus groups) and consumers hated it. Why? They told us that they didn’t trust that their requests as entered would be accurately captured AND that the category itself didn’t have a lot of trust so they wanted to see everything repeated back to them before they confirmed the booking.
For the rental-car company, a great and well-meaning strategy failed when it came to human behavior and the layer of category mistrust. Ever sense, as Sam Walton opined, I realized data without talking to the customers was a dangerous game of chance.
While the term “reality distortion field” may have been coined about Steve Jobs’s leadership on the development of the Mac, it’s something that has become more and more popular in business. This is of course odd, since we’re talking more and more about data and insights. However, in the face of all that stuff, to just have a POV and cherry pick the data to support that POV is very, very tempting. Compared with actually trying to understand what the data is hinting at for the future. Make no mistake, the data is not the future it is the past. So sometimes we just guess, which is risky business.
The future is where the Oracle of AI (and its hand servant the algorithm) lives to make sense of all that big data history and take that risk out—or so we hope. But how do we factor in the human behavior factor? That crazy variable that has yet to be quantified or built that pays all that data forward into what will happen in the future. The random associations and behavior that are all too human are hard to write into equations about what do. AI at this point other than to incrementally make what sprang from human behavior and invention better, is not about future innovation or inspiration. It’s beautiful optimization but is it insight? That calls for a true and deep understand of what Spock would call the illogical that makes us human. I’m really curious to see how we cross logic with serendipity so that big data can help us navigate the future not just understand the past.
Just maybe we caught a glimpse of this future with the “reality distortion field” and the Mac. Data and experience would have said “impossible” but the anomaly of inspiration and fear threw that data out the window and created the personal computer.
I remember early in my career, when I became passionate about a point of contention (I don’t know at this point what it was) in a meeting that someone told me keep emotions out of it. And for many years in my ascent of the towers of commerce, I practiced that approach to decision making. Like Michael Corleone in the Godfather, “It’s not personal. It’s strictly business.”
For a marketer, that is the kiss of death I have come to believe. If you are not passionate about what you’re doing and who you’re doing it for, you’ve missed the boat of effective communication. Yes, even in B2B business. “In a recent study performed by the CEB, which examined the impact of personal emotions on B2B purchases, it was found that 71% of buyers who see a personal value in a B2B purchase will end up buying the product or service,” says Daniel Newman in Forbes.
So why then do we keep deferring to non-emotional metrics to “improve” our work? Sure, in a world where bots and algorithms are trading in commoditized categories, efficiency equals efficacy. Not so in categories where there is a human factor deciding between business or consumer purchases that will have career or social impact. Yet often with our b2b customers, the focus is on what it’s easiest for the business to push put: case studies, spec sheets, just-the-facts PR releases without much or any thought to understanding the customer’s emotional and behavioral triggers.
This is where effective interactive storytelling becomes critical: the brand tells the story while the potential customer provides the emotional reaction: call and response at its best and most subtle. With more than 70% (Forrester) of the buyer journey occurring before a customer reaches out to a brand/vendor the marketing that touches them had better understand the customer as a human before it pushes the customer as a bot-like buyer. And that requires some EQ before it requires a spec sheet.
Just had a thought-provoking lunch with Byron Reese and the topic of his new book is AI (releasing in April). I asked him, because they seem to be used interchangeably, is there a difference between AI and algorithms, because I have more of an issue with the latter than the former—in concept at least. My thinking runs to a working definition of AI that involves its ability to create revolutionary new things, not just evolve old things into the next generation things. Would either ever have put bacon on the donut maple log?
Now I’ll admit upfront that I’m a fan of the cautionary tale told in Cathy O’Neill’s “Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy” that we are all too willing to assign authority to equations whose logical structure and assumptions we know very little about. But those are algorithms right, not AI. Or are they?
Byron pointed out that there is no really good definition of AI and that at its most rudimentary instance, algorithms can be considered AI. Well, that brings me back to bacons and donuts because what goes in, the inherent biases good and bad of the programmers determines the outcomes. As a case in point, look at the difficulty some facial recognition programs have with different races (e.g. they’re significantly more accurate with Caucasians).
So what does this have to do with marketing? A lot. And since AdTech and programmatic and computer-generated “creative” are some of my flash points—as well as catchall phrases for behavior that is a lot like the industry’s previous flight it and forget it mentality. Once an algorithm is blessed, there is little sense that it course corrects other than getting better than here it started.
As marketing becomes omnipresent (for better or for worse), actually connecting in a meaningful way with customers gets harder and harder. Think of NASCAR: How many logos does anyone actually see? Connecting brands and customers is no longer just about being there it is about recognizing each other as likely partners. And we all know how well the dating site algorithms do at predicting THAT little chemistry challenge.
“Robots and artificial intelligence will change the world,” Byron says, “empowering humans to be more productive and live better lives. We will use these technologies to end disease, hunger, and poverty.” In other words, they should be tools to better life, to allow more time for thinking, feeling and creating revolutionary solutions rather than evolutions. In marketing, as in life, we should be using our new tools rather than letting ourselves be dictated to by them.
Hear that HAL?
I’ve been doing a lot of research on introversion for a talk I’m giving. So I’ve been thinking about the Meyers/Briggs personality types as they relate to business. I’m an INTJ and have been lucky enough to have learned how to have a career that has taught me how to solve problems big and small systemically. This has not always been a way of thinking that clients or bosses have wanted in this quick twitch world.
When I have been successful in conveying that vision, that system, for solving the client’s business problem, it’s come down to the ability to capture it in story and/or metaphor that makes the benefits come alive. However, I can remember a disastrous client dinner when I was trying to make the connection between an article I’d done on Michael Jordan and the impact of one small inaccuracy in it and the client’s belief that his one data point was worth hanging his whole marketing plan on.
