Tag: Association bias

Why Legos Are So Expensive — And So Popular

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Lego

A lot of people wonder how Lego, selling a now un-patented product, can command both massive market share and sell at twice the price of the nearest competitor: Megablocks.

Rhett Allain, in his WIRED article addressing why lego sets are so expensive, unsatisfyingly concludes “Honestly, I don’t know much about plastic manufacturing – but the LEGO blocks appear to be created from harder plastic. Maybe this would lead them to maintain their size over a long period of time.”

While lego offers a superior product, that doesn’t wholly account for why they sell so well.

Chana Joffe-Walt offers a much better explanation in her NPR Planet Money article:

Lego did find a successful way to do something Mega Bloks could not copy: It bought the exclusive rights to Star Wars. If you want to build a Death Star out of plastic blocks, Lego is now your only option.

The Star Wars blocks were wildly successful. So Lego kept going — it licensed Indiana Jones, Winnie the Pooh, Toy Story and Harry Potter.

Sales of these products have been huge for Lego. More important, the experience has taught the company that what kids wanted to do with the blocks was tell stories. Lego makes or licenses the stories they want to tell.

Lego isn’t just selling a product, they are selling a story. Still, I doubt that alone fully explains the difference.

I think Warren Buffett offers the best explanation. Talking about the brand power of See’s Candies, he comments:

What we did know was that they had share of mind in California. There was something special. Every person in Ca. has something in mind about See’s Candy and overwhelmingly it was favorable. They had taken a box on Valentine’s Day to some girl and she had kissed him. If she slapped him, we would have no business. As long as she kisses him, that is what we want in their minds. See’s Candy means getting kissed. If we can get that in the minds of people, we can raise prices. I bought it in 1972, and every year I have raised prices on Dec. 26th, the day after Christmas, because we sell a lot on Christmas. In fact, we will make $60 million this year. We will make $2 per pound on 30 million pounds. Same business, same formulas, same everything–$60 million bucks and it still doesn’t take any capital.

… It is a good business. Think about it a little. Most people do not buy boxed chocolate to consume themselves, they buy them as gifts—somebody’s birthday or more likely it is a holiday. Valentine’s Day is the single biggest day of the year. Christmas is the biggest season by far. Women buy for Christmas and they plan ahead and buy over a two or three-week period. Men buy on Valentine’s Day. They are driving home; we run ads on the Radio. Guilt, guilt, guilt—guys are veering off the highway right and left. They won’t dare go home without a box of Chocolates by the time we get through with them on our radio ads. So that Valentine’s Day is the biggest day.

Can you imagine going home on Valentine’s Day—our See’s Candy is now $11 a pound thanks to my brilliance. And let’s say there is candy available at $6 a pound. Do you really want to walk in on Valentine’s Day and hand—she has all these positive images of See’s Candy over the years—and say, “Honey, this year I took the low bid.” And hand her a box of candy. It just isn’t going to work. So in a sense, there is untapped pricing power—it is not price dependent.

The reason Lego is awesome and Megablocks is not has as much to do with what’s in the consumers’ mind as the product on the shelf. It’s the experience you have with Lego that makes it so amazing.

Remember the first time you played with Lego? You want to pass that experience off to someone else. No one wants to show up to a kids birthday party and announce to everyone they took the ‘low bid’ on a relatively cheap children’s toy.

Lego is a safe bet and we want to reduce uncertainty.

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“It was not what people did not know that proved their undoing; it was what they thought they knew that wasn’t so.”

Reading Time: 1 minute

Were witches losers in a reproductive game?

Speaking about the great which hunts, in Mobs, Messiahs, and Markets: Surviving the Public Spectacle in Finance and Politics, Will Bonner writes:

But there’s another sense in which the witch trials turn out to be about sex, after all. You could see them as a variation of the reproductive game, only this time not centering around the winners but centering around the losers—the kind of people it would be easy to blame if anything did go wrong somewhere.

Most witches were alienated from ordinary family life’t hey were seen as different by their neighbours; they were disliked and feared. It was easy for a housewife to imagine that the childless old woman in the shack outside her home was eaten up inside with envy and ready to do her in. Even more important, the outsiders often had land that could be grabbed if they were convicted.

… Witches were feared as plague spreaders, as poisoners, and as workers of black magic on the community. They were the losers in the reproductive game.

… And that is the problem with the neocortex. It can always find plausible reasons … cunning justifications … and impeccable logic to do what it means to do anyway, and means to do for the most senseless of reasons.

In fairness this is only part of Bonner’s explanation of the witch hunts. The other part is largely the same one Charles Mackay lays out in Extraordinary Popular Delusions and The Madness of Crowds.

It was not illiterate fools who drove the persecution of the witches. It was the bigger semi-literate fools. It was not what people did not know that proved their undoing; it was what they thought they knew that wasn’t so.

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A Simple Checklist to Improve Decisions

Reading Time: 2 minutes

We owe thanks to the publishing industry. Their ability to take a concept and fill an entire category with a shotgun approach is the reason that more people are talking about biases.

