## Because we infer things that aren’t

A reader wrote to Dan Ariely about a panhandler who asked him for 75 cents. His question was

Do you think the 75-cent request could be a “market-tested” amount, one that yields a higher overall level of “donations” than asking outright for a buck or more?

The panhandler could be trying to make a unique request in order to separate himself from the competition. But my guess is that you were more willing to give him money because you inferred things from the specificity of his request.

Yes, we infer things like he was using market-tested pricing just like gurus infer business wisdom from any thing they run into.

And if you are asking, “what about being different?” – it only works if it is not a gimmick that anyone can copy. If one person wears stilts in a stadium he can see better but if everyone else does that it does not work.

So next time you see a business with its unique pricing beware of what you infer over what it really is.

## Variations of the World Famous Hershey’s Experiment

There is one behavioral economics experiment that has been in blogs and mainstream media more than any other, it is the Hersheys and Lindt experiment done by Dan Ariely, Professor at Duke and author of Predictably Irrational. It is quoted as unassailable evidence by every article extolling the virtue of the so called “freemium” model.

For those who are fortunate enough to not know about this magical experiment and its far reaching implications on pricing here is a quick summary,

In a busy  food court, where people already come everyday to make lunch purchases, Ariely and team did two tests. Tests were conducted at the check out counter, when customers pay for the food. I will let Ariely summarize the rest

in one trial of one study we offered students a Lindt Truffle for 26 cents and a Hershey’s Kiss for 1 cent and observed the buying behavior: 40 percent went with the truffle and 40 percent with the Kiss. When we dropped the price of both chocolates by just 1 cent, we observed that suddenly 90 percent of participants opted for the free Kiss, even though the relative price between the two was the same. We concluded that FREE! is indeed a very powerful force.

This finding from one trial, the 90% conversion is enough for most. And we are not stopping to do the expected value math on giving a free product to 90% of customers.

Success and popularity of two startups, Dropbox and Evernote, add to this madness. I wrote about cognitive biases in making a case for freemium and making blanket statements like, “free is free marketing”. Even now we see articles that base their case for giving our products away for free on Hershey’s.

Much has been written about the Psychology of Free. Two books that looked specifically into the subject are “Free” by Chris Anderson and “Predictably Irrational” by Dan Ariely. Putting it simply, Free is an emotional hot button that immediately reduces the mental barriers for the customer. Free makes people think that they have “nothing to lose” since many ignore time as an investment.

How relevant is one trial to every possible pricing situation out there? It is not enough to say we are in San Diego just because we see white sandy beaches. What are the variations of the experiment that model the webapp and iOS app worlds? Since they are not looking for it, let us look at other variations of the experiment and see how solid and relevant that one trial is for basing pricing model of web startups. (Consider these experiments in the context of thousands of webapps and iOS apps out there)

1. Run the  experiment with Lindt and with a no name brand of chocolate offered free. Will free win over Lindt’s brand and value proposition?
2. Run the experiment with Lindt and  Hershey’s and 20, 50, or  100 different no name brands. What will a no name brand’s share be compared to Hershey’s?
3. Run the experiment with Lindt and 20, 50, or 100  no name brands.  Will the 90% conversion still hold?  What will each brand’s share be?
4. Run the experiment with Lindt and some thing else that is not labeled as chocolate. Test participants should not be told what that second item is. It is just that it was offered free. Will the mystery item find bigger taking than a product whose value proposition is clear?
5. Lastly, don’t run the experiment in a food court where there are already people. Run it in the middle of no where. Will free still mean free marketing?
In all these cases will free still be the, “emotional hot button that immediately reduces the mental barriers for the customer and make people think that they have ‘nothing to lose’ since many ignore time as an investment”?
How is free means free marketing when you are one of many free offerings (case 3 above)?

## Wi-Fi In Airplanes – Stuck in \$0 Reference Price

Update 2/1/2010: Southwest planning to offer Wifi (for a price). It definitely will help them to read this.

How much is getting Internet connectivity at 30,000 feet above sea level and while moving at 240 miles per hour worth to you?  How much are you willing to pay for it? How much are you willing to pay for WiFi connection in an airplane?

I predict that most will say different numbers  for these questions, progressively decreasing from a non-zero number to none other than \$0 for the Wi-Fi question. The Wall Street Journal writes on the uptake of Wi-Fi in airplanes:

“There’s a very substantial decline in passenger usage the minute you start charging for the service,” said Michael Planey, a consultant specializing in in-flight passenger technologies. “It really begins to invalidate the model on which this service is being built for the next 10 years.”

Alaska Airlines found that even at a price of \$1 lot fewer people used its service then when it was free. So the demand curve for this service will look something like the one shown here, dropping abruptly at a price just above \$0.

Having connectivity is definitely of value to customers, some segments valuing it more than the others. But why are customers unwilling to pay for this value? The answer once again is the same one I showed in my Airline Unbundling study – Reference Price. Reference price is the price a customer used to paying for the service or expects to pay despite the value they get.  The purchase context does not matter to the customers, it is the price for the service. Everywhere they go, from coffee shops to hotels they received free Wi-Fi. So their reference price is \$0.

