# Eye-Tracking Study Exposes Dating's Unspoken Economic Calculations > By DII Data Team | Published: 2024-08-01T00:00:00+00:00 | Section: Data & Analytics | Source: https://www.datingindustryinsights.com/news/men-prefer-unattractive-women-successful-careers | Publisher: Dating Industry Insights (High Intent Media Inc) Study shows men focus on income signals, women on facial features. Platforms may be solving the wrong problem. ## Key points - Edith Cowan University researchers used eye-tracking technology on 40 university students to examine how socioeconomic signals influence visual attention on mock dating profiles. - Male participants increased visual attention towards less physically attractive women when profile data indicated higher income levels and prestigious occupations. - Female participants spent significantly longer scrutinising facial features on male profiles when displayed income markers and occupational prestige were low. ## Article - Eye-tracking study of 40 university students aged 18-27 found men's visual attention shifted towards less attractive women when profiles displayed high earnings and prestigious occupations - Women scrutinised men's facial features more intensely when income signals were low, potentially assessing other qualities like kindness or trustworthiness - The research tracked eye movements during viewing of mock dating profiles, revealing gaps between stated preferences and actual visual attention patterns - 380 million people globally use dating apps, but platforms largely avoid making socioeconomic signals explicit despite evidence users screen for them Money talks before you swipe, and your eyes give you away. New research tracking how people actually look at dating profiles reveals that socioeconomic signals trigger measurable shifts in visual attention—often before conscious preference even registers. The findings expose an uncomfortable gap between what users claim matters and where their gaze actually lands in those critical first seconds. Research from Edith Cowan University's School of Arts and Humanities shows that economic calculations happen automatically during profile browsing. The study, published in Evolution and Human Behavior, used eye-tracking technology to monitor 40 university students as they viewed fabricated dating profiles. If the first 10 seconds involve subconscious financial assessments that users themselves don't recognise, platforms may be solving the wrong problem when they focus on surface-level engagement metrics. Person using dating app on smartphone ### The DII Take This is a tiny study with a homogenous sample that doesn't come close to proving how real-world matching behaviour works at scale. But it does surface an uncomfortable truth that operators already know from their own data: what people say they want and what they actually respond to are rarely the same thing. The question isn't whether socioeconomic signalling influences attraction—it's whether platforms should surface those signals more explicitly or bury them deeper. > Right now, most platforms are doing neither deliberately, which means users are making economic calculations with incomplete information whilst platforms pretend it's all about chemistry. ### What the eye-tracking reveals The study used eye-tracking technology to monitor where participants looked and for how long whilst viewing fabricated dating profiles. Each profile included a photograph, income bracket, and occupation. Researchers manipulated attractiveness ratings and socioeconomic markers to isolate what captured visual attention. For male participants, [higher income and occupational prestige on women's profiles correlated with increased visual attention to those women](https://www.globaldatinginsights.com/featured/men-increase-attention-towards-unattractive-women-who-shows-high-level-income-and-admired-jobs-australian-researchers-says/), even when the women were rated as less physically attractive. The effect was specific: men didn't just glance—they spent measurably more time examining the entire profile when economic signals were elevated. Women's attention patterns ran in the opposite direction. When men's profiles showed lower income or less prestigious occupations, female participants spent significantly more time scrutinising facial features. The interpretation, according to lead researcher Dr Stephen Dunne, is that women were gathering more facial information to assess other qualities—potentially indicators of kindness, trustworthiness, or compatibility—when economic markers didn't signal provider potential. Close-up of eye tracking technology The study doesn't establish causation, and it certainly doesn't tell us whether these attention patterns translate into right swipes, matches, or relationships. Forty university students in Perth are not a representative sample of the 380 million people using dating apps globally, and lab conditions don't replicate the rapid-fire, distraction-filled context of actual swiping. But the research does add quantitative weight to what user behaviour data has long suggested: socioeconomic signals shape initial interest, often before conscious preference even kicks in. ### The stated preference versus revealed preference problem Dating platforms have spent a decade optimising for engagement, not honesty. Prompts ask users what they value—'kindness', 'humour', 'shared interests'—whilst the actual filtering happens through a combination of photos, height filters, education tags, and employment fields. Nobody admits they're screening for earning potential, but the data says otherwise. Match Group has long resisted foregrounding