Unfortunately, talk alone will not eliminate them but it is possible to take steps to counteract them. Reducing biases can make a huge difference in the quality of any decision and it is easier than you think.

In a recent article for Harvard Business Review, Daniel Kahneman (and others) describe a simple way to detect bias and minimize its effects in the most common type of decisions people make: determining whether to accept, reject, or pass on a recommendation.

The Munger two-step process for making decisions is a more complete framework, but Kahneman’s approach is a good way to help reduce biases in our decision-making.

If you’re short on time here is a simple checklist that will get you started on the path towards improving your decisions:

Preliminary Questions: Ask yourself

1. Check for Self-interested Biases

  • Is there any reason to suspect the team making the recommendation of errors motivated by self-interest?
  • Review the proposal with extra care, especially for overoptimism.

2. Check for the Affect Heuristic

  • Has the team fallen in love with its proposal?
  • Rigorously apply all the quality controls on the checklist.

3. Check for Groupthink

  • Were there dissenting opinions within the team?
  • Were they explored adequately?
  • Solicit dissenting views, discreetly if necessary.
  • Challenge Questions: Ask the recommenders

4. Check for Saliency Bias

  • Could the diagnosis be overly influenced by an analogy to a memorable success?
  • Ask for more analogies, and rigorously analyze their similarity to the current situation.

5. Check for Confirmation Bias

  • Are credible alternatives included along with the recommendation?
  • Request additional options.

6. Check for Availability Bias

  • If you had to make this decision again in a year’s time, what information would you want, and can you get more of it now?
  • Use checklists of the data needed for each kind of decision.

7. Check for Anchoring Bias

  • Do you know where the numbers came from? Can there be
  • …unsubstantiated numbers?
  • …extrapolation from history?
  • …a motivation to use a certain anchor?
  • Reanchor with figures generated by other models or benchmarks, and request new analysis.

8. Check for Halo Effect

  • Is the team assuming that a person, organization, or approach that is successful in one area will be just as successful in another?
  • Eliminate false inferences, and ask the team to seek additional comparable examples.

9. Check for Sunk-Cost Fallacy, Endowment Effect

  • Are the recommenders overly attached to a history of past decisions?
  • Consider the issue as if you were a new CEO.
  • Evaluation Questions: Ask about the proposal

10. Check for Overconfidence, Planning Fallacy, Optimistic Biases, Competitor Neglect

  • Is the base case overly optimistic?
  • Have the team build a case taking an outside view; use war games.

11. Check for Disaster Neglect

  • Is the worst case bad enough?
  • Have the team conduct a premortem: Imagine that the worst has happened, and develop a story about the causes.

12. Check for Loss Aversion

  • Is the recommending team overly cautious?
  • Realign incentives to share responsibility for the risk or to remove risk.

If you’re looking to dramatically improve your decision making here is a great list of books to get started:

Nudge: Improving Decisions About Health, Wealth, and Happiness by Richard H. Thaler and Cass R. Sunstein

Think Twice: Harnessing the Power of Counterintuition by Michael J. Mauboussin

Think Again: Why Good Leaders Make Bad Decisions and How to Keep It from Happening to You by Sydney Finkelstein, Jo Whitehead, and Andrew Campbell

Predictably Irrational: The Hidden Forces That Shape Our Decisions by Dan Ariely

Thinking, Fast and Slow by Daniel Kahneman

Judgment and Managerial Decision Making by Max Bazerman

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Evidence-based tips for Valentine’s

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Need to woo a partner in time for Valentine’s? Follow these simple, evidence-based instructions for boosting your irresistibility.

When asking a lady for a dance or for her number, your chances will be improved by lightly touching her on the arm. Try not to do it in a creepy way.

Use mimicry, bodily and verbal. Use mimicry, bodily and verbal (see what I did there?)

If you’re male, try to make yourself look taller and vice versa for women.

Hire a sports car, if you’re a man, but don’t bother if you’re a woman. Both sexes should avoid Toyotas – that’s a joke, please don’t sue, they’re lovely cars. 

When flirting with a man, use direct, no-nonsense chat up lines rather than the subtle or witty approach. Men are very easily confused.

When wooing a woman, use chat-up lines that demonstrate your helpfulness, generosity, athleticism, ‘culture’ and wealth. Don’t bother with jokes, empty compliments and sexual references. This ought to do it – ‘Hey gorgeous, sorry I’m late: the opera over-ran, then I had to race to my neighbour’s to help carry her piano upstairs – the one I bought her as a moving-in present’.

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If all else fails, impress them by telling them you read Farnam Street.

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Robert Cialdini on the Best Persuasion Technique for Job-Seekers

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The Monitor spoke with Robert Cialdini, who wrote the now infamous Influence: The Psychology of Persuasion, about his work and its influence.

At one point in the interview, Cialdini talks about the best way job-seekers can use persuasion to help them land a job.

