This coupon (which would only cost you money if they return to purchase more items) would be more appealing and more effective than a sweepstake for $1000 - a reward that is large, but highly unlikely. If you offer a reward for users who write a product review, for example, consider giving all reviewers a coupon for 10% their next purchase. To persuade users to take an action, consider using the certainty bias to your advantage: people would rather accept a small but certain reward over a mere chance at a larger gain. The opposite is true when dealing with certain losses: people engage in risk-seeking behavior to avoid a bigger loss.

We would rather get an assured, lesser win than take the chance at winning more (but also risk possibly getting nothing). People tend to overweigh options that are certain, and are risk averse for gains. We discuss each of these biases in detail below. Prospect theory explains the biases that people use when they make such decisions: Yet people largely prefer one option over the other. In both these situations, the expected utility of both choices is the same (+/-$900): the probability multiplied with the expected win. These types of behaviors cannot be easily explained by the expected-utility approach. Again, both options have equal expected values. When aiming to avoid a loss, people become risk seeking and take the gamble over a sure loss in the hope of paying nothing. Losses are treated in the opposite manner as gains. Note also that the overall expected value (or outcome) of each choice is equal. When dealing with gains, people are risk averse and will choose the sure gain (denoted by the red line) over a riskier prospect, even though with the risk there is a possibility of gaining a larger reward. However, if I asked you to choose between losing $900 and take a 90% chance of losing $1000, most of you would probably prefer the second option (with the 90% chance of losing $1000) and thus engage in the risk-seeking behavior in the hope to avoid the loss. However, when it comes to making decisions such as whether to purchase something, make a donation, or pick a level of a service, people are highly susceptible to cognitive biases, and often donвЂ™t make the logical choice.ДЇor example, what would you choose: to get $900 or take a 90% chance of winning $1000 (and a 10% chance of winning 0)? Most people avoid the risk and take the $900, although the expected outcome is the same in both cases. In the field of user experience, we often talk about how users weigh the expected utility of different alternatives to determine what action to take or where to go next. We would all like to believe that we are logical decision makers. The perceived likelihood of a major health problem is greater than the actual probability of such an event actually occurring. Even though the likelihood of a costly event may be miniscule, we would rather agree to a smaller, sure loss - in the form of an insurance payment - than risk a large expense. One of the biases that people rely on when they make decisions is loss aversion: like in the insurance example above, they tend to overweight small probabilities to guard against losses.

(Sadly, Tversky had died when the prize was awarded.) The prospect theory was proposed by psychologists Daniel Kahneman and Amos Tversky in 1979, and later in 2002 Kahneman was awarded the Nobel Prize in economics for it. Purchasing insurance plans is an excellent example of the prospect theory at work.Дefinition: The prospect theory describes how people choose between different options (or prospects) and how they estimate (many times in a biased or incorrect way) the perceived likelihood of each of these options. After much deliberation, my cat now has her own insurance coverage. This uncertainty made the decision rather difficult: I could save my insurance money and hope for my cat to remain perfectly healthy, but if a health issue were to appear I would possibly need to spend exorbitant amounts of money for treatment. Because the cat couldnвЂ™t provide any family health history, I saw the likelihood of her having an issue as an unknown: there was no way to predict when or if something could pop up and be a major expense. I recently adopted a kitten and was faced with the decision of whether to purchase pet insurance for my little fur baby.

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