Psychology and its influence on design: Users are social animals
To design better experiences, we must understand what users need and want by observing their thoughts, feelings and behaviours. However, understanding the mental process of how they interact with a product, service and system is not easy, as there can be no greater scientific mystery than the human mind.
In this article, I’d like to point out how psychology shapes user experience, focusing on how humans make decisions and how others influence them in society. Decision-making can involve more people than we expect. With this in mind, we should look at not only the problem that requires a solution but the people who solve it and the context where the decision is made.
Human behaviour and decision-making
Due to the limited cognitive bandwidth, human brains are conditioned to focus on things seen as most important. It is impossible to process all information that might be relevant in a world with so much uncertainty. Doing things right can be challenging for many of us because we need to pay attention to too many details that seem easy to ignore. To overcome it, we may use many shortcuts, such as experience and heuristics, to help us go for good enough outcomes to save time and effort (see Gerd & Wolfgang, 2011).
In the tradition of choice theory, people are assumed to know the consequences of their choices beforehand, which is seen as perfect knowledge (Glasser, 2007). Also, they are motivated to make the best possible decision to optimise outcomes based on logically related facts. In other words, intuitions are considered unreliable. However, this may not be the complete picture of making decisions. The context where decisions are made is often neglected.
As humans are a very social species, using the behaviour and experiences of other people is a fundamental aspect of our decision-making (Simon, 1990). For example, we may check comments on Google and make our final decisions based on what others say before going to a new restaurant. Individuals, in general, believe our social environment is made up of a large part of people having similar tastes and values as ourselves. It is thus seen as a perfect and rational strategy to use the knowledge accumulated in our social network, where information travels from one end of the network to another.
Wason selection task
Now, let’s make a decision on a four-card problem. Please try to be as fast as possible. This is a psychology experiment, a logic puzzle devised in 1966 by Peter Wason, an English Cognitive Psychologist. It is one of the most famous tasks in the study of deductive reasoning:
Each card has a number on one side and a patch of colour on the other. Which card or cards must be turned over to test the idea that if a card shows an even number on one face, then its opposite face is red?
In this case, the rule is if the card shows an even number on one face, then its opposite face is red. The correct response is thus to turn over the 8 card and the brown card. The details are shown as follows:
- It doesn’t matter if the 3 card is red or brown. The rule makes no claims about odd numbers.
- If the 8 card is not red, it violates the rule.
- The red card can be odd or even. The red colour is not exclusive to even numbers.
- If the brown card is even, it violates the rule.
Let’s try another task:
Each card has an age on one side and a drink on the other. Which card or cards must be turned over to test the idea that if you are drinking alcohol, then you must be over 18?
Leda Cosmides and John Tooby (1992) indicate the selection task is likely to draw out the correct response without making much effort when given in a context of social environments. As shown in the drinking example, people must be over 18 to be able to drink alcohol. Most participants in this task can easily select the correct cards, which are the 16 card and the beer card. It is shown easier to find out who the underage drinker is than the abstract concept.
In a series of experiments in different contexts, it is argued that people learn the social exchange rules via practice and consider it easier to apply familiar rules than less familiar ones. Rather than content-free general-purpose mechanisms, context-sensitive mechanisms govern human reasoning to solve particular social interaction problems. Note that the debate on domain-specific reasoning mechanisms (context-sensitive) is still ongoing (see Kaufman and colleagues, 2010), which is out of the scope of this article that we will not focus on.
The impact of social networks
From a psychological point of view, it is widely accepted that humans are social animals who frequently interact with one another. While in a community, individuals often collaborate without centralised direction, namely herd behaviour. That is, the chain of command that is not distributed from top to down of a group. For example, voting, sporting events, riots and everyday decision-making are all human-based herd behaviour (Braha, 2012).
As noticed, people are connected through a social network. Individual cognition and social interaction appear to be co-dependent. These interactions may attend to the exchange of information, the sharing of norms or the transmission of viruses. According to Dunbar (1992), humans have evolved a cognitive ability to maintain steady social relationships with a structure of about 150 people.
It is interesting to note that social interactions are much more complex when we are linked globally via the internet with the abundance of social media. Many interactions still happen in smaller networks with dense connections, such as families and friends, where users pay the most attention (Krienen and colleagues, 2010). In other words, humans up to this time still tend to cluster in smaller groups as we did in tribal networks hundreds of thousands of years ago.
In general, people fear social exclusion. We feel a need to observe what is considered normal in the community and collect information on the merits of one idea over another. In an agent-based model powered by NetLogo (1999) as shown below, it can be easily seen from the experiments indicating how fast a product can spread through a community with a strong social influence.
To what extent are humans social animals?
