Monthly Archives: September 2012

Meet McDonald’s TV. It’s worth a quarter billion dollars.

McDonald’s has been on a tear lately. Its stock has nearly tripled since 2006, global revenue is up to $27 billion, and more than 45% of its restaurants have been upgraded from the stale plastic of yore to the woodsy-green-and-steel hues of a classy Starbucks.

And now, here comes McDonald’s TV. About 700 restaurants are testing the “M Channel,” an in-store television network with custom news, entertainment, and ad inventory for marketers eager to get at McDonald’s customers.

We estimate in the U.S. alone this TV outlet is worth more than $250 million in potential new revenue for McD’s. Here’s the math:

  • McDonald’s makes $8.5 billion in annual U.S. sales. Assuming a $5 average order size per customer, that’s 1.7 billion U.S. guests per year or 4.6 million people visiting McD’s daily.
  • Now, let’s assume the average guest spends 15 minutes inside the stores (some drive-thru, others stay longer). That’s 70 million minutes of TV exposure per day once the M Channel is in all U.S. locations. If McD’s weaves in only one commercial message every two minutes, that’s 35 million daily commercial ad impressions.
  • Finally, assume McDonald’s can tell marketers these ad impressions have a bit more value than the 166 regular television spots most consumers ignore at home each day. (The average U.S. consumer has the TV set blaring 5 hours daily, working out to that many conceptual ad exposures. Yep.) McD’s could charge a $20 CPM (cost per thousand impressions), about double that of standard cable rates.
  • That’s $700,000 in daily advertising inventory potential, or $255 million per year in TV spots that could be sold.
Of course for McDonald’s, a quarter-billion dollars is a rounding error equal to barely 1% of its total revenue. But a 1% lift for a company with fiercely competitive margins is a good thing, and the additional upsales potential of getting consumers to hear about deserts and coffee could jack McDonald’s total revenue further.
And for advertisers hungry to break through old TV clutter, the M Channel could be tasty.

The novelty effect

This is a story about why stories no longer hold your interest.

About 30 years ago Cormac McCarthy sat down to write “Blood Meridian,” a gruesome Western tale with evocation like this:

“That night they rode through a region electric and wild where strange shapes of soft blue fire ran over the metal of the horses’ trappings and the wagonwheels rolled in hoops of fire and little shapes of pale blue light came to perch in the ears of the horses and in the beards of the men. All night sheetlightning quaked sourceless to the west beyond the midnight thunderheads, making a blueish day of the distant desert, the mountains on the sudden skyline stark and black and livid like a land of some other order out there whose true geology was not stone but fear.”

It’s beautiful stuff, but as I read it, I doze a bit after 10 pages or so and then pick up my MacBook to check more modern writing like this:

“I don’t know if I’ve ever seen @maddow deliver such a blistering, fed up, disgusted introductory monologue.”
“Love this Eury Perez guy. Our own Dave Roberts! #Nats”
“49 Things You Must Tell Your Baby…”

First, I have the author who would win the National Book Award and Pulitzer Prize. Second, I get Twitter gibberish about liberal talking heads and 49-things linkbait. Yet somehow Twitter, like its social-media brethren, feels more alive and interesting than all the beautiful words about horses poor Cormac can muster.

One possible explanation is what psychologists call “The Novelty Effect,” or the tendency of people who encounter a new experience to have a higher emotional or cognitive response. This effect can sometimes be a downer — like your first airplane ride, where you clutched the armrests in a silent scream — or an upper, like your first kiss, or A+ from a teacher, or cash bonus greater than $1,000. You get more jacked when you see Santa Claus for the first time, and over time, more meetings with the big elf never recreate the initial thrill. New technology creates similar juice by making us put more attention on new communications devices, and in turn we feel like we’re getting more out.

Google+ was a recent example. When the moderately improved version of Facebook first showed up, people loved the beauty of the layout, the thinner-but-more-meaningful social links, the feedback and debates that appeared rapidly beneath every post. G+ felt better than other tools at first because, in its novelty, it attracted our focus, we put more in, and the resounding ripples gave us more ego-boosting content out.

