What 238,619 Searches Reveal About How People Find OnlyFans

We logged every search, filter and "near me" tap on findapeach for six weeks, 238,619 of them. The most common search we saw was someone on their phone, in the Midwest, typing the name of their own state, rather than lingerie or celebrities.

You might expect an adult search box to fill up with wild fantasies, famous names and the kind of queries that make a cheap headline, but ours mostly doesn't.

What people actually type is Iowa. Then Ohio. Then Kentucky, Michigan, Maine. Six of our ten most-typed queries in June were nothing but US state names. The first look word with real weight behind it didn't show up until seventh place, MILF.

That sums up most of the report. People come to findapeach to find out who's on OnlyFans near them, and the rest of the data adds detail to that picture. The detail is worth a closer look.

01How people actually search

Every tap on a findapeach search form gets logged. In June, the demand split almost evenly across four habits, and the quiet winner is the one nobody asks for by name.

Form-event mix, June 2026.

Look at line three. "Near me" is nearly a quarter of everything we log, and it comes from a button people press rather than words they type. It's also our most honest signal of where the audience physically sits, because the browser hands us a real coordinate. More on that in a minute.

02Everyone's looking close to home

When people use the location filter, English-speaking countries lead, the US first, then Canada, the UK and Australia, with Romania the one outlier that keeps showing up.

Location-filter picks, June 2026. Also active: Ireland, France, El Salvador, South Africa, New Zealand.

But the filter rounds people up into countries. The free-text box is where they tell you what they really mean, and what they mean is their own backyard. Here's the search box, ranked:

Typed queries after test/spam strings removed. The tail runs Utah, Wisconsin, Minnesota, Idaho, Arkansas, state after state.

It keeps going like that. Idaho, Arkansas, Louisiana, Alabama, Missouri, all interleaved with a handful of look-words, BBW, Irish, latina. Most people seem to be checking what's available in their own area rather than browsing a catalogue.

And "near me" says the same thing in a different language. It's a phone behaviour through and through: 95% of those taps come from mobile. When we roll the geolocated sessions up by country, the shape is identical to the filter, two-thirds American.

Bars scaled to the US figure. Female is the runaway preference when one is set, 14,696 sessions, against 1,114 male and 769 trans.

The city ranking surprised us, because it doesn't follow the coastal megacities you'd expect. London leads, sure, and LA and Chicago are right there. But the fourth-biggest city for "near me" is Oklahoma City, ahead of New York, ahead of Seattle. Wichita, Albuquerque and Omaha all rank alongside the famous names. Demand is spread thin and wide across mid-size, Midwest and Southern metros, not pooled on the coasts.

Australia does the opposite trick: small as a country (4%), but every single state capital, Melbourne, Brisbane, Perth, Adelaide, Sydney, lands in the global top 20. Relative to its size, no country searches more at the city level.

03The look they describe

When people reach past geography to describe a type, the vocabulary is narrow and consistent. It's built from three things: ethnicity, body type, and the MILF/mature bracket. The tag filter ranks like this:

Tag-filter usage, June 2026. The free-text box pushes the same words harder: MILF, indian, BBW, Irish and latina lead the typed looks.

Two axes do most of the work. Ethnicity is one: latina, asian, indian and the nationality words. The MILF/mature bracket is the other; it tops the typed looks outright. Everything else (tattooed, blonde, curvy) is a smaller, steady undercurrent. If you're a creator wondering which words to put in your bio, this list is a good place to start.

04The combination that actually wins

Most searches carry one idea. But when someone packs both a place and a look into a single query, the same pattern comes up again and again: geography times ethnicity, anchored on the US.

Both-field searches. The tail: Colombia + latina, South Africa + indian, Spain + girlfriend-experience.

One word travels further than the rest. "Asian" pairs with the US, Australia, the UK and even Austria; it's the most location-portable look we have. "Latina," by contrast, stays in the Americas, clustering on the US and Colombia. That's useful to know if you're deciding which audience to target.

05What it adds up to

Across all of this data, one preference stands out: people want someone local. The state-name queries, the filter rankings and the "near me" coordinates don't disagree on a single point: this is a US-first, mobile, close-to-home audience, and the most common move on the entire site is a visitor checking who's nearby in their own state.

For creators, that's encouraging, because it's something you can control. Being easy to find where you are matters more than appealing to a national audience. Put your state and your city in your profile. Pick the two or three "look" words that genuinely fit, and lean on the evergreens the data keeps returning: latina, asian, MILF, tattooed, blonde, and the nationality you can claim honestly. Then let the geography do the heavy lifting.

In short, people search by neighbourhood far more often than by fantasy.

SOURCE, findapeach rwe_search_analytics. Search, filter, gender-preference and "near me" events logged from on-site forms, 30 Apr - 15 Jun 2026 (238,619 events; 57,738 in June). Near-me geography from 36,783 coordinate-stamped sessions. Bot and injection noise filtered; a handful of anomalous values excluded. No Google Search Console or third-party keyword data used.