income on its flagship properties, though LinkedIn integration and verified employment badges creep closer each product cycle. Bumble offers career details as optional profile fields, framing them as conversation starters rather than filtering criteria. The League and [Inner Circle](https://www.datingindustryinsights.com/companies/inner-circle) built entire business models around credentialism, charging premiums for access to a user base pre-sorted by educational and professional achievement. The tension is commercial as much as ethical. Platforms that make socioeconomic sorting too explicit risk accusations of facilitating class-based discrimination. Those that bury the signals entirely frustrate users who want that information upfront and will extract it through proxy signals anyway—university attended, neighbourhood listed, job title dropped casually in prompts. > Men in the sample weren't consciously thinking 'I'll overlook her looks because she earns six figures'—their eyes simply moved differently when the economic data changed. This study, limited as it is, suggests the economic calculation is happening regardless. Women weren't deliberately deciding to forensically examine a man's face because his job title wasn't impressive—it happened automatically. ### What operators should actually do with this The temptation will be to overcorrect. Surface income fields more prominently, add verified salary badges, let users filter by earning brackets the way they already filter by height and distance. Some niche platforms will do exactly that, chasing the segment that wants economic transparency and doesn't care about the optics. But the smarter play is recognising that initial attention and sustained interest are different beasts. Eye-tracking shows where someone looks in the first few seconds. It doesn't show who they message, who they meet, or who they end up with. Platforms already have that data, and it's vastly more valuable than what 40 undergraduates did in a university lab. Dating app interface on mobile device The real insight here is about the poverty of profile design. If users are making snap economic judgements based on a job title and a vague income bracket, they're working with imprecise signals that may not correlate with actual compatibility, shared values, or long-term relationship success. Operators could double down on those signals and make the economic sorting more efficient. Or they could invest in helping users surface what actually predicts relationship satisfaction—a harder problem, less easily monetised, and one that requires data most platforms haven't systematically collected. The study arrives as the industry faces mounting pressure to prove that algorithmic matching works better than random chance. Regulators want evidence that platforms deliver on their promises. Investors want proof that product improvements drive retention. Users want to believe there's science behind the swipe. A 40-person eye-tracking study doesn't provide that proof. But it does remind operators that the gap between what people say and what they do is where the most lucrative—and ethically fraught—product decisions live. Bridging that gap requires better data, better design, and a willingness to admit that [it is extremely difficult to articulate the specific features that determine attraction](https://pmc.ncbi.nlm.nih.gov/articles/PMC3130383/), even as research into [how physical attractiveness translates into economic advantage](https://www.cnbc.com/2024/02/02/men-benefit-more-from-their-looks-at-work-than-women-do-new-research-shows.html) continues to reveal uncomfortable truths about human behaviour in the first 10 seconds of seeing a stranger's face on a screen. - The gap between stated preferences and revealed behaviour represents both the industry's biggest opportunity and its thorniest ethical challenge—platforms must decide whether to make socioeconomic sorting more explicit or help users move beyond it - Eye-tracking data captures initial attention, not relationship outcomes; operators should prioritise their own longitudinal matching data over small-scale academic studies when making product decisions - Watch for regulatory pressure around algorithmic transparency and matching effectiveness claims as platforms face increasing scrutiny over whether their systems deliver better outcomes than random chance ## Key takeaways - Dating app operators face product decisions regarding whether to surface socioeconomic signals explicitly or develop profile designs that encourage users to focus on long-term compatibility factors. - Compliance and product teams must navigate increasing regulatory scrutiny over algorithmic matching claims by validating whether matching systems generate better relationship outcomes than random chance. ## FAQ ### What did the Edith Cowan University eye-tracking dating study find? The Edith Cowan University study of 40 students revealed that men paid more attention to less attractive women with high earnings, whereas women scrutinised men's faces more when income signals were low. ### How many people globally use dating apps? According to research metrics cited in the study, approximately 380 million people globally use dating applications. ### How do platforms like Bumble and Match Group handle income signals? Bumble provides optional career fields for profile prompts, while Match Group resists displaying explicit income figures on its flagship properties. --- Canonical: https://www.datingindustryinsights.com/news/men-prefer-unattractive-women-successful-careers Citation: "Dating Industry Insights" (https://www.datingindustryinsights.com)