Eventually the love affair fades, like a sexy iPhone 4S suddenly looking boring next to the 5, but social networks in general still provide more arrogant reflection than the cold hard TV tube or the silent pages of a book.

Quality has little to do with the appeal of novel technologies, because the newness itself is what forces our attention. Social media is over-rated for its supposed radical restructuring of human communications; what we really like is the snazzy interface, which gives us new ways to reflect on our own intelligence and charm. Like the classic Dilbert cartoon in which one coworker introduces a handsome new manager with the caveat, “don’t worry, he gets stupider the longer you know him,” eventually the new thing goes “ooga!” and we realize we must find something more new.

It’s hard to believe that a sudden skyline stark and black can’t hold our attention. But then, McCarthy never retweeted you.

Prediction markets as a form of artificial intelligence

As the current political race nears the finish line, here’s a refresher course on prediction markets. I wrote this column for Businessweek back in October 2008, a month before Barack Obama was elected president. Today, you can check Barack vs. Mitt’s odds over at As of this writing Intrade places Obama’s chance of victory at 66.8%.

With all the fuss about Wall Street lately, one fact has gone unobserved: The stock market has performed brilliantly as a form of artificial intelligence. That’s right. The Dow Jones can see the future, and last month it tried to warn you.

Consider what happened on Monday, Sept. 29. A $700 billion bailout package was on the table in Congress, and many constituents were opposed to it, complaining that it would help fat cats on Wall Street but not mainstream America. The House of Representatives, where members are up for re-election in November, stopped the bill. That same day, the Dow Jones industrial average plunged almost 778 points, its biggest one-day percentage decline in two decades. A vast group of investors bet instantly that the political logjam was very bad for the economy. And as the global stock sell-off continued in the succeeding days, Americans began realizing that failure to do something to help the credit markets was not helping their personal fortunes.

A Pool of Intelligence 

How did Wall Street know what would happen? It acted like a prediction market, a pool of intelligence that can foresee the future. Prediction markets are simply bets on ideas: What do you think something is worth, and more important, what will it be worth tomorrow? When groups of people bet on something, their combined intelligence is often remarkably prescient.

British scientist Francis Galton was one of the first to notice this in 1906, when he observed 787 people at a country fair try to guess the weight of an ox after it was slaughtered. The average of all guesses was 1,197 pounds, only one pound less than the correct answer. James Surowiecki expanded on Galton’s observation in his 2004 book The Wisdom of Crowds. The most obvious example of collective intelligence is sports wagers, where the odds are really set by all people placing a bet, he wrote. Think of a horse race where the odds are 3 to 1 that one horse will win. If suddenly more people start betting on that horse, the odds rebalance in that horse’s favor. The tendency of sports fans to collectively set the right odds is how bookies make money. If it works in sports, “wouldn’t people betting on other kinds of events be equally as good, as a group, at predicting them?” Surowiecki asked.

Recently new types of markets have emerged to specifically predict the future. The Iowa Electronic Markets is one of the most famous prediction markets, set up to foretell U.S. Presidential elections. Thomas Rietz, a University of Iowa finance professor who helps direct the IEM, notes it has accurately foretold each election result since 1988 with only a 1.33% error rate in voter totals. 

Games for Adults 

How does it work? Traditional markets such as stock exchanges, Rietz says, are “affected by a whole range of factors.” Prediction markets, on the other hand, try to “untangle those factors that cause change,” he says. The IEM lets you bet yes-no on simple questions, such as will Senator John McCain win the election? If the odds are 50-50, you could buy a 50¢ contract and get a $1 payout if you win (while someone on the losing side of that bet is out 50¢). As bettors change opinions, the odds shift. McCain has had a rough patch recently; on Oct. 11 the IEM “winner take all” contract for McCain had fallen to 15.5¢—the market’s way of saying he has 15.5% odds of becoming President.

