Monthly Archives: November 2012

Tis the season for fake savings

Savings is such a marketing game. Nothing is ever 30% or 40% off, and yet consumers respond in droves when retailers announce “savings” or “discounts.” Why is this so?

About 30 years ago behavioral economist Richard Thaler wrote the landmark papers on pricing psychology, with one beautiful premise: People are really bad at judging value so always need a reference point. If marketers control that reference point, they can also control how people feel about value.

Consider something 50% off. A reference point pushes your brain to make a snap decision on whether you’re getting a good deal or not. If you see a dress on sale, marked down from $140 to $70 — 50% off! — you immediately feel good, as if this bit of clothing were a bargain. What you are really considering is spending $70 on a bunch of stitched silk, but the clever marketers have set a high reference point — the $140 starting price that never really existed — to get your juices flowing.

Here are four ways marketers manipulate consumers’ price sensibilities:

1. Artificially high reference prices. If you find a leather coat priced at $300, marked down from $500 — you get $200 in savings! Nope. $500 never existed. The $200 in savings is fiction. $300 is actually leaving your wallet to go to the retailer, champ. But you just can’t help believing it, can you?

2. Price obscurity. That box of candy at the movie theater costs $5.00, but ooh, it’s such a strange, big size, in a box and not bag no less. Must be a good deal! Nope. The reason you never seen those strange candy-box shapes anywhere else is movie theaters are obscuring the fact that $5.00 box of candy has just a little more in it than the bag you get for a fraction of the cost at a drugstore.

3. Price bundling. If you’ve ever seen a TV spot featuring a bunch of acne medicine and skin scream and a special battery-powered forehead scrubber, you’re looking at a bundle of stuff cleverly designed to make discerning the value of the actual products impossible. Omaha Steaks is the king at this; for $89.99 you can order a bundle of steaks that come with burgers and pork chops and hot dogs and mashed potatoes and gee, all that feels like a deal. If you actually broke down the price of each component vs. your local grocery store, you’d realize Omaha is cleverly charging a premium price for each item.

4. Decoy prices. Decoys are products set at high prices that drive you to buy another product at a different price. Realtors do this when they show you a house that needs a new roof, right before they show you the home they really want to sell you. Apple does this by pushing iPods and iPhones with different price points; if you don’t want the most costly version, the “cheaper” one seems a bargain. The decoy is meant to turn you off, so you swing over to the next product that will turn you on.

This pricing irrationality is driven by our ancestral instincts, which help us make snap decisions on value. If you were in the wilderness, you’d only get a quick second to decide if the berries are nutritious or poisonous, or if that snake will bite you. For tens of thousands of years, we’ve had to use fast references from the world around us to discern what helps us survive and not die. Because we survived in clans, if another human told you this berry was better than that one, you’d go ahead and take a bite.

All of which explains the long lines at the mall.

Image: Voshie

Tis the season for fake savings

Savings is such a marketing game. Nothing is ever 30% or 40% off, and yet consumers respond in droves when retailers announced “savings” or “discounts.” About 30 years ago behavioral economist Richard Thaler wrote the landmark papers on pricing psychology, with one beautiful premise: People are really bad at judging value so always need a reference point. If marketers control that reference point, they can also control how people feel about value. Consider something 50% off. A reference point pushes your brain to make a snap decision on whether you’re getting a good deal or not. If you see a dress on sale, marked down from $140 to $70 — 50% off! — you immediately feel good, as if this bit of clothing were a bargain. What you are really considering is spending $70 on a bunch of stitched silk, but the clever marketers have set a high reference point — the $140 starting price that never really existed — to get your juices flowing. Here are four ways marketers manipulate your price sensibilities: 1. Artificially high reference prices. If you find a leather coat priced at $300, marked down from $500 — you get $200 in savings! Nope. $500 never existed. The $200 in savings is fiction. $300 is actually leaving your wallet to go to the retailer, champ. But you just can’t help believing it, can you? 2. Price obscurity. That box of candy at the movie theater costs $5.00, but ooh, it’s such a strange, big size, in a box and not bag no less. Must be a good deal! Nope. The reason you never seen those strange candy-box shapes anywhere else is movie theaters are obscuring the fact that $5.00 box of candy has just a little more in it than the bag you get for a fraction of the cost at a drugstore. 3. Price bundling. If you’ve ever seen a TV spot featuring a bunch of acne medicine and skin scream and a special battery-powered forehead scrubber, you’re looking at a bundle of stuff cleverly designed to make discerning the value of the actual products impossible. Omaha Steaks is the king at this; for $89.99 you can order a bundle of steaks that come with burgers and pork chops and hot dogs and mashed potatoes and gee, all that feels like a deal. If you actually broke down the price of each component vs. your local grocery store, you’d realize Omaha is cleverly charging a premium price for each item. 4. Decoy prices. Decoys are products set at high prices that drive you to buy another product at a different prices. Realtors do this when they show you a house that needs a new roof, right before they show you the home they really want to sell you. Apple does this by pushing iPods and iPhones with different price points; if you don’t want the most costly version, the “cheaper” one seems a bargain. The decoy is meant to turn you off, so you swing over to the next product that will turn you on. This pricing irrationality is driven by our ancestral instincts, which help us make snap decisions on value. If you were in the wilderness, you’d only get a quick second to decide if the berries are nutritious or poisonous, or if that snake will bite you. For tens of thousands of years, we’ve had to use fast references from the world around us to discern what helps us survive and not die. Because we survived in clans, if another human told you this berry was better than that one, you’d go ahead and take a bite. All of which explains the long lines at the mall.

