Behavior Change

Depending on the person’s goals, these changes can be beneficial or not. In the context of fields like nudging and choice architecture, behavior change is typically talked about in the context of some kind of intervention - for example, helping people to quit smoking, exercise more or save money for retirement.

At the same time, psychologists use behavior change to describe any kind of alteration in a person’s actions, which can happen for lots of reasons (e.g. a mental health issue, changes in the physical environment, social pressure, etc.).

That said, the context we’re interested in is the nudging kind of behavior change - how we can understand people’s goals and help them get there more effectively.

This term was coined by Richard Thaler and Cass Sunstein in their 2008 book, Nudge: Improving Decisions about Health, Wealth and Happiness. The idea behind their term was to help people reduce ‘errors’ in decision-making that arise because of a set of very predictable biases - in other words, to nudge them toward decisions and actions that are in their best self-interest. Of course, deciding what’s in a person’s interest is no walk in the park, and this is why choice architecture, and the underlying “libertarian paternalism” philosophy that Thaler and Sunstein promote, have received some criticism.

Some basic strategies to improve decision-making are things like:

• Making better choices more salient - for example, the famous example of putting healthier eating options at eye level on a menu board. An experiment in a New York cafeteria found that elevating the placement of fruits and salads increased their sales by 25%.
• Reducing choice overload by limiting the number of alternatives a person has to explore - for example, the other famous example of reducing the number of jams. A study conducted in a gourmet market demonstrated that customers exposed to 24 varieties of jam were ten times less likely to purchase than those who encountered only 6 varieties.
• Using defaults to leverage the fact that people tend to take the path of least resistance, particularly when faced with tough decisions - for instance, automatically enrolling employees in retirement savings plans, but allowing them to opt out if they choose. Studies show that default enrollment can increase participation rates dramatically, often exceeding 90%.
• Simplifying information to help people understand their choices better - for example, redesigning electricity bills to make costs and savings clearer can lead to more informed and better decisions about energy consumption.
• Providing immediate feedback - this can help people understand the consequences of their choices in real-time. For example, displaying real-time fuel consumption in cars can lead drivers to adopt more fuel-efficient driving habits.
• Incentivizing desired behaviors - for example, offering small financial rewards for using less energy during peak hours has been shown to reduce overall electricity consumption significantly.

Quick ethics sidenote: at TDL, we subscribe quite strongly to SPICE: Socially-conscious, Pragmatic, Inventive, Catalytic, Evidence-based. We wouldn’t be worthy of the S if we didn’t mention the dark side of all of this. Many behavior change efforts are there to understand what people want to achieve and empower them to do it. But, in other cases, behavior change can be coercive - i.e. pushing people toward something they do not actually want, or that may even be harmful to them (e.g. a gambling website). We’re not here to pass judgment but suffice it to say that the research which all of this is grounded on is generally bound by very strict ethical guidelines - guidelines which ideally should exist in industry as well, but hey, lots of things ‘should’.

Okay, back to our regular programming. While basic strategies like the ones we listed above (salience, defaults and so on) are a good starting point for trying to design interventions,many situations called for a more complex approach. For example, while changing a retirement savings account from opt-in by default to opt-out by default might increase participation drastically, you may need a more sophisticated approach to increase the amount of contributions. This is where behavior change frameworks come into play - they allow you to really dissect a target behavior (e.g. increasing contributions) into lots of small elements (e.g. social influence, salience, loss aversion, etc.) that can then help you design a single intervention that is jam-packed with the right combination of ‘basic’ ingredients. In essence, behavior change frameworks allow you to go from the raw ingredients to a complex cooked meal.

Frameworks like COM-B, EAST and MINDSPACE essentially allow applied behavioral scientists (those people who do behavior change projects) to clearly diagnose a problem and design a sophisticated solution. An important caveat here is that frameworks, like any non-empirical tool, are meant to give you a starting point for building hypotheses that you then test empirically. In other words, while the output may work, it also may not. It’s your responsibility to design solid experiments that allow you to tell the difference. 

If you’d like to learn a bit more about behavior change frameworks and see how you can get started in applying them, you can download our free guide below (we wouldn’t be much good at behavior change if we didn’t kindly ask for your e-mail in exchange).