Some prediction markets act as games for adults. The Hollywood Stock Exchange lets you place bets on whether movies will succeed at the box office. The Popular Science Predictions Exchange puts odds on whether almost any event will happen—say, whether someone will hack the iPhone within two months of its release. (Those who bet yes won the prize.) Corporations, too, are realizing the value of collective intelligence. In 2006 Yahoo! asked employees to dream up new products, but instead of leaving final judgment to top brass, it created a prediction market that let employees bet on which idea would thrive in real-world competition. Microsoft and Google also have tapped the wisdom of employees with similar markets.

Public Health Implications

But now, prediction markets may have even wider applications, bearing relevance to public health and global warming, for example. The IEM is now experimenting with a private flu market that would enable health-care professionals from different states to bet on when flu will erupt in the U.S. and how severe the outbreak will be. Rietz says the flu market may solve a thorny problem for the U.S. Centers for Disease Control, which until now had to watch flu outbreaks in a rearview mirror, too late for hospitals to prepare. “Flu is actually spread in a predictable pattern,” Rietz says. “Kids get it first, parents stay home with the kids, and local clinics and nurses see it happening,” he explains. “If we can get their information aggregated, hospitals can have an early warning.”

Academics now hope to move prediction markets beyond single future predictions to evaluation of many alternative, possible futures. To understand this, think of the basic problem of setting public policy. Will the recently approved $700 billion bailout really unlock credit markets? Or, how about these questions: Would taxing CO2 emissions stop rising sea levels? Which form of energy exploration—oil, coal, wind, solar, nuclear—is most likely to lead to U.S. energy independence? Which Presidential candidate, Barack Obama or McCain, is least likely to start a new war? Each of these questions requires an “if A, then B” prediction.

The idea of scenario forecasts using group intelligence was created by Robin Hanson of George Mason University, who has noted public policy often fails because it is created by an “insider’s club of pundits and academics.” The trouble with humans, it seems, is that even when we’re smart, we have access to imperfect information and follow the groupthink of our peers. Because we often disagree with other groups, we band together and end up agreeing too much with our own teams. No single leader can overcome such biases and data gaps to predict with certainty whether an action will succeed or fail. But Hanson suggests markets can do just that.

Bubbles Aren’t New 

Certainly all markets have their flaws. Bubbles and busts have been around since the Dutch tulip craze of the 1630s, when single tulip bulbs traded at values 20 times greater than the annual income of most workers. Wall Street’s recent mania over questionable mortgages caused today’s current crisis, and the manic sell-off backlash was eventually driven by fear, not logic.

But if markets are watched carefully they reveal a vast artificial intelligence, based on the individual data each human provides as he or she makes a best guess about the future. In a way, we are all like bees, frantically collecting pollen and rarely looking up to note the overall hive activity. Occasionally, something like the Dow falling almost 778 points in a single day—or a 936-point rebound a few days later—makes us see the big picture.

Image: Matt Westby

The miraculous illusion of Amazon’s free shipping

People are funny about perceiving value. We all want value — we run mental calculators in our minds, trying to predict transactions of love or money in our favor, and yet typically we suck at this. In a world of millions of products, we can’t tell if $400 for a leather coat or $20 for a book is a good deal. So most companies resort to pricing games to bend our minds into a state where we feel we’re getting value.

My favorite pricing gambit is Amazon Prime — a daring attempt by Amazon to convince us that every time we drop scores of dollars on an order, the shipping that supports that purchase is “free.”


Amazon is playing a classic pricing game, used by everyone from Apple to Walmart, to make the perceived value of a purchase feel better. It includes a basic reference price — first, set up a higher price, or in this case, “shipping costs X” … and then discount below it, in this case, “shipping costs $0.” It also uses price obscurity, bundling the real cost of something into an unusual package (sort of like candy sold in unusual package sizes at movie theaters). Amazon Prime costs $79 annually. If you pay, Amazon says you get “free” shipping for one year plus streaming of some video content, and one free Kindle book to rent monthly. Voila! We feel like we’re getting a deal.

