A Thought Experiment: Lobby Ads

Screen Shot 2017-05-31 at 10.54.34 AMImagine this: A set of large screens in your corporate lobby running, in real time and randomly, the actual digital ads you are running on the pages the ads are being displayed on. A viewer would also be able to stop the ads and scroll back to see any ad at will.

As a marketer, are you OK with your executives, visitors, and the general public seeing your ads and scrolling through them?

Or would you think this is too risky?

If you wouldn’t be comfortable doing this, you need to ask yourself what you’re doing wrong in your digital advertising. And change it.

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A Loyalty Program Retort: British Airways

“When you pass the football, three things can happen. Two of them are bad.”

This quote has been attributed to Woody Hayes–probably incorrectly–Darrell Royal, Chuck Mills, and several other famous football coaches. It’s stuck with me over the years, particularly with regard to retention marketing and customer communication. So much so, that I’ve referred to myself as a “Woody Hayes marketer.”

When you communicate with an existing customer, only a few things can happen, and most of them are bad:

  • “Oh, I’m still paying for that? I need to cancel.”
  • “Who bought that thing? We have to return it.”
  • “This is aggravating. Next time I’ll go with brand X.”

I’m not telling you to never communicate with your customers. What I’m saying is that you need to think carefully why you want to communicate with them, segment your customers strategically, then make sure the message is perfect and perfectly clear.

In a post today, the great Drayton Bird shows us what can go wrong. British Airways wrote a careless letter to a formerly valuable customer. Instead of throwing it away, he wrote back. In his response, you see the thought process that a poorly-written loyalty program letter can trigger.

Although the gentleman’s reply to British Airways is probably one of few well-written responses, you can be assured that many others were thinking the same thing.

Now, in this case British Airways got some candid and free feedback, so maybe it wasn’t a total loss. But I’ll bet their CRM spewed out a whole series of similarly poorly thought out letters. I wonder what damage those letters are doing.

Takeaway: Before communicating with your customers, make sure you need to do it. Figure out one thing you want them to do.  Segment your audience carefully. And for heaven’s sake, hire a good copywriter. And win.

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Automation and Digital Marketing

Screen Shot 2017-05-22 at 12.06.20 PMWhy are digital marketing vendors so obsessed with automating the processes involved in advertising? Everything from deciding on what media to buy, to bidding, tagging, tracking, analysis and creative development has been automated to varying degrees.

Everything seems to be moving along at a faster rate every day. You need to ask yourself one question. Who benefits? 

Hint: It’s probably not you, the advertiser with the money that feeds the system.

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Why Are We Eliminating The Human?

Screen Shot 2017-05-16 at 9.55.24 AMDavid Byrne wrote an eloquent piece yesterday, in which he said:

“Our random accidents and odd behaviors are fun—they make life enjoyable. I’m wondering what we’re left with when there are fewer and fewer human interactions. Remove humans from the equation and we are less complete as people or as a society. “We” do not exist as isolated individuals—we as individuals are inhabitants of networks, we are relationships. That is how we prosper and thrive.”

That reminded me of a discussion with some co-workers about the supposed rudeness of New Yorkers. In my past experience that stereotype has never been true. I’ve never been let down when asking for help. Sure, the interaction might have been short, because New York is a fast-moving place. But the stereotype? Not true.

I believe that stereotypes are more likely to survive in today’s high information era. One can walk the streets of Manhattan, staring at device while looking at Google maps, Yelp and summoning transport via Uber or Lyft. All the while, never having meaningful conversations with New Yorkers. Certainly not the serendipitous types that Byrne mentions in his post.

So, for all we know, the residents of NYC, Paris, or Berlin, are what the stereotype says they are. This isn’t an improvement. It’s a step back.

That makes me a little sad. It’s personal interactions that make life worth living, not shaving the last tenth of mile off a random walk to a restaurant suggested to you by a total stranger. Or finding the optimal hotel for a couple of days of sight-seeing in a strange town.

It’s not the money, the time, the rational decisions that make life worth living. It’s the people. And when we remove people and replace them with glowing screens and algorithms, we’re the worse for it.

I’m not sure our masters at Facebook, Google, Amazon and Apple understand that.

Takeaway: Drop the phone. Have coffee with a human. Pay too much. Take too long to get there. Wander around a little*. Be human. And win.


* From the Tolkien poem in The Lord of the Rings, “Not all those who wander are lost.” You’ll often find me wandering in thought, place, and priorities. I like it that way.

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Ad Exchange Rules of Thumb

Working with ad exchanges? Do these things:

  • Require MRC accreditation
  • Implement a whitelist-only policy
  • Never pay for any impressions listed as “unknown”
  • Require a full site transparency report every week

If the exchange will not agree to the above, drop it instantly and move on.

In addition, you should test your own ads with real humans every day. And have your marketing managers do it, not your interns. Not your ad agency. If you see one questionable website, audit the whole exchange immediately. If you see two questionable websites, pause the spend while the audit takes place.