Facebook’s new matchback tracking finds you at the mall

Facebook has made an old marketing measurement trick new again, getting many marketers excited that it could finally match online ad impressions to offline shopping behavior for better ROI calculations. The only question is, will it work?

First, here’s the old trick — a “matchback.” Say you were a marketer running a direct mail campaign, and wanted to know how many people really bought your product after you sent them postcards with “50% off our Gizmo!” messages. You could count phone calls or web visits if you printed unique numbers or URLs on the cards, but those always undercount response — for every 10 people who call in or click to your landing page, another 20 might show up at the store. If you can’t count all the behavior, you’ll never know how the campaign really worked. Ah, but being clever, you decide to match the list of people you sent mailers to with the names of buyers at the stores (where computer systems can count up those names and addresses via loyalty cards). If that mailing cost you $50,000 and you generated $200,000 in sales, voila! — you have a 4:1 return on investment!

This is called a “matchback,” because you match the people who buy back to the list you sent the direct mail to. Doing this, of course, requires that you have a centralized ID system for the people you marketed to that can be matched to the actual people who buy at the store.

Enter Facebook, replicating all of this online. Facebook has the largest data set in the world of social media users and their corresponding email addresses; it has entered a partnership with Datalogix, a massive data company that has detailed information on most U.S. consumers compiled from retail loyalty cards, which identify consumers at stores. Online tracking of your ID + offline tracking of your ID = hey, a new matchback!

In simple terms, Facebook is trying to solve the “real ROI question” on its advertising, by finally counting all possible sales — not just online clicks — resulting from FB ads. Marketers love this idea, because finding the real source of sales is extremely difficult when most digital advertising can only be counted to the online checkout and not the offline behavior.

See FB ad for suit. Buy suit at mall. Now, FB knows.

Let’s use a theoretical campaign for Men’s Wearhouse as an example:

1. You see an ad on Facebook for a Men’s Wearhouse suit. You click or don’t click on the ad, it doesn’t matter.
2. This weekend, you go to Men’s Wearhouse and buy a suit.
3. Men’s Wearhouse now gets a report from Facebook matching people exposed to their FB ads with people who actually make the product purchase.
4. Men’s Wearhouse marketers can now tally up all sales and revenue from those ads, and get a true picture on ROI.

To protect privacy and avoid freaking out FB users, individual personal information is disguised through a series of data hashing (which prohibits marketers from learning that exactly you, John Doe, bought the suit), but in aggregate marketers can get a count of exactly how many ad exposures match how many consumer sales.

While it all sounds sexy, Facebook’s matchback poses a question — could it over-count results? Facebook ads sure reach a lot of people; because the ads have low click-through rates (about 0.03%), a small $10,000 budget spent on Facebook at an average $1.50 cost per click would back out to a whopping 22.2 million ad impressions. If you hit the entire world with your ad message, and some buy, those people may be triggered by many other factors, and Facebook could be taking credit for sales that might have happened anyway. Maybe you just really needed a new suit.

