Cognitive bias: the power of free

The power of free

Free delivery fees, buy one item to get the second item free, free entry fees,… many of our daily marketing offers include something free. 

The trick is obvious, widespread and has been used by merchants for centuries. But it still works. Why?

Let’s analyze this behavior from a behavioral economic point of view.

Scientific evidence

In his famous book Predictable Irrational, Dan Ariely, professor at Duke University, illustrates “the power of free” with two experiments.

In the first experiment, customers were offered either a high-quality chocolate at 0.15$ (about half its actual cost) or an average chocolate at 0.01$. Most customers decided to buy the more expensive but tastier chocolate.

Now, if customers were offered the same chocolates, but at a price of 0.14$ for the high-quality chocolate and for free for the average chocolate, most customers will change their mind and prefer the free chocolate.

This change of behavior cannot be explained with a traditional economic model. If you are ready to pay 0, 14$ more for the high-quality chocolate in the first case, why would you change your decision in the second case?

To check that these results were not due to convenience (not having any change, having to hunt around in a purse for coins, etc.), the experiment was repeated in a cafeteria food line where the cost of the chocolate could be easily added to the total purchase. Results were similar.

“Most transactions have an upside and a downside, but when something is FREE! we forget the downside. FREE! gives us such an emotional charge that we perceive what is being offered as immensely more valuable than it really is.” Dan Ariely

Prospect Theory and the power of free

The rational is that our perception of quantity is biased. 

First, the smaller the amounts, the more sensitive we are to their difference. We are very sensitive to the difference between 0$ and anything, even 0.01$. We are less sensitive to a difference between 0.14$ and 0.15$. We are indifferent between buying a house at $100.000,01 or $100.000.

Second, we are more sensitive to losses than to gains. More precisely, we are on average twice more sensitive to losses than to gains. It means that we will be twice more sensitive to paying 0.01$ (a loss), than to win 0.01$. This bias is called loss aversion.

You have purchased a meal for 20$ but delivery fees are free only if your order 25$? You will buy the overpriced coke at 5$ to “win” the free delivery…

These misperceptions have been modeled in the famous Prospect Theory by Daniel Kahneman and Tversky. In this model, our perception of gains and losses is captured by a S-shape utility function. The larger the gains are, the less sensitive we are to their increase. The larger the losses are, the less sensitive we are to their increase too. Moreover, the utility function is slightly deviated in the loss domain to capture the fact than we are more sensitive to losses than to gains (on average, twice).

The S-Shaped Utility Function of Prospect Theory | Download Scientific  Diagram