It’s easy to think of online trends as separate lanes: fragrance is “lifestyle,” OnlyFans is “creator economy,” and AI is “technology.” In reality, they’re all versions of the same thing: markets built on preference—what people like, what they click, what they buy, and what they come back for.
A short lifestyle piece about “men’s favorite perfume” generated by AI analysis might feel worlds apart from reports claiming Americans spent $2.6B+ on OnlyFans in 2025, but the underlying logic is identical: data is being used to translate messy human desire into measurable patterns, rankings, and revenue.
This article ties three sources into one narrative:
- how an AI-assisted study ranked men’s favorite fragrances (and what that signals about taste modeling), via this write-up on men’s favorite perfume according to artificial intelligence
- how macro reporting framed the U.S. OnlyFans market with a “$2.6B in 2025” headline, via this post on Americans spending $2.6 billion on OnlyFans in 2025 (note: this page was not accessible to me due to a browser challenge, so I’m careful to treat it as a cited claim rather than verified details)
- how a stats-heavy breakdown of subscriber behavior (spenders vs non-spenders, transaction patterns, etc.) supports a more grounded view of the market, via this analytics gateway link to OnlyFans statistics (which redirects to an OnlyGuider statistics page)
1) What an “AI perfume ranking” really represents
The fragrance article is brief, but it’s revealing: it describes a French startup (Sensia) using AI to analyze consumer feedback and reviews—reportedly based on 10,000+ consumers and e-commerce review data—to identify which perfumes are most favored.
For men, the top pick was stated as Dior Sauvage Elixir with 97% positive reviews, followed by items like Boss Bottled Elixir and One Million (Paco Rabanne).
It also includes a top-10 style list, which is basically a “taste map” presented in a simple format people understand instantly: rankings.
The bigger point isn’t which scent “wins.” It’s that we’re increasingly comfortable letting algorithms do two things at once:
- summarize preference at scale (thousands of reviews → a single ranking), and
- explain popularity (review language → reasons a scent succeeds).
That same logic shows up everywhere online. And it shows up very strongly in creator monetization.
2) OnlyFans spending headlines are preference data, too
Now jump to the creator economy side. A headline like “Americans spent $2.6 billion on OnlyFans in 2025” is essentially a macro-level taste signal: it says “a lot of people bought this kind of digital experience repeatedly.”
Your SolPlaza link frames that claim directly: Americans spent $2.6 billion on OnlyFans in 2025. (I couldn’t load the page due to a protection interstitial, so I’m not quoting its internal methodology.)
However, the same “~$2.6B” magnitude appears in other reporting that cites OnlyGuider/Finbold-style calculations—for example, an article stating Americans spent nearly $2.64B on OnlyFans in 2025 and describing it as year-to-date derived averages.
Whether the exact number is $2.60B or $2.64B, the strategic meaning is the same: this is not one-off novelty spending. It implies recurring behavior—subscriptions, unlocks, tips—happening at high frequency.
And here’s the link back to the perfume story: both are about capturing and monetizing preference. Fragrance brands want to know “which scent profile wins.” Creators want to know “which offer and persona wins.” Platforms want to know “which experiences drive repeat purchases.”
3) The stats that matter: most users don’t spend
The macro headline is impressive, but the micro behavior decides who actually earns. That’s why the third link matters: the redirect leads to an OnlyGuider statistics post that claims it analyzed 1,003,855 subscribers and 58,947,698 transactions in a dataset focused on subscriber behavior.
One striking claim in that summary: only 4.2% of male subscribers made any purchases, while the rest spent nothing.
Even if you treat this as one dataset with its own limitations, the direction is consistent with what many digital marketplaces see: revenue is concentrated. A small segment of users drives a large segment of spend.
That changes how you interpret the $2.6B headline. It’s not “everyone is paying.” It’s “enough people are paying a lot, often repeatedly.”
And that brings us back to preference modeling: when value concentrates, what matters isn’t just “how many users,” but “which users” and “what triggers them to buy again.”
4) The shared engine: ranking and segmentation
Look at how the fragrance article works:
- it takes a messy universe of taste,
- compresses it into a list,
- and makes that list actionable (“these are the top choices”).
OnlyFans marketing (and creator strategy) is basically the same process, just with different objects:
- instead of “perfume notes,” it’s niches, aesthetics, and promises,
- instead of “positive reviews,” it’s conversion and retention,
- instead of “top 10 perfumes,” it becomes “top 10 content angles” or “top 10 upsell scripts.”
This is why platforms and marketers obsess over segmentation:
- some segments want low price + high volume,
- others want exclusivity,
- others want personalized interaction,
- others want a fantasy “brand” that feels consistent.
In fragrance, you could call it “fresh vs spicy vs woody.” In creator economy, it’s “free funnel vs paid page,” “girlfriend experience vs premium content,” “community vibe vs 1:1 attention.” Same concept: categorize desire into buckets you can serve.
5) Where AI fits: from “what people like” to “what people will buy”
The perfume piece suggests AI can explain why certain fragrances succeed by analyzing review language.
That idea (mining text for preference signals) is extremely applicable to creator businesses too:
- analyzing DM conversations for recurring purchase triggers
- analyzing caption language that leads to higher click-through
- clustering audience reactions by theme (“confident,” “romantic,” “taboo,” “luxury”)
- predicting which fans are likely to convert from subscriber → buyer
This is also where creators can pull lifestyle branding into monetization in a non-obvious way. Fragrance is a physical signal of identity. If your persona is “luxury, date-night, confident,” then referencing scents, routines, and “real world texture” can strengthen the brand story—especially when you sell higher-ticket offers, customs, or VIP experiences. (You’re not selling perfume; you’re selling a coherent identity that fans feel.)
So the bridge between these links is not random at all:
- AI ranks fragrance preference using review signals,
- OnlyFans revenue scales because preference becomes repeat spending,
- OnlyFans stats show that spend is concentrated, so targeting and positioning matter more than raw reach.
6) A simple takeaway model
If you want one clean way to combine all three sources, use this model:
Preference → Packaging → Purchase → Repeat
- Preference: people have tastes (scent profiles, creator niches).
- Packaging: AI and content strategy turn taste into a clear promise (rankings, categories, positioning).
- Purchase: a subset converts (in OnlyFans datasets, a minority may drive most revenue).
- Repeat: the market becomes “big” only when repeat behavior is normal—hence headlines like Americans spent $2.6B in 2025 and similar reporting around ~$2.64B.
And that’s the shared lesson: the modern internet is built to measure desire, rank it, and sell it back—over and over.