No matter. With Facebook struggling to continue to scale revenues, a matchback service in the world’s largest digital ecosystem will be certain to lure marketers. Correlation may not be causation, but Facebook will sure look good taking credit for it.

Image: Toni Blay

What’s wrong with Groupon?


Poor Groupon. The stock price of the cost-cutting online coupon service has plummeted below $3, down nearly 90% from its IPO launch high. Nearly two years ago I dissected the pitfalls of Groupon’s model — back when the buzz on the service was red-hot — over at Digiday. Groupon isn’t a bad idea; it’s just a commodity idea, and commodities tend to have margins and profits hammered out of them. The trouble with Groupon is it is not sustainable or competitively defendable. Here’s a replay below:

It’s tough to knock Groupon, the deal-of-the-day web sensation that could be the fastest company in history to reach $1 billion in sales. Groupon is wildly popular today with 35 million registered users, skewing to women with upper incomes. It offers what economists call an assurance contract — a deal that is only good if enough people sign up for it — so businesses know if they play, they’re almost guaranteed a crowd. What’s not to love? Plenty. Let’s take a look.

Groupon’s pricing model is unsustainable. Gouging is an ugly word, but damn, Groupon charges a lot — businesses often pay 50 percent of all revenue associated with their special offer to the service. This is compounded because you have to offer a “discount” as well to build the deal. So if you run a massage spa and want to give consumers a “50 percent off” Groupon offer, you’d cut your normal $100 rubdown price to $50 — and then pay Groupon half the remainder, or $25, for every customer in the door. In effect, you’ve given away 75 percent of your total revenue. Yikes.

There is a disincentive for businesses to repeat offers with Groupon. Companies can give Groupon a shot once if they’re willing to play price-framing games (e.g. mark up your service high to then “discount” it low), perhaps to get a splash in a new market. But no company can stay in business with repeated marketing that gives away 75 percent of its sales. Don’t expect to see annual media plans with Groupon as a recurring line item next to banner advertising and Google search. What happens to Groupon after it cycles through all the interested businesses once in each market?

There are no barriers to competitor entry. Yes, Groupon has a network of millions of consumers it can email offers to. But who else has similar networks? Apple, Facebook, Walmart, and almost every large retail brand has lists of customers it could reach with the same quasi-viral coupon deals. Google Offers, announced in January, is just one of hundreds of Groupon competitors. LivingSocial is backed by online heavyweight Amazon, and we hear Amazon has a pretty sweet product line. Others, such as Dealery and Yipit, aggregate deals from multiple coupon players, just as Kayak and Travelocity give you ticket prices from numerous airlines. Coupons, it seems, are a commodity, and anyone with a network can play.

There are no barriers to customer exit. Consumer loyalty can be built with several strategies — price discounts are one form, but the least effective because low prices are easily matched; points, rewards, game mechanics, customer service, and positive and negative switching costs are stronger ties. Facebook has positive switching costs because once you’ve uploaded your contacts and family photos to its platform, you’d hate to leave that personal investment behind. AT&T uses both positive and negative switching costs to hook you — deals on phones that extend future contracts, and nasty termination fees if you cancel early. Groupon is just a price play.

A wise observer might look at the past few years of economic malaise, coupled with the novelty of social networking tools, and conclude Groupon is riding a chance wave of interest from businesses desperate for sales and consumers desperate for savings. With hefty fees, business one-offs, keen competitors and customers looking for deals everywhere, you have to wonder how long will Groupon’s billions last.

Image: Purplemattfish

Hm. What if Apple’s Siri is learning from us?

While many of you ask Siri questions on your iPhones, have you ever considered that Siri may be monitoring you as well … and getting smarter because of what you ask? I wrote over at Google+ a while back that the iPhone Siri app may be the first real foray of humanity into artificial intelligence. Here’s an update:

Many have tried to build artificial intelligence. Apple, thanks to the popularity of the iPhone, may be the first to succeed by crowdsourcing responses from its Siri assistant. Siri is an application in the iPhone that answers questions, looks up information, and can take basic orders such as setting an alarm clock. Pundit Andrew Sullivan recently noted the program improves over time by collating user questions and requests, and learning from whether responses are accepted. Big software spread across millions of people provides more than a service, you see — it also taps into all those users as a free research pool, and can improve based on user feedback. One joke in tech circles was Google gave away a free phone-number-lookup service called GOOG-411 for a while, getting millions of people to voice in questions, and then pulled it — because Google had finished human trials of voice-recognition software and no longer needed us for its product development.

