Intergroup Bias
[Last Updated January 21st 2024]
An in-group is any social group that an individual believes they are a member of. For example, an individual may identify as being Muslim, as a Canadian, as a War Veteran, as a Sci-Fi Fan, and/or as a Maple Leafs Fan. In-groups make people feel more comfortable. And people tend to automatically trust those in their in-groups (especially relative to those in an out-group). Out-groups on the other hand refer to any group that an individual does not identify with.
Intergroup bias represents a heuristic-based (automatic) preference for one’s in-group over one’s out-group, influencing a number of different cognitive and behavioural factors in respect to perception and decision making. Intergroup bias is also discussed as in-group favouritism, in-group preference, in-group bias, or in-group-out-group bias. This is an incredibly well researched and complex topic, as intergroup bias has been an integral part of wars, genocides, slavery, and discrimination throughout history and in the present. That being said, intergroup bias plays a role in almost all marketing strategies and needs to be understood, considered, and applied with caution.
The best way we can explain the powerful effect of intergroup bias is through the minimal group paradigm, designed by Tajfel et al. (1971) in the 1970s. In these experiments, Tajfel et al. (1971) assigned individuals an arbitrary group. For example, in one experiment they had participants rate paintings, and then randomly assigned them to a group denoting preference for a certain painter. Keep in mind, each individual participant may not have actually preferred that painter as assignment to groups was random. They were just told that they preferred a painter to create an arbitrary in-group identity. Participants were then asked to complete a resource distribution task where they had to choose how much of a resource to distribute to others, who were only identified by an ID number and their arbitrary group identity. They were told that they would receive whatever resources others distributed to them. In this situation, they wouldn’t have benefited from directly allocating any resources to a specific other (as everything was done anonymously), and they shouldn’t have been influenced by any social factors as they were interacting with ID numbers. The only variable that could influence them here is the arbitrary group identity. As you might have expected, participants provided more resources to those who were part of their arbitrary in-group. Since these studies have been carried out, they have been replicated numerous times under many different conditions in order to discover what factors can influence ingroup bias. There is currently no comprehensive review or meta analysis of the minimal group paradigm, but Otten (2016) provides a useful discussion of how it was being used in research approximately a decade ago. One study that demonstrates the potential power of ingroup identity was a minimal group paradigm study performed by Van Bavel et al. (2008). Here, white participants were told they were assigned to either the Leopards or Tigers team, and that they would be competing with the other team. Their first task was to memorize members of the team (they were shown photos). Each team had six black members and six white members. They then performed another task to help them categorize faces by team, and then a categorization task that included categorizing faces by either team membership or race. Following these tasks, participants were asked to rate the faces on a six-point liking scale, and perform a memory task where they reported which team each face was on. Van Bavel et al. (2008) found that participants preferred faces of in-group members, and that this preference wasn’t affected by race (which normally confers in-group and out-group status). Further, they examined neural processing via fMRI and found that it only took a few minutes for in-group biases to occur in respect to teams. Thus, an arbitrary group membership was able to override traditional in-group out-group bias within minutes, and influence preferences. As this was an fMRI study, Van Bavel et al. (2008) also describe the neural activity associated with this bias, which is worth reading if you are interested in social cognitive neuroscience. Some researchers describe this pattern of preferences for arbitrary in-groups as representative of mere membership, whereby individuals form ingroup bias by categorizing themselves into social groups. Dunham (2018) provides a great review of mere membership and its implications on our social relationships. In respect to marketing strategy, the key takeaway here is that in-groups influence our perceptions and decisions, and can be extremely arbitrary. This in turn suggests that through proper framing and priming, good marketing strategy can invoke or create ingroup identity.
One important additional consideration for marketing is the possibility of an ultimate attribution error towards your brand. This concept was introduced by Pettigrew (1979) as an extension of the fundamental attribution error, and suggests that when prejudiced individuals see an outgroup member performing a negative act, they will attribute that act to their personality or personal disposition, rather than consider environmental circumstances that may have led to the act. On the other hand, when they see an outgroup member doing something positive, they will assume environmental causes or alternative explanations like luck or hard work. The opposite holds true for ingroup members however, where a negative act is seen as due to external circumstances, and a positive act is thought to be due to disposition. Pettigrew (1979) examined this concept in terms of race/ethnicity considerations and prejudice. However, twenty years after Pettigrew (1979) introduced this concept, Hewstone (1990) performed a review of 19 studies and described how the ultimate attribution error could arise outside of prejudice, such as with sports fans in respect to home/away team performance. Similarly, a more recent study (Priedols et al., 2022) has found that the ultimate attribution error can arise within the domain of politics as well. As it seems like the ultimate attribution error may be reflective of intergroup bias, perceptions of your brand may play a role in customer’s assumptions about your decision making. This may become crucial in times of crises, where your brand’s reputation is at stake. If many of your customers see your brand as an in-group member (e.g. your brand lines up with their values and beliefs), they may forgive you if you make a mistake, and accept an apology. For example, if you post a politically incorrect tweet, those that identify with your brand may accept an apology claiming that it was an oversight error. On the other hand, if customers view you as an out-group member, they might assume that your mistake was a result of a problematic company culture or bad management. The best recent example of this was in 2023 when Bud Light sent a special can to a transgender influencer as a part of a small paid sponsorship. Immediately, conservatives in the United States labelled Bud Light as a “woke” company (an out-group derogation) and boycotted the product, calling for management to be fired (see Stewart, 2023), harming profits. At this point, every mistake Bud Light made was attributed to being a badly run company due to its adoption of woke culture by conservative media, and every attempt to mitigate the situation (such as putting marketing executives on leave) failed. Unlike Bud Light, Apple managed to make the best out of a bad situation, in part due to the many people who view Apple products as a lifestyle (and thus view Apple as sharing an in-group identity). In 2015, Taylor Swift removed her music from Apple music when they decided not to pay artists for free three-month trials that they were offering to their users to incentivize trying out the new service (see Bariso, 2015). She also wrote a letter on her Tumblr chastising Apple for their decision, but started the letter by praising Apple as a great partner (thus defining Apple as having in-group status to her fans). Apple quickly apologized, and agreed to pay artists during free trials. Within a few months, Apple Music had launched and become a success with over 15 million users (Atkinson, 2015) and 6.5 million paying subscribers (Faughnder, 2015). These examples demonstrate how your relationship with customers can influence their judgement and perceptions of your brand during a crisis, which in turn can have a dramatic impact on your brand’s success.