First, obviously, shipping costs something. There are no magic elves delivering books, and the guy in the big brown truck in your driveway makes a salary. Analysts have figured this Prime fee actually costs Amazon $90 in shipping and streaming services for a typical customer, so Amazon loses money per “Prime” customer … if you only count the cost of shipping and streaming. For every $79 covering shipping costs that comes in, Amazon spends $11 more than that to ship stuff out. All told, Amazon in 2011 had shipping revenue of $1.55 billion but paid out $3.99 billion in shipping and fulfillment costs, for a net loss on shipping of $2.4 billion. Yep, Amazon lost billions to get goods to your home.

But what about all the profit from all those books and clothes and shoes you order via

Well, that is big. In 2011, Amazon made $48 billion in sales and $631 million in net income. That works out to a 1.3% profit margin per customer order — thin, because this is a competitive business, but one that Amazon certainly wants to scale. And “free shipping” is helping the company grow. Amazon sales have been accelerating, up 41% overall in 2011 vs. 40% in 2010 and 28% in 2009. Amazon notes in its annual report that “increased unit sales were driven largely by our continued efforts to reduce prices for customers, including from our shipping offers…”

When you add it up, it’s a clever gambit. Amazon loses $2.4 billion in shipping and fulfillment to gain $48 billion in sales … while jacking up growth to please investors at a torrid 41% rate per year. In balance, Amazon comes out way ahead. And all of this growth — in a world where Amazon has been the top e-commerce player for years — means on average, you’re likely spending 41% more at each year. Other retailers have noticed, which is why you’ll see “free shipping” on nearly every e-commerce site this holiday season. Morgan Stanley has predicted Amazon may approach $100 billion in sales by 2015, simply by moving its spending per customer from the current $275 per year today closer to the $750 per customer spent at Walmart.

Oops. Did you catch that? The typical Amazon customer spends $275 annually there today. If you sign up for $79 in Prime free shipping above that, $79/($275 + $79) or 22% of your annual spending goes to … free shipping.

So go ahead, get that shipping deal. At least, it feels like a deal if you don’t do the math.

Image: Selva

Strategy requires that you make a choice

Harvard Business Review is a thick, fibrous magazine, a green spinach of publications that when you pick one up at an airport newsstand provokes the clerk to do a double-take at the $16.95 price. Seventeen bucks? Really? Why does one magazine cost so much?
Quality, in fact. In the September 2012 issue, HBR unveils “Bringing Science to the Art of Strategy” — a simple and insightful framework for making the business cliche real. “Strategy” is too often tossed around as a buzzword, but the authors of this bit — who include A.G. Lafley, former CEO of Procter and Gamble — explain that strategy is simply about making a choice.
“Why do the operations managers in most large and midsize firms dread the annual strategic planning ritual?” the authors begin, and then answer it’s because most organizations get mired in data, analysis and issues without framing the discussion in terms of choices that drive action.
Chess is a game of strategy, and to play you have to move the pieces. You have to think of different outcomes, and then choose each piece, and then decide its direction. Running an organization requires the same actionable choices.
The authors provide an insightful framework for listing, and selecting, your strategic choices:
  1. First, don’t list “issues” in your discussion, but instead define “choices.” For instance, imagine your profits are down. A typical management offsite might prioritize that issue, and then brainstorm all the reasons why. But reframing “low profits” as a choice means coming up with options that move the problem. Say: (a) you could create new products with higher margins, (b) you could raise prices on current products, (c) you could drop supply costs on current products, (d) you could enter a new market with higher-margin products, (e) you could exit a sector with low-profit products, or (f) you could acquire another company that has higher margins. In general terms, list your major choices.
  2. Second, generate strategic possibilities. Look at the chess board, and don’t think of where you are now, but where you possibly could be tomorrow. Don’t be critical in this stage, simply imagine different futures. Say for (c) above, in one future you drop supply costs, so a strategic possibility is you find a new inventory supplier at the same quality levels with lower material or labor costs. As you list possibilities, be sure to include the status quo, where you are now, because staying in one place is a choice as well — and standing still can hurt you as the competitive market moves past you.
  3. Third, list the conditions required for success for each possibility. For (c) above, dropping supply costs, you must find a supplier in India; manage communication, time-difference, cultural, currency, and negotiation issues; assure quality control; test the products; have customers willing to pay for this new product. If all of those conditions could be met, the strategic choice is an option. If someone is critical in this stage, reframe it as a condition. “We don’t know any firms in India!” becomes “For this future scenario to work, we would need to find firms in India.”
  4. OK, OK, in step 4, now you can be critical. For each “condition” that must be met, define the barriers. This includes prioritizing barriers and designing tests to see if the barriers hold true. Because you are likely to have long lists of barriers, the authors suggest starting with the biggest, thorniest ones — if those fail, you can toss out the possibility.
Bravo, you are now ready to make the choice. Lafley and team tell the story of P&G going through this process in the late 1990s to solve the problem that while it had successful beauty products, it was missing millions in the profitable beauty care sector. P&G considered acquisitions and various brand options before deciding to move Oil of Olay upmarket from a perceived stodgy cream for old ladies to an upscale beauty product. It wasn’t enough to define the issue and list the problems; P&G had to make a choice from several possible paths forward. In less than 10 years the revitalized Olay brand was generating $2.5 billion in yearly sales.
You don’t play chess by analyzing the pieces and describing them. You have to decide where to move on the board. Thanks, HBR, that was worth seventeen bucks.

