Loss Aversion

Loss Aversion is the recognition that for most humans, losses are more salient than gains, leading to non-optimal behaviours and decision making directed towards avoiding the feelings/emotions/affect associated with loss. This is related to the negativity bias (for an example, see: Molins et al., 2022), which is a more general concept that encompasses various domains. For example, if winning $100 would generate 100 points of happiness, loss aversion suggests losing $100 would reduce happiness points by more than 100. Kahneman and Tversky (1979; 1992) famously described loss aversion in respect to prospect theory (which garnered a Nobel prize in 2002). Prospect theory examines how individuals make decisions that involve risk, and argues that due to loss aversion, individuals will choose certain decisions (e.g. $450) even when an alternative choice has higher expected value (e.g. 50% chance of winning $1000 and 50% chance of getting nothing, which has an expected value of $500). Similarly, individuals might choose to take huge risks if it involves preventing them from taking a loss. Tversky and Kahneman (1991) also extended loss aversion to decision making that does not involve risks, suggesting losses impact consumer preferences more so than gains. For example, they cite evidence for the endowment effect, whereby individuals demonstrate differences between the minimum price they would be willing to sell a good they own (e.g. $1000 for a piece of art) and the price that they would be willing to pay for the same item (e.g. $600 for that piece of art). Further, Tversky and Kahneman (1991) suggest that loss aversion also helps explain the status quo bias whereby individuals prefer to preserve the status quo rather than adopt change and use the status quo as a positively valued reference point to judge losses and gains.

Various meta-analyses (Brown et al., 2021; Neumann & Böckenholt, 2014; Walasek et al., 2018) have supported loss aversion, suggesting that it should be considered when making business decisions. Further, Sokol-Hessner and Rutledge (2018) provide a great review of the neural basis of loss aversion, including a useful chart summarizing previous studies on the mechanisms involved, which suggest loss aversion has a biological basis. However, it is also important to recognize that the impact of loss aversion differs quite a lot across studies, suggesting that context is also an important consideration. For example, Gal and Rucker (2018) provide evidence that many loss aversion studies fail to demonstrate any significant effects from loss aversion, and thus loss aversion may not be as universal as many believe it to be.

Loss Aversion Considerations in Marketing and User Experience Design

Assuming that losses are more impactful on behaviour and salient than gains, you want to ensure that you are framing situations that involve losses and gains in a way that benefits your business. For example, if you are providing discounts to customers you could reframe “Spend $50 and get $5 back” as “Spend $50 and save $5.” Similarly, if you believe your business will help individuals save money (e.g. a discount grocery store) you can frame your product/service as preventing loss (e.g. “Don’t waste $5 on a banana”). Further, you want to make sure that any sales you hold involve a sense of urgency (e.g. time constraints), and you want to avoid excessive sales (e.g. a new sale every week). By only having sales once in a while, the feelings associated with missing out (a loss) are enhanced. If you run an app or are a software as a service developer, you want to make sure you aren’t removing features or making your product/service seem like it is offering less as time goes on. Companies often try to simplify their user experience, or cut out unprofitable branches of their business, but this creates negative feelings towards their brand. In general, you want to ask yourself what aspects of your business/brand involve losses and gains, and consider how loss aversion may affect perception and decision making within those domains.

Practical Examples of Loss Aversion

Loss Aversion through Urgency in eCommerce

One popular way to take advantage of loss aversion on eCommerce websites is to use a countdown timer in respect to sales/deals. It’s important that these countdown timers are believed to be legitimate, and justified (e.g. a Christmas sale). Visitors will feel that not making a purchase within the allotted time will cause them to lose out. Further, you can track users who add items to their cart but never complete a purchase (e.g. abandoned carts) and reach out to them with an additional timed discount. By providing them with this extra discount, you are taking advantage of gratitude and reciprocity, increasing the chance that they will return to your website to purchase the items. Additionally, you can release limited-time items and create a fear of missing out (FOMO). For more information on the nuances of this strategy please visit our page on scarcity and read about time scarcity.

Loss Aversion through Scarcity in eCommerce

Creating scarcity (whether true scarcity or artificial scarcity) can engage loss aversion and increase sales/conversions. Many smaller eCommerce startups do this through limited drops. For example, they might release 100 t-shirts with a specific design on them, and mention that when they are sold out, they won’t return. Another way to engage scarcity is to allow users to add items to a wish list and send them an email whenever an item on that wish list is running low. In this situation the user doesn’t feel that you are pressuring to buy the item, but rather feels that you are doing them a favour by letting them know the item is almost sold out. But due to loss aversion, they are likely to feel pressure to purchase the item while it is still available, as they aren’t sure if it will come back in stock Further, due to the endowment effect, by having the item on their wish list they may already feel some sense of ownership or connection to it, making them less willing to risk losing the item. Similarly, many eCommerce websites show the remaining stock of each item. However, some artificially diminish the stock so all items look like they are selling fast. This engages loss aversion as customers don’t want to miss out on an item they want. Further, this takes advantage of social proof and acts as an indication that others also desire the product. You can enhance this by having messages on websites saying things like “Get it before it’s gone.” However, it is important that you consider advertising laws in your country to ensure this is not viewed as false advertising. Further, if a customer realizes/guesses/assumes you are using this tactic, they will likely feel negatively about your brand. For more information on the nuances of this strategy please visit our page on scarcity.