What I had hoped would be a colorful and entertaining way to make the point that just because the name on credit card payment for a rental car was male, did NOT mean that the shopper/decision maker was male. The client was offended by what he took as my bragging about having interviewed Michael Jordan. My lesson: know your audience and how they learn information. I hadn’t done my homework on the client—though I had on his target audience. That meant I’d missed a critical part of the sell-in by leaping to the story’s end and over the middle, which was selling him part.
“The single biggest problem in communication is the illusion that it has taken place,” said George Bernard Shaw. And as a in introvert, I’ve had to learn as much as I’d like to have people just “get it”, I’ve learned to invest the time in building teams that are all on the same page.
Saul Kripke, a philosopher and logician, supposedly once negated a conference lecturer whose subject was how a double positive never made a negative. Kripke, shouted “yeah, yeah” from the back of the room, his voice dripping with sarcasm and left. That’s the way a lot of the people we marketers pitch feel about our clients’ brands and products. Because of the promises we help them make. It makes it hard to look in the mirror some mornings, doesn't it?
While we all espouse transparency and straight talk, somewhere in the backs of our heads too is the question “What’s the real story?” or sometimes “What’s the whole story?” All too often we don’t challenge our clients and ourselves to come clean, we rely on the fine print and disclaimers to do our legal CYA but is that really good for anyone? Does it make us feel good? Is it an ethical CYA?
I’ve certainly been on the receiving end of brand promise when it’s turned out not so swell. Sometime it matters a little (ok the battery buried in the specs for those wireless earbuds doesn’t actually get me through a movie on a plane).
But sometimes it does matter (I really, really can’t see through those glasses you sent me without having them perched on the end of my nose). It’s then that someone should have communicated that sometimes that happens and you can’t send them back without crawling the stations of the cross. Then I eat the cost and tell friends don’t use THAT company…ever. (BTW, it is NOT Warby Parker, with whom I’ve had the opposite experience).
My point is the down side (and every product or service has one), doesn’t need to be the hook or the headline, but wouldn’t it be great if we challenged ourselves to find it—and find a way to make it honestly a part of the promise? Our glasses are great and low cost but not if your prescription requires your frames fit exactly. Being upfront about your limitations only elevates what you’re great at delivering and strengthens your brand. Then a marketer can look at them selves in the mirror and feel good.
In her thoughtful and insightful article on UX Principals for Better Content, Lucia Z. Wang, discusses content personas as being different (slightly) from marketing personas. This is something we fundamentally disagree with, like a project brief, customers need one holistic persona that captures all their facets without this there can be no alignment between experience, product and marketing.
We use the analogy of a architect building a house (the software developer) but then the landscape designer (the media planner) building the path to the front door on the side of the house. Because they have fundamentally different specs. Ideally the personas capture each type of customer from 360 degrees, because the their needs can differ by time of day, role during the day, etc. It is a blending of not just one use case but of media insights and data points as well as geographic and behavioral information. Even if the persona isn't granular, it at least needs to address all the different stakeholders creating the experience.
So all the creation stakeholders, including of course the client, need to align with the persona before anyone starts pouring the house's foundation.
Inspired by the crashing and burning of Democratic fundraising strategy, Cathy O'Neil’s Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy, and programmatic media buying I’ve been thinking about what the role of humans in marketing is today and tomorrow.
In a future world run by algorithms, big data, and AI, what is the role of the human being in marketing, heck in work, or life at all. Maybe this why the grassroots craftsmen movement has taken root? We want to celebrate imperfection (the not the same, not the perfect) somehow, somewhere.
Now more than anything, it seems our role in marketing is to make mistakes; to bring the imperfect opportunity to do something new through error, guesswork, and serendipity. Perhaps as Leonard Cohen so eloquently put it, “the cracks are where the light gets in” to marketing.
One of the most infamous mistake in modern marketing was when Spencer Silver, a researcher in 3M Laboratories, who in trying to make a stronger glue came up with the weaker glue that made marketing researchers iconic symbol, the Post-it note, possible. And what AI would have gotten from serial killer Gary Gilmore’s last words, “Let’s do it”, to “Just Do It”? There are other versions how the tagline came into being but there is only one Dan Wieden.
Big Data and AI, can move us incrementally forward but only human intervention can make the big leaps that transforms marketing from Robocalling to cultural mantra.
A couple of times when I have been client side I’ve gone fishing. It’s a bad habit and I’m not proud of it, especially now that I’m running my own small group. You all know what I’m talking about: it’s the cheap way to get ideas, insight, perspective on your business by asking a few agencies to come in and suggest what they think they could do for you.
In for-profit companies, no matter what their size, it’s a not so honest way of getting consulting thinking for free. For agencies, it’s a time sump and an opportunity cost much like buying a Lotto ticket. Sometimes it’s completely overt, think the Sears controversy a few years back when its RFP said that Sears would own any submitted material. This led to a 4As position paper defining how to avoid this behavior.
The challenge for any small agency without the leverage of a big holding company behind them: How much do you give away without charge to show your thinking? How much product do you share for free as part of a sampling? Too much product shared, like bait in the water, and the fish goes away with the free meal.
I’m pondering this because we had a meeting with a small digital startup that is have both customer acquisition and retention issues. After an hour of reviewing Google Analytics and the acquisition sources, we had a pretty good idea on how to approach the problem/s. The obvious next step: how would you like us to help you? We can propose an overview of your customer journey and identify the low-hanging fruit to address your issues; you can point us at the areas you believe are causing the problems.
What we got was a well, why don’t you do a deep dive into our GA and then tells more things that we should look at. We’re a bit stymied because we are curious and want to do the right thing but we are a business to and there is that darn opportunity cost.