Consistency is a good weapon of influence in job-hunting — the idea being that if you make a public statement, there are strong pressures to stay consistent with that, both internal and external. Let’s say you’ve got a job interview, and you know that you’re among a variety of candidates. Say something like, “I’m very pleased to be here, and I look forward to giving you all the information you’d need to know about me, but before we begin, would you mind telling me why it is that you selected me to interview.” And let them speak. Let them, in a public, active way, describe your plusses. And they will spend much of the rest of the meeting validating what they are on record as having valuing about you, because people want to stay consistent with what they’ve previously claimed. And you’re entitled to that. Why be in the dark?

In his seminal book on the topic, Influence: The Psychology of Persuasion, Cialdini went undercover to learn the tricks mastered by used-car dealers and Fortune 500 executives alike, bringing persuasion research to psychology’s forefront. Cialdini also co-authored a how-to guide, Yes!: 50 Scientifically Proven Ways to Be Persuasive.

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Scientifically Proven Ways to Increase Tips in the Service Industry

Reading Time: 4 minutes

Tipping is a $40 billion dollar industry in the United States. Yet from the traditional economic perspective, which sees us as rational agents operating in our own interest, tipping waiters, barbers, taxi drivers and other service workers is crazy.

Many food servers depend on tips to make their living. Understanding the variables that affect tipping behavior can make a huge difference on income. Of course, a lot of the variables that influence tipping behavior are outside the servers’s control. For example, customers tend to leave larger tips when the weather is pleasant, when there is desirable background music, and when the restaurant is elegant or in an urban area. Food quality has a large impact. Research also suggests that tipping behavior is affected by customers’ characteristics, including size of the dining party, amount of alcohol consumed, customers’ gender and ethnic background, and method of payment.

However, research also indicates that servers can control some variables that influence tipping behavior.

If you’re a food server try—and if you’re a customer watch out for—the following:

Have your restaurant prime the customer with examples of what a tip would be at 20%
This study examined the role of gratuity guidelines on tipping behavior in restaurants. When diners were finished with their meals, they were given checks that either did or did not include calculated examples informing them what various percentages of their bill would amount to. Results indicated that parties who received the gratuity examples left significantly higher tips than did those receiving no examples. These results and their implications are discussed.

Introduce yourself by name
…wait staff who introduced themselves by name received an average tip of $5.44, or 23 percent of the total bill, and those who used no name were tipped on average about $3.49, or 15 percent of the total bill.

Squat when you first get to the table
Walters should squat down next to the table upon their first trip to the station, Lynn recommended, based on his study at an unnamed casual Mexican restaurant in Houston. Those who squatted received an average tip that was 20 percent higher — $6.40 as compared with $5.18 — than those who stood on their initial visit to the station.

Smile
Servers should give their customers a large smile — with mouth open and teeth showing — while they work.

Approach The Table Often
Walt staff should visit their tables more often, Lynn suggested as another technique, based on a study conducted in the 1970s at a Chicago steak house. Those who approached their tables — just to check up on the customers and not to deliver anything — two times or more received average tips that were 15.6 percent of the total bill, while those who approached the table only to deliver something or take something away received tips that were on average 13.8 percent of the total bill.

Touch your customers
He recommend they touch them lightly on their shoulders when delivering the bill or when returning with change or a credit card. His study for the technique was conducted at a Bennigan’s in Houston. Those who touched their customers for an average of two to four seconds received an average tip of 18 percent, or $3.20, of the total bill, and those who didn’t received a 12-percent average tip, or $2.52.

Give your customers something extra, like a mint
Another controversial technique Lynn recommended is for wait staff to give their customers after-dinner mints, based on his study at a Philadelphia restaurant. Servers who left their customers mints received tips that were on average about 28 percent, or $5.98, of the total bill, and those who left no mints received average tips of 19 percent, or $4.64, of the total bill.

“The technique didn’t work at steak houses with a [per-person] check average over $30,” Lynn said. He added that leaving mints for customers at upscale restaurants seems to have no impact on tips. “But at casual restaurants, it does increase tips,” he insisted. “It works because customers got something free, so they want to repay their servers.”

Compliment your customers
The present study examined the role of ingratiation on tipping behavior in restau- rants. In the study, 2 female food servers waited on 94 couples eating dinner, and either complimented or did not compliment the couples on their dinner selections. Results indicated that food servers received significantly higher tips when complimenting their customers than when not complimenting them. These results and their implications are discussed.

Other ideas? Write “thank-you” or simply draw a smily-face on the bill (to create a likeable impression); Print a picture of someone smiling on the bill, or the American Flag (something most people would associate with happiness); Make paying by Visa the default; If you’re a guy give the bill to the woman and if you’re a woman give the bill a guy; and Tell customers the weather is supposed to be nice tomorrow (take away a subconscious worry).

If you’re interested in learning more about gratuity’s try reading Keep the Change: A Clueless Tipper’s Quest to Become the Guru of the Gratuity. The best book out there on working in a restaurant is Kitchen Confidential.

Sources
– Ingratiation and Gratuity: The Effect of Complimenting Customers on Tipping Behavior in Restaurants
– Tip gratuity scale in server’s favor with simple techniques
– http://www.allacademic.com/meta/p_mla_apa_research_citation/3/0/7/3/0/p307300_index.html

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