Ujwala Agawane, Professor Brett Martin, 24 November, 2021

Recent research by Whyte, Torgler and Chan (2021) found some interesting results about how consumers date today. For example, people tend to be picky with many people having many factors they judge others on. “For men, the likelihood of having such stringent preferences was most common between ages 20 and 40. Among women it was more likely between the ages of 35 and 50.” Building on this work, we offer some key ideas about consumers and online dating, particularly how artificial intelligence (AI) is used by dating platforms.

Background: Online dating

Online dating was introduced in the 1990’s using text advertisements. Like the newspaper ads for partners, people had to read text to imagine the person advertising for a match. Match.com introduced the first online dating site in 1994. Although popular culture began making references to the use of electronic media for relationships, it was the innovation of smart phones that offered a major opportunity in dating through the use of mobile apps. In 2012 the market changed when Tinder added a simple visual interface along with geolocation. Tinder allows for the fast processing of multiple potential matches and includes proximity to encourage actual meetings between potential partners.

Too Many Profiles

For consumers, one of the key issues of whether a dating app is useful is whether desirable matches are shown to them. This may seem an obvious point but people looking for a long-term relationship with online dating tend to find the process exhausting and frustrating.

Poll: 45% of current or recent users of dating apps say using these platforms made them feel frustrated

Credit - Kaspersky Lab

One reason is that current algorithms for dating apps use matching based on partner preferences, mutual interests, lifestyle choices and perceived attractiveness. Physical attributes like appearances and financial expectations can be easier to match but personal attributes which reflect quality of life, morals and values can be more challenging attributes to validate. Another issue for consumers with dating apps are the sheer volume of potential matches. This might seem unusual as more profiles means more variety to consider. Some research also suggests that consumers are motivated. For instance, research suggests that a fear of being single is associated with frequent dating app usage.

However, even if motivated, research shows that consumers can become negative with so many potential matches to sort through. People – women in particular – can get a rejection mindset where they become more pessimistic as they view screen after screen of dating profiles. In addition to the sheer quantity of people to consider, the nature of assessing potential matches through online dating being offered by AI can change how people view if someone is seen as attractive.

A challenge for AI in offering relevant matches to consumers is that online dating offers the possibility of presenting exaggerated or false identities. For example, according to research, men exaggerate their income and height, while women exaggerate being a lighter weight and their looks by showcasing inaccurate photographs. In recent research on social media (not dating apps), female consumers viewed men who display their muscular physiques as less trustworthy, although the research did not address whether these men were viewed as attractive.

Relatedly, a second challenge relates to the unobservable motivations for why people are on the dating platform. For example, people who want short-term versus long-term relationships or who are pretending availability for ego-boosting self-validation purposes. Although for business AI benefits include speed, accuracy and consistency, for identifying matches for people who want long-term relationships, challenges for AI match selection include assessing consumer attributes like kindness, emotional intelligence, generosity, narcissism or forgiveness.

Despite the view that the visual swiping approach of dating apps leads to fast, superficial consumer judgments of matches, some research on Tinder suggests that people say they look for people with similar personality traits. Yet in an age where consumers use digital platforms to present different narrative selves to the world, the issue of authenticity is a challenge for a big data and data analytics approach.

Interestingly, as an aside, in the field of romantic consumption, marketing research also shows the types of marketing messages for romantic consumption work best for different types of attachment styles, and how the desire for emotional intimacy can drive consumer behaviour for romantic consumption products.

A third challenge, relates to the concern people have about sharing private information with strangers online. This concern with information and digital platforms is being addressed with our consumer research projects.

Overall, the field of online dating is interesting both for research and for AI dating apps to address some of the challenges we outline. We look forward to future AI research and innovations that address these challenges.

Authors

Ujwala Agawane

Ujwala is an Advertising and Marketing professional based in Brisbane, Australia. An Alumna of QUT Business School with a major in Strategic Advertising, Ujwala currently works as a Marketing Coordinator with M Group Co.

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Professor Brett Martin

Prof. Martin researches consumer behaviour. He has published in a range of marketing, advertising, psychology and tourism journals.

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