Leveraging Point Systems and Branded Currency

Providing customers with points or branded cash (e.g. fake cash they can only use at your store) each time they make a purchase can help increase repeat purchases. Individuals who have these points or cash will want to use them, else they feel as though they are losing money. This is especially salient if the cash is designed to look like real currency. For example, Canadian Tire money has at times been described as the most popular loyalty program in Canada (“Canadian tire money”, 2001). To encourage use of these points/currencies and make loss aversion more salient, time-limits can be used. For example, Hot Topic (An alternative fashion clothing store) often gives out coupons called “Hot Cash” which need to be used between certain dates. By calling these coupons “cash,” it makes customers feel as though they are losing money if they don’t use them, and provides a strong incentive to go to the store during the sale period. Points can also be used to keep customers subscribed to an email list or loyalty program. If the loyalty program has an annual fee, customers can be informed of the risk of losing their points if they don’t renew. This works alongside the idea of sunk costs to draw customers back to the store on a regular basis.

Research Example of Loss Aversion

The Asian Disease Problem

(Note: this study is also described on our Framing page)
The most famous example of how loss aversion influences our decision making comes from a series of studies by Tversky and Kahneman (1981). In one of these studies they split participants into two groups. Both groups were told to imagine the U.S. was preparing for a disease outbreak which could kill 600 people. The first group was asked to choose between Program A and B. Program A would save 200 people, while program B would have a 33.33% chance that 600 would be saved, but a 66.66% chance that no one would be saved. In this scenario, 72% chose option A, where 200 people would be saved. They then presented the second group with reworded (reframed) versions of both programs. Program C was described as leading to 400 people dying, and program D was described as a 33.33% chance nobody would die, and a 66.66% chance that 600 would die. Here, 78% of people chose program D. Program A and B were identical to C and D from a mathematical perspective in respect to life and death. But because group 1 saw options framed as gains (saving lives) and group 2 saw options framed as losses (people dying) participants from each group on average made different decisions. A loss frame led to a willingness to take greater risks (to avoid a loss), whereas a gain frame led individuals to stick with certainty. Thus, if you want customers to take risks, consider framing your requests or marketing copy in terms of potential losses, rather than gains. However, keep in mind that this tactic is likely very context-dependent, and be sure to A/B test to see which frame works best for your unique situation.

Works Cited

Brown, A. L., Imai, T., Vieider, F., & Camerer, C. (2021). Meta-analysis of empirical estimates of loss-aversion. CESifo Working Paper, 8848. http://dx.doi.org/10.2139/ssrn.3772089 (note: this has yet to be peer reviewed and published as of the last update to this page)

Canadian tire money: Most popular reward program. (2001, May 08). CBC News. https://www.cbc.ca/news/canada/canadian-tire-money-most-popular-reward-program-1.299620

Gal, D., & Rucker, D. D. (2018). The loss of loss aversion: Will it loom larger than its gain?. Journal of Consumer Psychology, 28(3), 497-156. https://doi.org/10.1002/jcpy.1047

Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47, 263-291. https://doi.org/10.1017/CBO9780511609220.014

Kahneman, D., & Tversky, A. (1992). Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk and Uncertainty, 5, 297-323. https://www.jstor.org/stable/41755005

Molins, F., Martínez-Tomás, C., & Serrano, M. A. (2022). Implicit negativity bias leads to greater loss aversion and learning during decision-making. International Journal of Environmental Research and Public Health, 19(24), 17037. https://doi.org/10.3390%2Fijerph192417037

Neumann, N., & Böckenholt, U. (2014). A meta-analysis of loss aversion in product choice. Journal of Retailing, 90(2), 182-197. https://doi.org/10.1016/j.jretai.2014.02.002

Sokol-Hessner, P., Rutledge, R. B. (2018). The psychological and neural basis of loss aversion. Current Directions in Psychological Science, 28(1), 20-27. https://doi.org/10.1177/0963721418806510

Tversky, A., & Kahneman, D. (1981). The framing decisions and the psychology of choice. Science, 211(4481), 453-458. https://doi.org/10.1126/science.7455683

Tversky, A., & Kahneman, D. (1991). Loss aversion in riskless choice: A reference-dependent model. The Quarterly Journal of Economics, 106(4), 1039-1061. https://doi.org/10.2307/2937956

Walasek, L., Mullett, T. L., & Stewart, N. (2018). A meta-analysis of loss aversion in risky contexts. SSRN. http://dx.doi.org/10.2139/ssrn.3189088 (note: this has not been peer reviewed and published as of the last update to this page)

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