A good article on what can go wrong is here at Digiday.



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Fake News Root Cause: Digital Advertisers

Screen Shot 2017-05-10 at 9.06.42 AMLike you, I’m sick of  the slanted stories being pushed to me through social media. I’m tired of having to hunt down the source material of everything I read, just to make sure I’m not being fooled. I’m disgusted with the low level of fact-checking and slipshod attention to detail in today’s 24 second “news” cycle. And I realized who’s to blame.

Me. And you. And the companies we work for.

Somewhere in our rush to use digital media, we got obsessed with reach and the size of audiences (the magic word again) and impressions. We got taken for a ride by the ad tech industry hucksters, who built an almost-perfect money-making machine on top of fake inventory created on phony websites.

Jim Rutenberg, of the New York Times, reminded us in an article last week that “Real news costs real money; fake news comes cheap.” If advertisers and our agencies are obsessed with getting more advertising inventory and cheap reach, there’s nothing like fake websites to satiate that desire. Why spend money on quality journalism, when you can invest that money in software engineering and arbitraging dodgy traffic to careless marketers? The margin is far better. Who cares if a little truth gets lost along the way?

Google and Facebook aren’t our friends either. You’re giving them 90%+ of your incremental spend this year. Have they ever fallen short of providing the impressions you “need” either? If volume is the name of the game, they’ll provide it and we’ll fall for it because, as Richard Feynman would say, we marketers “don’t look too hard.”

Shame on us.

Enough is enough. As Shareen Pathak in today’s Digiday asks, yes, media buyers do have a moral obligation to save media. We live in a society that needs a free flow of ideas and a strong, independent press to hold corporations and our government accountable. Quality journalism costs money. The good news is that quality attracts quality, in both viewers and advertiser dollars. It is a virtuous cycle. Somebody’s got to re-prime the pump. That’s the advertiser.

Stop looking at the CPM. Look at quality. Damn what your multitouch attribution model says (which is either owned by a publisher or an ad tech provider) and use common sense. Forget reach. Forget “audiences.” Demand quality. Buy quality. Do your own analysis. Be skeptical of everything you see or hear in the digital marketing ecosystem.

Win for your companies. Win for society.

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Now, Nobody Will Read About It

Funny how things change. In 2011, I wrote that nobody will write about a lousy product, despite the best efforts of your Marcom team. By 2017, because of all the useless viral and social sites, you can get “press” on anything.

It’s just that nobody (aside from bots) will read it.

Takeaway: You still have to build something worth talking about for people to talk about it.

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Assume Fraud Is Worse

When you’re looking to reduce your ad fraud rates, always:

  • Pick the vendor that detects the most fraud
  • Check every impression (not a sample) for fraud
  • Look for brokered traffic (it’s garbage)
  • Assume fraud is worse than you think
  • Don’t be obsessed by scale

Most importantly, stop advertising to audiences. Advertise to people. And win.

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Autonomy: Kitchen Cabinet Installers vs. Office Workers

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Not my kitchen

I’m listening to the kitchen cabinet installers upstairs working on my new kitchen and it dawned on me that they have more autonomy than a typical cube- or open-plan dweller in an office.

As Dan Pink points out, it’s mastery, autonomy, and purpose that really motivates us. One word comes to mind when I think of the guys re-doing my kitchen: autonomy. No bosses leaning over their shoulders, no Monday morning review of last week’s metrics. They’re just left alone to get stuff done.

Sure, the boss shows up every couple of days, but that’s pretty much it.

Leaders: How much autonomy are you delivering to your team this morning? Contributors: How’d your Monday start out?

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Mayan Marketing

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“All you have to know is what it is.”

Said Richard Feynman, in his introduction to his famous Sir Douglas Robb Lectures on quantum electrodynamics at Auckland University in 1979.

Feynman’s brilliance in those lectures and his book on the same topic is stunning. He is able to simply explain a complicated topic using words non-physists can understand and create a desire to learn more about physics and science in general.

“All you have to know is what it is” refers to his belief that the non-physicist didn’t have to know the math to understand QED. It was more important to understand “why.” The math, or “tricks” as he refers to them, can be applied later once you wanted to engage in experimentation or to further explore the principles of science.

Mayans: Good at “What,” Not “Why”

To illustrate his quote, Feynman uses the example of Mayan astronomy, sadly mostly lost to us during the destruction of their writings in the Spanish conquest. The Mayans could calculate the position of Venus in the sky (morning or night) on any given day, via a series of computations, the results of which we can see today in the Dresden Codex.

While the calculations were very accurate, they Mayans couldn’t explain why Venus would be in a particular position. They had a good grasp of mathematics and knew such things as even though they counted in periods of 365 days, that a year was actually slightly longer and could make adjustments in their calendar and calculations.

They just didn’t know how the planets actually moved, as they didn’t get around to identifying what we now know of as Kepler’s laws of planetary motion, before they were murdered by the conquistadores.

