MSU Study Puts Hinge and Bumble's Scarcity Logic on Trial

A decade of dating app product design rests on a single assumption: too many options paralyze users. Hinge's daily like cap, Bumble's swipe restrictions, the entire "intentional swiping" framing, all of it traces back to choice overload theory. New research from Michigan State University says that assumption may be wrong, at least in dating contexts. The implications for how you build, and who you're actually building for, are uncomfortable.

The study, published in the Journal of Social and Personal Relationships, ran two experiments involving 535 participants total. The first presented users with either 6 or 31 profiles. The second recruited active dating app users and replicated the design. Both times, more choices correlated with stronger stated commitment to pursuing a relationship and higher perceived compatibility with the selected match. The result was consistent across both experiments.

The High Intent Take

This research should make product teams at Hinge and Bumble uncomfortable, not because it's definitive, but because it directly challenges the design orthodoxy that justified a decade of artificial scarcity. If the choice overload theory is overstated in dating contexts, platforms may have been throttling user outcomes while optimizing for engagement metrics that keep people on the app longer without actually helping them find a match. That's a bad deal for users dressed up as a feature. The move here is to run a controlled test: expand visible choice sets for a segment, measure message rates, date conversions, and reported relationship formation at 30, 60, and 90 days. The data to resolve this question exists. The question is whether anyone has the appetite to ask it.

Dating Is a Matching Market, Not a Consumer Choice

The researchers, Junwen Hu and David Markowitz, frame online dating as a "matching market", closer to job hunting or home buying than to choosing between pasta sauces. That framing matters. In labor and housing markets, thicker pools demonstrably improve outcomes. More candidates increase the probability of finding someone who meets specific, complex, multidimensional criteria. The analogy positions dating as a search for genuine fit rather than a selection among interchangeable options.

Participants shown 31 profiles were more likely to identify someone who closely matched their stated preferences, which in turn drove both perceived compatibility and readiness to pursue a relationship. The study found no evidence that abundance made users more demanding or intensified fear of missing out, the two assumptions that most justify current design constraints. The abundance appeared to validate the search process rather than paralyze it.

A user shown 31 profiles and genuinely drawn to one of them has a clearer signal than a user shown six who selects the best available option. That's a meaningful difference in the quality of the commitment, and in the long-term value the platform delivers.

Current design constraints at Hinge and Bumble explicitly position scarcity as a benefit: limits encourage "intentional" swiping, the theory goes, which produces better matches. If this research holds, that framing is backwards. A smaller pool doesn't produce more intentional choices. It produces choices made with insufficient information, which is a worse outcome for users even if it produces more engagement time for the platform.

The Limits of the Research Are Real and Worth Naming

Both experiments measured self-reported intentions immediately after viewing profiles, not verified relationship formation or sustained commitment. The gap between "I would pursue this person" in a controlled research setting and actually messaging, meeting, and building a relationship is substantial. Lab conditions with curated profiles don't resemble the chaotic, infinite-scroll reality of Tinder or Hinge.

Sample sizes were modest: 193 participants in the first experiment, 342 in the second. Both were conducted online, not by tracking real app usage patterns over time. The research cannot tell you whether users shown 31 profiles daily would experience fatigue over weeks, whether they'd send messages at lower rates, or whether they'd churn faster than users in constrained environments. Those are the questions that matter to operators managing retention and lifetime value.

The study also doesn't address the economic incentives at play. If larger choice sets genuinely accelerate commitment, platforms face a real tension: better user outcomes may mean faster churn and shorter subscription lifetimes. That tension isn't new, but this research brings it into sharp focus.

What the research cannot do is settle the question. What it does do is challenge the certainty with which the choice overload assumption has been baked into product design without rigorous testing in actual dating contexts. The choice overload theory, as applied to dating, has been treated as settled science. It isn't.

The Operator Decision: Test, or Wait for a Competitor to Test First

Platforms now face an uncomfortable choice. Maintain current design constraints and risk that a competitor runs the experiment first and demonstrates better matching outcomes. Or expand visible choice sets, accept the possibility of higher short-term churn, and bet that superior user outcomes build the brand strength and word-of-mouth that drives organic growth long-term.

Bumble and Hinge both have the user bases to run statistically significant experiments comparing choice abundance against current constraints, measuring not just stated preferences but actual message rates, date conversions, and relationship formation at 30, 60, and 90 days. The research suggests larger pools improve compatibility and commitment in controlled conditions. The platform-scale test would tell you whether that holds in the wild.

Smaller operators and new entrants have less to lose from testing this aggressively. A platform built explicitly around abundant choice, algorithmically curated but visually presented in larger sets, could position itself as the anti-scarcity alternative to the incumbents. The pitch is simple: more candidates, better fit, faster commitment. Whether that converts subscribers depends on execution. But the competitive wedge is real, and right now it's unoccupied.

The fundamental tension between user outcomes (faster matching, shorter platform relationship) and platform revenue (prolonged engagement, longer subscription lifetimes) isn't resolved by this research. But it is sharpened. The question every product team needs to answer honestly is: which side of that tension are your current design decisions actually optimizing for?

Here's the move if you're a product leader at Hinge or Bumble right now. You don't have to commit to a full choice architecture overhaul. You run a controlled test: take 10% of new users, expand their visible candidate pool significantly, and track actual outcomes at 30, 60, and 90 days, not self-reported intentions, not engagement metrics, but message rates, first dates, and relationship formation. If larger pools produce better outcomes, you have a credible case to present to your own organization. If they don't, you've answered the question with data rather than assumptions. The cost of the test is low. The cost of continuing to design around an untested assumption is potentially much higher.

For new entrants, the competitive framing is straightforward: position explicitly as the anti-scarcity platform. Name the design constraint that incumbents have built their products around. Tell users directly that you show them more candidates because you believe they deserve a real chance to find a genuine match, not an artificially constrained queue. The research now provides the academic foundation for that claim. Whether users respond to that pitch in actual acquisition campaigns is an empirical question, but the positioning gap is real and currently unoccupied.