Siri is doing a similar thing with humans today — except instead of just queries for phone numbers, we are asking it almost anything. Millions of humans are directing Siri to do things or find information, and if Siri fails, we ask again in another way. Somewhere in the cloud Siri is collating all of this information to become smarter and smarter at answering, and anticipating, any question. Siri is learning based on the biggest data model in the world, millions of real human minds.

AI takes both big data and self-awareness

Decades ago a World War II code-breaker named Alan Turing came up with a concept of how to tell when artificial intelligence exists: if the system can fool a human observer into thinking it is intelligent, then for all intents and purposes it is. This became known as “the Turing test,” and modern prognosticators such as Ray Kurzweil believe that as computer speeds become faster and faster, eventually software systems will reach the point when they are for all intents intelligent — and will then surpass us. But more than simulation is required; true intelligence requires aspects such as learning from experience, creativity, and most important becoming self-aware. Awareness is a recursive form of reflection in which you realize that you are thinking, that you have an opinion of yourself, and you see the world around you as influencing your stature and survival. These are aspects that no computer systems have so far achieved … so far as we can tell.

Siri has the best shot, because she was launched based on artificial intelligence research. Siri began as the SRI International Artificial Intelligence Center project, funding by the U.S. military, and was an app that Apple acquired tied to deep databases such as Wolfram Alpha (an intellectual search database), Yelp (a leading review site), and Rotten Tomatoes (the movie review site). These datasets in turn were built by hundreds of thousands of human volunteers. If you ask Siri for a movie review, she pulls in information from a review that some other human once wrote. Siri is already using insights from human minds, perhaps even your own.

You don’t own an iPhone with Siri on it. You are participating in a vast study to help make Siri smarter. If any system is ever going to gather enough input to become truly artificially intelligent, what better way than to install it on mobile devices that millions of humans use, and to have us carry it around with us, informing it, every day? Go ahead, talk to Siri. She wants to hear more.

Image: AcidZero

Upscale Quartz skips banners, goes mobile first

This is rather interesting. David Bradley, chief of Atlantic Media (which publishes The Atlantic), has launched a new elite business publication that is already challenging The Economist. In September Quartz, available only online at qz.com, booted up with 20 writers; in October it surpassed 850,000 unique visitors, already matching 10% of the global traffic over at The Economist.

Behind the visitor growth are two amazing feats — Quartz accepts no standard display banner advertising, and it is not designed like typical web sites. Quartz is one of the emerging digital publications built first for tablets and smartphones, using a tile aesthetic that is more intuitive for pudgy fingers than mouse clicks. Quartz, as a digital-only beast, is of course keenly interested in marketing dollars, but ads are eschewed in favor of so-called sponsored content — paid advertorials that, while clearly marked as such, run in the same format as the news articles. For example, in the most recent edition of Quartz, Boeing is featured with this advertorial:

A better view on efficiency

Imagine cutting your vehicle’s fuel consumption by 20% and upgrading its interior to an unprecedented degree. If you’re Boeing, you don’t have to imagine. Their new 787 Dreamliner has done just that, exceeding the expectations of both engineers and passengers alike…

As with all advertorial copy, the story reads with whiffs of ecstatic silliness and awkward prose (advertorial writers tend to sound as if they are walking backward, and are always surprised that the product they are writing about has “exceeded expectations” of some sort). But at the same time, the sponsored content is compelling, breaks out of the clutter, and is clearly labeled as such so in no way tricks the savvier reader who just wants to consume pure editorial.

With Quartz, Bradley is betting big that standard banner formats aren’t the best way to monetize digital in mobile, especially on the small iPhones and Droid tablets loved by upscale business travelers. When space is small, advertisers have to be more clever about how they fit in. David Carr at NYT reports the strategy may work: Atlantic Media, after years of fighting the deadly decline of print, has refocused on digital content to double revenues from $20 million to $40 million in the past four years and now is back in the black.

And Quartz has one more secret weapon: Unlike The Wall Street Journal and The Economist, it has no paywall or subscription fees — presumably because it can float on the hefty premiums from its advertorial. Open systems flourish, and in a world of social media where users like to share content freely, open systems also tend to get lots of monthly unique visitors.