The airlines should not have made this offer free to begin with but they need to do that for testing. They should have recognized this reference price effect and should have first worked on improving it before charging for it. One option I showed that worked in the unbundling study is introducing options, one high priced and another low priced. Presence of high priced option helps to improve reference price and hence customer acceptance of lower priced option. The airlines could have introduced a guaranteed speed, unlimited bandwidth version and a limited speed, limited bandwidth version at two different price points.

Another takeaway in this story is how a marketer can destroy future profit by setting a low (or \$0) reference price. I am afraid however that this story is going to be  used by “Free” proponents like Mr. Chris Anderson. A case will be made about why free is the future and once again a reference will be made to the attractiveness of  \$0 price, quoting Prof. Ariely’s work. I would like you as a marketer to be aware of the reference price effect and find ways to charge for this service that adds value to customers.

It is true that providing Wi-Fi at 30,000 feet is a high fixed cost operation and once you rolled out the service your costs are sunk and your marginal costs are \$0. But before you made the business case for the investment the costs were not sunk and you should have made an analysis how much you expect to charge and how many customers would pay. You should not have invested with the hope that you will first get the customers and then figure out how to monetize it.

The net is, if the service is of value to customers then you should charge for it. What the customers are willing to pay for the service is not commensurate with value but lower because of the reference price. Focus on improving the reference price to capture a fair share of the value you add.

## Survivorship Bias and Other Flaws in Anderson’s FREE

[tweetmeme source=”pricingright”] In his new book, FREE: The Future of a radical Price, Mr. Chris Anderson supports his arguments with many examples of businesses that used razor-razor blade model, advertising model, and free + premium model. The last few pages of his books are just a list of examples of businesses that are successfully implementing, according to him, what he calls the “freemium” model. Are examples enough to state absolutes like “the future of a radical price”?

Even if that is enough, Mr. Anderson lists only those businesses that seem to have made it, at least for now, and does not include those businesses that tried many of the free models and failed. That is the classic survivorship bias. If we restrict just to the new media businesses that Mr. Anderson focuses on, there are many instances of ventured that went under. Even the small subset one can find in TechCrunch’s  “DeadPool” is a daunting number.

Even among those businesses selected,  the time horizon is too short to say they are successful or will deliver long term profit growth. Mr. Anderson uses  a different metric, “uptake among customers” rather than profit to measure their success. His careful choice of metric is not by accident, it is about cleverly framing the argument and directing his readers and listeners to focus on a metric that is irrelevant but supports his argument.

The next problem is confusing correlation with causation. Among the blockbuster success stories he quotes like YouTube, he attributes the customer uptake to the free model. He uses  Prof. Dan Ariely’s  Hershey’s experiment to substantiate this claim on causation. You can see Prof. Ariely’s comments on people using his experiment in his blog. In his Hershey’s  experiments, the claims were based on experiments that used control groups and treatment groups. But Mr. Anderson makes his claim based on YouTube being free.

Businesses, before jumping on Mr. Anderson’s far-reaching conclusions, should ask about his decision making process and analyze their own business based on hard data. As professors Pfeffer and Sutton point out in their book Hard Facts, the difference between an academic (who is much maligned by the new media Gurus) and a self proclaimed Guru is  that an academic gives you an open system of decision making where as a Guru gives you a closed system that talks in absolutes, ignores evidence, focuses just on benefits and minimizing the drawbacks of their recommendation.

## The Most Discussed Free Experiment

Update: An article in The Economist (11/27/2009) adds some evidence to the hypothesis stated in this article.

There is one behavioral economics experiment that has been in blogs and mainstream media more than any other, it is the Hersheys and Lindt experiment done by Dan Ariely, Professor at Duke and author of Predictably Irrational. The news presence comes thanks to Mr. Chris Anderson who used it in his latest book, Free, to make his case about the attractiveness of the \$0.00 price.

We already know that from Prof. Ariely’s book and we also know that Mr Anderson leaves out the part of the book (and research) in which Prof Ariely warns about the anchoring effects of initial low price. Now let us take the discussion one step further. The Hershey’s experiment found that when offered free, more people preferred Hershey’s than they did when offered at 1 cent. (You can read Predictably Irrational for the details).

Suppose if there had been a third stage to this experiment, this time in addition to offering Lindt  at a small price and Hershey’s at \$0.00, there were also other candies (comparable to Hershey’s kisses) offered at \$0.00 as well. Then what do you think will be the share of the different free offerings?  For sure, the market will be fragmented. In addition, I hypothesize that(which needs experimentation to verify)

1. more people will switch back to Lindt
2. of the free versions, the name brand versions will end up garnering a larger share
3. most of the free versions will find very few to no takers

The problem is when you give it away for free and there are many free offerings from your competitors, customers will start worrying about their opportunity cost and go back to priced versions.  The fact that some offerings are not free  signal value to customers and reduces their risk of trying.

Now where does that leave the “long tail” free offerings?