Studies on intergroup bias suggest there ought to be considerable benefits for your brand if consumers view your company or brand as having in-group status (e.g. if they can relate to your company in some way). For example, if your company primarily sells video games and regularly demonstrates that they are passionate about them (e.g. through social media posts), many users will likely view the company with some level of in-group favoritism compared to a random department store that also sells games. This can improve brand perception, which in turn can increase sales or purchasing intentions. The minimal group paradigm suggests that you can artificially create meaningful in-group identities, and increase their effect on behaviour and decision making by increasing their salience. Thus, if you don’t automatically fall into some form of in-group designation with your customers, it may be beneficial to create an in-group related to your brand. Apple did a great job accomplishing this through their Mac vs PC advertisements (Lo, 2012), that differentiated Mac users (portrayed as young and cool) from PC users (portrayed as being geeky). And their success navigating the previously mentioned Taylor Swift crisis likely benefited from having built this strong identity. If you are unable to build an in-group identity related to your brand, you can use social media and social media influencers to align your brand with various existing in-group identities. It is also important to always consider how others might view your business as an out-group, and plan how to respond to those individuals if a crisis ever occurs, as they will likely jump at an opportunity to criticize your brand. Further, recognizing when you are afforded the benefits of in-group status can help you determine how to respond to criticism. For example, if many of your customers personally relate to your brand, environmental excuses can potentially be effective (e.g. apologizing and blaming an intern). On the other hand, if you don’t have in-group benefits, you may want to consider addressing the crisis in terms of fixing issues with your company culture (e.g. firing managers, or restructuring departments and policies).
When launching a new product that has pre-existing demand, organize beta testers into a social group (e.g. a private Discord channel) and allow them to provide feedback and advice. Have an employee respond to nearly every suggestion, and summarize key concerns that appear repeatedly. Make sure you thank people, and address concerns. You will get free valuable beta testing, while artificially creating a group of individuals who feel like they have a direct connection with your product. These individuals (who you validated) are more likely to leave great reviews, share your product with friends and family (as they feel as though they played a role in it), and support you through mistakes. This is also a great way to find valuable talent for your team, especially in a startup environment.
Rather than create generic advertisements, find unique and distinguishable social groups to target. Then, create advertisements that will specifically resonate with those in-groups. For example, you might target Anime fans (a demographic easily targeted through advertising metrics) with anime-esque ads. Your ads will benefit from increased visibility. If someone likes anime, an anime-esque ad will shine above all generic ads on their feed. You will also automatically generate brand positivity in those viewing your ads, as people will assume you are part of their in-group (or at least recognize the importance of their in-group). In addition, you will almost always gain an advantage over competition that doesn’t speak to the in-group you are targeting.
Partnering with influencers who have strong in-group followings like Swifties (Taylor Swift) and Army (BTS) allows you to align your brand values and identity with their in-group identity. This can increase sales, and create a set of social media defenders in case you ever face a crisis. Of course, it’s important that you treat these individuals with respect, and understand what they are seeking in a brand. To determine if an influencer has a strong in-group oriented following, determine if they have a nickname, active fan groups, an active Reddit or Discord (or similar communities), etc. If you find up-and-coming influencers, paid sponsorships early in their career can get you a lot of credibility with their fan base. Branded merchandise (e.g. Samsung selling BTS phones and headphones) can also increase brand loyalty, as in-group identity may become partially tied to ownership of your branded product. This in turn can increase the lifetime value of customers.
If you are a small business, or have an interesting back story, you can connect your brand with its founders or owners, and use their in-group identities to connect with customers. For example, a female-led Middle Eastern beauty brand might leverage stories about their founders growing up without access to makeup that matches their skin tone. In this situation, not only would potential customers identify with the brand, but they might actively want the brand to succeed as they view the brand as an extension of their self-concept. Narratives are extremely powerful, and can easily make in-group identity salient, and blur the division between brands and individual identities.
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