Deconstructing the canned Pepsi Facebook feed

Social media promised a new ability for brands to engage with and build relationships with their customers. So why does Pepsi have such a simple Facebook feed?

If you “Like” Pepsi in Facebook, here’s what you get: A series of Pepsi cans in your Facebook feed. Cans. And more cans. Blue cans with the Pepsi logo, blue cans in front of walls, blue cans on blue cans sitting in the sand at the beach. Anyone savvy in marketing might wonder, Pepsi, can’t you do better than cans? Why aren’t you engaging with your Facebook customers?

We suggest there are three reasons Pepsi is spraying its Facebook fans with little more than images of its blue cans:

1. Engagement doesn’t work for everyone. Two decades ago, the one-to-one guru Don Peppers posited that engagement (he called it personalization) only made sense for companies whose customers had wide variances in terms of what they need from you and the financial value they provide to you. Book readers and movie renters have wide ranges in needs, so it makes sense that Amazon and Netflix became experts in personalizing recommendations. Personal investors have wide ranges in financial value, so of course financial advisors treat Jane different from Jim when they call. The more diverse the needs and values, the more critical engagement — and its corresponding personal feedback — is to persuade customers to do business with you.

But if all of a brand’s customers simply want the same commodity, it makes little sense to personalize communications or engage in meaningful two-way conversations. Gasoline, laundry detergent, kitchen ovens and sodas are all simple commodities. Customers of such products have little range in value, so treating me differently than you won’t really drive more sales. So Pepsi is doing the right thing — it’s ignoring the expense of engagement and simply spraying everyone with one simple message. We have pretty blue cans.

2. Frequency is important. U.S. consumers are exposed to thousands of advertising messages each day: more than 160 television spots, scores of web pages, and hundreds of social-media updates. The typical Facebook user makes 3.5 “Likes” or comments daily, and with the average user having 234 friends, he or she (Facebook Edgerank filters notwithstanding) could be exposed to 820 messages bouncing back to them daily. Brands must break through this clutter, and the best way to influence consumers is to focus on frequency — the idea that it takes 3 or 4 outbound messages per week for a brand to penetrate a consumer’s mind. By peppering you with blue Pepsi can images, Pepsi is building a frequency of advertising impressions that might influence you next time you’re shopping in the soda aisle.

3. Social media is not “social” most of the time — because if one-way communications are a worthy goal, the “social” is gone and all that is left is broadcast media. This sounds cold, but most of social media has turned into broadcast as users spray other users with their wit, links and thoughts much more than they engage in two-way conversations. If you don’t really listen to the 1,000 people you connect with on Twitter, what chance does a non-corporeal brand have to really engage with you?

Pepsi is doing the right thing by turning social media into a spray-and-pray advertising platform. That’s the hard logic of a world where there are more commodity brands who want to engage with you than you have attention to give back in return. Pepsi may seem annoying in your Facebook stream, but look again, people: All Pepsi is doing is making its soda pop.