ARTICLE: Sarah Freitag

How to use loss aversion bias to evoke more meaningful user feedback on your EdTech product

As a product owner, you know that your users’ feedback is the most valuable asset in your arsenal. After all, your EdTech product can only succeed to the extent that it actually meets your users’ needs. And the more deeply you understand your users — their desires, mental models, requirements, and preferences — the more perfectly you can tailor your product to suit their taste. 

So it’s imperative that you draw out frank, unbiased, and uncensored feedback in every round of user testing. One surefire way to do that? By leveraging the principle of loss aversion. Here’s how. 

What is Loss Aversion? 

Nobody likes to lose. But the theory of loss aversion goes further than simply pointing out this obvious fact. It suggests that we actually hate losing far more than we like winning. 

Put in real terms, the loss aversion bias predicts that the pain of losing $100 will be far greater than the pleasure you might take in gaining $100. In fact, some studies suggest that losses are twice as powerful, psychologically speaking, as equivalent gains. 

The term “loss aversion” was coined by researchers Amos Tversky and Daniel Kahneman, who found that people would rather accept a small but certain reward over a mere chance at a larger gain. In other words, as an extension of wanting to avoid loss, we prefer certainty. (This same principle can help explain users’ loyalty to particular tools.)  

As a thought exercise, consider this: Let’s say you’re buying a product online — one that you’ve purchased before. In one scenario, you unexpectedly get a $5.00 discount. You probably feel pleasantly surprised. But the intensity of your pleasure is most likely mild and fleeting. Now let’s say that rather than a $5.00 discount, you’re hit with an unexpected $5.00 fee. The amount is nominal, but your displeasure? Probably pretty strong. In fact, it may be enough for you to abandon your purchase altogether. This simple example illustrates that losing something you already have elicits a much more intense response than gaining the same exact thing would. 

As you might expect, loss aversion plays an important role in how people make decisions, especially when it comes to weighing risks. In particular, it helps to explain why we tend to be risk-seeking when maximizing gains and risk-averse when minimizing losses. 

Putting Loss Aversion to Work to Build Better Data in UX Testing 

It’s important to be mindful of loss aversion in the context of user testing. This is true for two reasons. The first is that UX researchers can actually leverage loss aversion as a way to tease out more meaningful feedback from users. And the second is that loss aversion can sometimes pop up as an unexpected bias in your research that must be recognized and corrected for. Let’s look at each one in more detail. 

Leveraging Loss Aversion to Get More Meaningful User Responses 

User testing often involves showing your users a prototype and (in more sophisticated terms) asking if they like what they see. 

If you present your product or feature in user testing session as an option users can choose to utilize (or not), they are more likely to perceive the product or feature in generally rosy terms. Which means that they are less likely to think deeply about what does and doesn’t really work for them. 

In instances such as these, you can elicit more valuable responses by leveraging loss aversion. As we’ve already established, people’s responses intensify when they are faced with losing something they already have and value. In his popular product market fit survey, business consultant Sean Ellis takes advantage of this exact principle by asking customers how disappointed they would be if they could no longer use a given product. 

In addition, when people are given the option to adopt a new product over something they are familiar with, they are more likely to stick to what they know (even if it’s not perfect). This tendency can be attributed to inertia — it takes a lot of energy to learn a new system — as much as loss aversion. 

Rather than asking users to give their feedback about your product in a vacuum, ask them how they would feel if they were forced to use your product instead of the tools they currently use. 

By considering your product in light of an associated loss, your test users are sure to assess it more carefully — and more critically. As a result, you stand to gain more meaningful feedback about how your test users actually feel about your product, what excites them, and what fails to meet their needs. 

If your test users tell you that they’d be excited to give up their existing product to use your product, that’s a huge win. It means your product offers so much value that it manages to clear the loss aversion hurdle. 

Note, however, that this approach should be used carefully. It has the potential to introduce bias in some scenarios, and it certainly doesn’t make sense all the time. The best time to leverage loss aversion in this way is during early-stage user tests, when you are trying to determine product market fit or compare a product to an equivalent alternative. You can also use this approach to help define an MVP by asking users something to the effect of, “how upset would you be if this feature were to be cut?” 

Identifying Loss Aversion Bias in Your Data 

UX researchers can intentionally wield loss aversion to their advantage. But loss aversion can enter the testing environment uninvited, as well. 

For example, let’s say you’re working on a redesign for an existing product. You come up with two versions. One is a subtle refresh of your existing product. And the other is a more radical reworking of your product, complete with new workflows. If all of the users you recruit for testing are existing customers, don’t be surprised if you discover that the majority of them claim to prefer the refresh over the full redesign. 

To rule out loss aversion bias — in this case, the possibility that your existing customers are reacting more to the loss of something familiar than a true preference for one version over the other — you’ll need to include test users who have never before used your existing product. Of course, both sets of user groups are valuable. But your “fresh” users may give you a more balanced and objective idea of which design is truly the better fit. 

Depending on the situation, loss aversion can be a UX researcher’s best friend or worst foe. By knowing what to look for — and how to wield loss aversion to your advantage — you can draw out more meaningful user feedback. With your users’ candid opinions as fuel, you can build a product that your customers would absolutely hate to lose.

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    Sarah Freitag

    As Director of UX Research, Sarah draws on her deep understanding of EdTech users and her background in research, design and business strategy to enable our clients to make confident decisions that result in products that solve real needs and create demonstrable impacts on their business’ bottom lines. Like her design-side counterpart at Openfield, Sarah is responsible for fostering collaboration, team development and for bringing new strategic initiatives and methodologies that allow our company to stay ahead of the curve of what EdTech users truly need to realize higher levels of learning and teaching success. Sarah is an avid reader and an adventurous explorer. Highlights from her favorite travels include Morocco, Peru, Italy, Denmark and France. With the recent pandemic-induced reduction in travel, she makes it a point to fulfill her wanderlust with another one of her passions, cooking and baking, by experimenting with recipes inspired by cultures around the world.

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