Rebuilding the Dating Market

01 — The Problem

A right swipe costs nothing. The upside, a possible match, stays constant no matter how many profiles someone swipes through, while the downside of swiping right on someone you would never actually message is close to zero. Swiping on everyone is therefore the rational move, not a character flaw, and the apps' own mechanics reward it: more swipes, more matches, more sessions, more time in the product.

That volume has to land somewhere. On most mainstream apps it lands disproportionately on women, who end up receiving far more matches and messages than they can genuinely evaluate. The work of figuring out who is actually interested, as opposed to who swiped right on everyone within range, now falls entirely on the person receiving the attention. A full inbox looks like abundance. In practice, it is mostly noise with a small amount of real signal buried inside it.

The men who do swipe deliberately pay a cost for this too. Their genuine interest looks identical, from the receiving end, to everyone else's indiscriminate swiping, so it gets buried in the same inbox and treated with the same suspicion. The apps have no way to tell the two apart, because they never asked the question. A right swipe means the same thing whether it was the only one sent that day or the three-hundredth.

02 — Why Now

Swipe-based matching has worked this way for more than a decade, and the incentive problem inside it is not new. What has changed is how openly people talk about it. Dating app fatigue, matches that go nowhere, conversations that die after three messages, has become a mainstream complaint rather than a niche one, and a meaningful share of the people who would be a dating app's best users are the ones most likely to say they have deleted the apps entirely.

At the same time, the tools needed to fix this are newly cheap. Identity verification and liveness checks, once expensive enough to skip, are now close to commoditized, which matters for an app trying to guarantee that the person on the other end of a match is real. More importantly, the behavioral data needed to tell a selective swiper from an indiscriminate one, swipe-to-match ratio, response rate, how often a conversation actually leads somewhere, has always existed inside these platforms. It has simply never been used to shape who gets access to whom. Computing and acting on that signal is now inexpensive enough to be a product decision rather than an infrastructure project.

03 — What We Believe

We believe the dating platforms built on the current swipe mechanic are structurally unable to fix this, because the thing they would need to reduce, indiscriminate swiping, is the same thing their engagement metrics reward. A platform paid by subscription or ad impressions has very little reason to make swiping more expensive, even when its own users are telling it the volume is the problem.

The behavior persists for understandable reasons on every side. Men keep swiping broadly because the occasional match, arriving at random, is worth far more than the five seconds it costs to try, the same variable-reward pattern that keeps any low-cost, high-upside action going. Women keep using apps that overwhelm them because opting out means forgoing the connections mixed in with the noise, not because the current volume works for them. And the platforms keep optimizing for more matches and more messages because that is what their revenue depends on, independent of whether those matches lead anywhere.

A right swipe should cost something again, not money necessarily, but attention, restraint, or consequence, so that reaching someone means something by the time it happens.

We believe the next platform in this category will not win by making matching easier. It will win by making indiscriminate swiping a visible, measurable, costly behavior, and by making genuine selectivity, on both sides, something the system can actually see and reward.

04 — Customer & Use Case

The clearest pain sits with the people on the receiving end of disproportionate volume, on most platforms today, primarily women, who want a smaller number of matches they can trust rather than a larger number they have to screen. Right behind them are the minority of men who already swipe deliberately, whose genuine interest is currently indistinguishable, to the system and to the person receiving it, from everyone else's volume.

05 — Market & Business Model

We are deliberately leaving the exact mechanism open. What we believe, based on what is being asked of this thesis, is that the model needs to attach a real cost to low-selectivity behavior and a real reward to high-selectivity behavior, whether that cost is economic (a limited number of free swipes before each additional one costs something), algorithmic (reduced visibility for accounts that swipe on nearly everyone they are shown), or social (a visible, honestly computed selectivity signal attached to a profile). Which of these actually changes behavior without just pushing indiscriminate users to a free-for-all competitor is a question for whoever builds this, not one we are answering in advance.

06 — Existing Alternatives

The existing responses to this problem have mostly added filtering on top of an already-noisy signal rather than making the signal itself more honest. Paid boosts and super-likes increase a given profile's visibility, which increases the volume problem for whoever is on the receiving end of it. Paywalls that let you see who already liked you monetize the noise rather than reducing it. Requiring women to message first, popularized by Bumble, shifts who carries the burden of the first move, but a man can still swipe right on everyone before that point, so the underlying incentive to swipe indiscriminately is untouched. Identity verification badges, now common across most major apps, address whether a profile is real, not whether the person behind it is being selective.

None of these change what a right swipe actually costs the person sending it. That is the piece we think is still open.

07 — What We Would Test First

Before building a new app, the thesis worth testing is whether a selectivity signal, however it is computed, actually predicts which matches turn into real conversations, and whether making that signal visible changes how people swipe. If a visibility penalty for indiscriminate swiping does not change behavior, because people simply tolerate lower visibility or move to an app without the penalty, the mechanism does not work regardless of how well the rest of the product is built. That is the experiment to run first.

08 — Founder Profile

Someone who has built a consumer product where one side's behavior directly shapes another side's experience, a marketplace, a social platform, a trust-and-safety system, and understands how reputation and incentive design actually change user behavior rather than just how they look on a slide. Direct, honest frustration with the current state of dating apps helps, but conviction about why the incumbents cannot fix this from the inside matters more.

09 — Open Questions

• Can a selectivity signal be computed in a way that is hard to game, or will people simply learn to swipe right less often while being no more genuinely selective about who they choose?
• Will men tolerate, or even prefer, a system that visibly throttles indiscriminate swiping, or will enough of them simply churn to an app without that friction?
• Does the cost attached to low-selectivity behavior need to be economic, algorithmic, or social to actually hold, and does that answer differ by market or culture?
• What would prove this thesis wrong? If people keep choosing the free-for-all apps over a quality-gated one despite complaining about the noise, the premise does not hold.