For the Mayans’ purposes, the actual reason “why” Venus appeared in certain positions didn’t really matter that much. They could get the dates right, and for their cultural and religious purposes that was enough. It’s not like Venus is going to change its apparent behavior anyway. It’s a planet and doesn’t do anything in an arbitrary fashion.

Watch Feynman speak of Mayan–and digital marketing–priests:

Digital Marketing: Good (Maybe) at “What,” Not “Why”

When I think about modern digital advertising, I see a lot of the Mayan astronomer in us. Many detailed calculations and complicated equations involving things like multi-touch attribution models, fractional attribution, gradient boosting classification predictive algorithms, all running in and updated in real time on multi-tenant Hadoop clusters, powered by 30 petabytes of daily data.

All that is taken together and the output is: if you serve the following types of ads at these times, in this order, with this frequency, you’ll get what you want. A response, a click, a purchase or whatever you decide to optimize for.

The problem is that it is all very Mayan. We count all these observable things, which Feynman likens to counting nuts into a pot, and put them together based on a series of rules and develop law-like proclamations that say if we do these certain things, the thing we are trying to predict, will happen.

It all sounds scientific, but when you ask the Feynman question “why?” the answers are unsatisfying. There’s some vague explanation of how the regression model is so complicated and updated by-the-second that a human can’t possibly understand it. (But never mind that, the nuts will be counted into the right pots!) Sometimes you’ll be quizzed like a heretic. “Well, what’s your idea, smart guy?” You get branded as a non-believer.

Now that might not be a problem if the thing you’re trying to predict is like the position of Venus. It isn’t going to do anything odd tomorrow, the day after or for billions of years. The problem is that as marketers, we are trying to predict what humans will do.

And humans ain’t planets.

People: Hard to Quantify

If humans made decisions in a purely rational way and there were no other inputs to their decisions aside from our marketing–or at least no other variables that we couldn’t include in our models–we wouldn’t have a problem. We may not know exactly why they respond or not to our marketing efforts but, like the Mayans, we could predict the results quite well.

But there are problems.

The first problem is that much of what we do on a daily basis is automatic (Kahneman’s System 1 thinking) which we can’t even describe. The automatic functions that tell us that I like blue while you like green. In this case, I can’t even tell you why I prefer blue. I just do.

I pick up the Duracell batteries off the shelf maybe because my mom always bought them, maybe they met some internal heuristic of “first national brand that catches your eye” or maybe the size of the display was bigger. Who knows?

When I get home, intent on placing an online order for that pair of shoes I saw an ad for today at the bus stop–and need, because mine are a little ragged–my son surprises me with the news that he’s going to Philmont for a Boy Scout trip. Off we go to REI to pick up some needed gear for the high adventure trip. I’ve either forgotten about the shoes or maybe decided a new pair of hiking boots catch my fancy while I’m at the store–for a brand that I’ve never consciously seen an ad for.

How about this one? I wake up in a bad mood and just decide I’m not going to go to the ball game today. I never buy the ticket, never sit in the stands, and never eat the hot dogs and drink the beers that ads for have been carefully targeted toward me.

These are just a couple of simple examples of things we can never model, because humans make most of our decisions either irrationally or unconsciously, using decision criteria that are downright random.

In other words, you can’t quantify most of what we do. We can build overfit models that might provide a lift in response for a fleeting second, but we can’t include everything that influences the decision–including my bad mood. We’re fooling ourselves by telling ourselves that our equations can predict fickle human behavior.

Because It Wanted to Get to the Other Side

So we know why the chicken wanted to cross the road. So why did the human being decide to buy a new pickup truck? You could build some complicated Mayan counting model to try to predict it, or you could sit down and think about it for a minute. Possible reasons are (which could be combined):

  • My current truck broke down/is beat up/I’m bored with it
  • I had an accident and want to get a truck instead of a car
  • I wrecked my truck and need a new one
  • I just got a raise and want to treat myself
  • I just moved to a house in the country and need to transport hay bales
  • I bought a horse and want something to tow the trailer
  • I think the girls/guys will like me more as a truck owner
  • The neighbor guy just got one
  • I liked the color
  • They had a good deal
  • What the hell, why not?
  • Etc.

The interesting thing about all of these types of reasons is that they mostly can be derived from known data about individuals.

We have lists of people with the age and registration date of their current trucks and since we have statistics on how long trucks last, we can have an idea of when somebody might be in the market for a truck. We know when people change addresses. We can see when income changes or when nearby neighbors buy pickup trucks that result in influence on behavior.

The above happens when we start by asking “why” and don’t get too bogged down in the glamorous world of technology and counting. We can then take the reasons why we might buy something, apply it to people and then try to find them in various media, including digital media, and develop math that supports the underlying theory. Not the other way around.

That’s what I call “left to right” marketing or non-Mayan marketing.

More to come.

Takeaway: Stop counting the beans into pots. Find the people who are going to buy your products. Carefully select and segment them. THEN select channels to reach them. And win.

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