At times, feeling uncomfortable won’t stop us from imitating others. Social norms may cause us to choose a product or conform to an idea that we don’t like. We do it because we may feel even more uncomfortable when sticking out. As a result, much of our behaviour is driven by normative force rather than personal preferences. Norms are one of the critical drivers of behaviour to inform us about what is considered accurate in a given situation.
Preferential attachment also plays a vital role in society, especially in larger groups. Famous people tend to have a lot of followers, which is the primary mechanism behind why kids like to be friends with their popular classmates. The more connected a person is, the more likely they will receive new links. The popularity grows on the number of followers one has. It can be beneficial that powerful friends help to contribute to our social status.
Contracting a virus in a social network may be fast, but diffusing an idea can be very slow, even in a closed group. To decrease the spread of the virus, we can reduce the number of links such as physical distancing. However, it takes work to remove an idea from a person when it is accepted. As stated by Victor Hugo, no force on earth can stop an idea whose time has come. Adopting a product, similar to buying an idea, is a perplexing process. Although we’ve seen the computational simulation in an agent-based model indicate that users in a community can quickly adopt a product with a strong social influence, how does it work in real-life situations?
How likely individuals want to conform to social norms varies depending on various situations. It may be more common to ignore the red light and cross the street than to commit a crime risking prison sentences. When it comes to making decisions in our private lives, the norm of what rice we eat will not be as important as what clothes we wear on certain occasions where we are visibly exposed.
Meaningful connections
As expected, deciding what to invest in a financial product is fundamentally different from what to have for lunch. When buying a sandwich, customers can readily choose to try something new based on what others say. There won’t be a huge risk to take, and it won’t put anyone’s life in danger. On the other hand, investing is a big deal for many people. Losing money can be a terrible thing, which doesn’t mean humans are not social animals when it comes to money. On the other hand, it shows a dynamic network with diverse agents comes into play.
Based on the empirical data of a project I worked on for Lloyds Banking Group, we discovered meaningful connections are a critical driver for the customer investing journey. A preferential attachment won’t work so well if we only share expert testimonials with the customers. How do we form a meaningful connection with our users?
Take a look at the communication used on the website. When given to participants in our project, many don’t think they should follow what others do, although it encourages a fear of missing out. They want it to be a personal choice that suits their situation. The message does not successfully build a meaningful connection between investors and non-investors. Financial experts’ instructions may gain the general audience’s trust but do not resonate with them. Resources are expected to share similar characteristics with the users, such as the same financial and regional background.
Takeaways
- Humans rely on what others say.
- Social groups tend to be small, with a structure of 150 people.
- Humans are wired to pay special attention to families and friends
- When making decisions, it may be easier in a social setting that is familiar to the user.
- When a user follows a social norm, context is vital.
- To reduce the fear of users, the credibility and similarity of other people can help
- Meaningful connections shape the user experience.
References
Braha, D. 2012. Global civil unrest: Contagion, self-organization, and prediction. PLoS One: 7(10), https://doi.org/10.1371/journal.pone.0048596.
Cosmides, L. & Tooby, J. 1992. Cognitive adaptions for social exchange. In Barkow, J; Cosmides, L; Tooby, J (eds), The Adapted Mind: Evolutionary Psychology and the Generation of Culture. Oxford, England: Oxford University Press.
Dunbar, R. 1992. Neocortex size as a constraint on group size in primates. Journal of Human Evolution, 22(6): 469–493, https://doi.org/10.1016/0047-2484(92)90081-J.
Gerd, G & Wolfgang, G. 2011. Heuristic decision making. Annual Review of Psychology: 62(1): 451–482, https://doi.org/10.1146/annurev-psych-120709-145346.
Glasser, W. 2007. Choice Theory: A New Psychology of Personal Freedom. New York: HarperCollins.
Kaufman, S; De Young, C; Reis, D; Gray, J. 2010. General intelligence predicts reasoning ability even for evolutionarily familiar content. Intelligence: 39(5): 311–322, https://doi.org/10.1016/j.intell.2011.05.002.
Krienen, F; Tu, P I’m & Buckner, Randy. 2010. Clan mentality: Evidence that the medial prefrontal cortex responds to close others. The Journal of Neuroscience 30(41), https://doi.org/10.1523/JNEUROSCI.2180-10.2010.
Simon, H. 1990. Invariants of human behaviour. Annual Review of Psychology: 41: 1–19, https://doi.org/10.1146/annurev.ps.41.020190.000245.
Wason, P. 1966. Reasoning. In Foss, B (ed), New Horizons in Psychology. Harmondsworth: Penguin.
Wilensky, U. 1999. NetLogo, http://ccl.northwestern.edu/netlogo.
