Marketers oftentimes decide who to target by segmenting consumers into groups based on collected data. While creating these clusters, sometimes marketers fall into a trap of enforcing stereotypes, whether they be social, cultural, or based on gender. During these trying times where protests to ban discrimination are rising in many areas of our country, it’s important for marketers to refrain from exposing audiences to uniform messaging, especially if the messages can be deemed prejudice or controversial. This type of messaging can push potential customers into a bubble where they feel they must accept an ideal image that has been painted by marketers and can even sometimes prevent brands from truly understanding their consumer’s preferences.
There is, however, a remedy for this. With the digital era has come a golden opportunity to collect huge amounts of consumer information. Machine learning has significantly helped the marketing industry in this regard by turning all of this data into information that can then be utilized. Machine learning searched for patterns and is able to pick up on the intentions of consumers to make purchases. Additionally, information coming from browser cookies, social media, and previous e-commerce purchases, gathers and “memorizes” these behaviors.
So what does this all have to do with prejudice in marketing? Well, when marketers have the correct information that they need in hand, they can accurately pinpoint customer journeys and adjust what they are offering depending on each customer and also deliver these messages on the appropriate channels and at the right time to entice consumers to purchase.
An article by The Future of Customer Engagement and Experience elaborates further on this, stating that “Looking at a customer as part of a cluster may lead marketers to offer her/him a specific series of products, whereas looking at the individual behavior may lead to very different conclusions. As a beneficial side-effect, this, in turn, helps individuals eliminate the prejudice their specific cluster has locked them in when it comes to product preferences. Is this why, in parallel with the rise of more sophisticated customer profiling techniques, male toiletries has been one the fastest growing subcategories of cosmetics just over the last three years? Or why personal finance apps are flourishing, targeting long-neglected younger customers who want to make the most out of their limited spending capacity?”
Additionally, when it comes to content creation and the creative side of marketing, professionals must try to avoid utilizing stereotypical images. One of the purposes of marketing is to use images in order to elicit associations. This can be a problem when so many images have concealed associations that can spark reactions. Reactions to images and how they are interpreted differ extensively from person to person so sometimes ads can unintentionally propagate negative stereotypes. By putting these images out there, marketers run the risk of perpetuating prejudice and bias. However, by crafting exceptional and authentic images, the marketing industry can change the landscape and significantly decrease discrimination.