OnlyFans Spending by State: What the 2026 Forecast Means for Your Funnel

Reviewed September 11, 2026. The figures below are third-party forecasts. The campaign examples and recommendations are our analysis.

Where should an independent creator look for their next paying audience: the states with the biggest market, or the states where spending is highest relative to population?

New research gives those questions different answers. OnlyGuider projects US OnlyFans spending of $5.256 billion, up 8.9%, for FY2026: December 2025 through November 2026. That is gross fan spending before the platform's share. Source: OnlyGuider's US forecast.

The forecast attracted coverage from Vice Snob. For creators building their own websites, email lists, and referral funnels, its most useful angle is the gap between market size and spending per adult. That gap can suggest a test. Your own conversion and retention numbers must determine whether the test deserves more money.

Two rankings, two different questions

Largest projected state markets, FY2026:

1. California: $675.0 million.
2. Texas: $497.5 million.
3. New York: $341.9 million.
4. Florida: $325.4 million.
5. Illinois: $243.5 million.

Highest projected spending per 10,000 adults, FY2026:

1. North Dakota: $278,815.
2. Nevada: $272,126.
3. Colorado: $247,984.
4. West Virginia: $246,565.
5. Arizona: $245,779.

Both rankings come from OnlyGuider's state report. Colorado is third on the population-adjusted measure; West Virginia is fourth. The denominator is the adult population, not paying subscribers.

A large total suggests room to reach more people. A high population-adjusted figure suggests more modeled spending relative to the size of the adult population. Neither measure tells you how many people an advertising channel can actually deliver to your particular offer.

That distinction matters when deciding between a broad campaign and a smaller geographic experiment. A state can look attractive in a national ranking while providing very little relevant inventory on the specific channel you use.

Understand what is being estimated

OnlyGuider is a commercial creator-discovery publisher, not OnlyFans. Its methodology starts from Fenix International's audited global gross site volume and reported geographic revenue shares. It uses Google Ads API search volume for the brand keyword "OnlyFans" to distribute estimates geographically, then forecasts annual series with Google's TimesFM 3.0. Historical geographic estimates and future forecasts are therefore separate modeling steps.

The publisher describes short annual histories and mixed backtests: an older model performed better for some geographic groups, while a simple drift baseline slightly beat the selected model globally. It chose a consistent forecasting approach across levels. Using a Google model does not make this a Google-issued forecast. Source: OnlyGuider's global report and methodology.

Those details set the appropriate confidence level. An audited company total does not turn each downstream state estimate into an audited transaction count. Search activity is evidence of interest, but the relationship between searching and paying requires assumptions. A returning subscriber might spend without searching for the platform at all.

Before basing a substantial decision on geographic forecasts, ask whether the broad pattern remains useful if the exact ranking changes. If your campaign only makes sense when one state is precisely third rather than fourth, it depends too heavily on uncertain precision.

Also keep the business units straight. Spending attributed to a customer's location does not describe the earnings of creators living there. Gross purchases are not creator take-home pay, and projected growth does not promise that an individual account will grow at the same rate.

Why per-capita spending is easy to misread

The calculation is straightforward: estimated state spending divided by the state's adult population, multiplied by 10,000. It makes populations of different sizes comparable.

It cannot separate the number of paying customers from how much each customer spends. To see why, imagine two fictional towns with 10,000 adults each. In one town, 100 customers spend $200 each during a year. In the other, 20 customers spend $1,000 each. Both produce $20,000 per 10,000 adults. Their customer counts and purchase patterns are very different.

That is why a population-adjusted ranking cannot establish subscriber acquisition cost, average paying-fan value, or the probability that any particular resident will subscribe. It also cannot tell you which niche, price point, creator identity, or content format people prefer.

A useful planning note might say, "This market deserves a controlled test because the aggregate signal is interesting." A claim such as "People here are our biggest spenders" would require your own customer evidence. Geographic averages do not justify assumptions about individuals, political identities, relationships, or private interests.

Turn the rankings into a testable funnel hypothesis

Start with a question narrow enough to answer. For example: "On a channel that permits our offer, can a selected geographic audience acquire new paying fans at a sustainable cost using the same landing page and creative as our baseline?"

Keep your current working audience as the baseline. Choose one challenger with enough available reach to produce useful observations. Document why you selected it, whether the reason came from the national research, your own site traffic, a relevant partner, or a combination.

You do not need a separate page for every state. A useful landing page explains your offer, who it suits, what visitors can expect, and the next step. A genuine local connection can support the message, but a location label alone creates little value. Avoid pretending to live somewhere or manufacturing local testimonials to make an experiment feel personalized.

Think through the full path before buying attention: discovery, qualified website visit, an appropriate opt-in or offer click, paid-platform visit, first purchase, and a reason to return. Each stage has a different job. Our creator funnel explainer walks through that structure.

An email opt-in may be useful when visitors need more information before buying. It can also add unnecessary friction when someone is ready to subscribe. Test that decision against your offer and audience instead of adding a mailing-list step automatically.

Check the traffic source before designing the campaign

A promising state does not make an adult offer eligible for every advertising platform. Google's policy prohibits graphic sexual content and applies its rules to ads and destinations. Its wider policies also address cloaking and destinations whose sole purpose is sending visitors elsewhere. Google's graphic sexual content policy and advertising policy overview.

Plan around a channel whose current terms permit your actual business, creative, destination, and audience. A mild-looking bridge page is not a dependable way to qualify an otherwise prohibited offer. Evaluate the complete visitor journey, including the site you ultimately send people to.

Possible experiments include relevant creator partnerships, permitted adult advertising inventory, and placements with publishers whose audiences fit your offer. These are options to investigate, not blanket endorsements: each provider has its own rules, targeting capabilities, measurement, and inventory quality.

For an adult offer, keep the experiment within the channel's permitted adult audience and applicable access requirements. Set up geographic targeting through the provider's supported controls. Keep age-assurance information separate from marketing; a visitor's proof of adulthood is not a reason to collect extra targeting data.

Ask practical questions before paying: Can you actually select the geography? How is location estimated? What traffic-quality reporting is available? Can repeated exposure be limited? A national spending ranking cannot answer any of those questions for a specific supplier.

Measure the handoff from your website

Your own site gives you a place to explain your offer and measure interest. It does not automatically reveal what happens after someone leaves for a subscription platform.

Google Analytics documentation describes campaign parameters such as utm_source, utm_medium, and utm_campaign for identifying referring campaigns. Google's campaign URL guide. Use consistent labels, such as partner_a, referral, and geo_test_01. Keep names readable so you can understand the report a month later.

Those inbound labels establish where a website visit came from. They do not, by themselves, connect that visitor to a later purchase or renewal on another service. Use platform-supported attribution where available and record its limits. Keep an "unknown" category when a purchase cannot reliably be assigned.

Record campaign cost, qualified visits, outbound offer clicks, attributable first-time paying fans, and creator receipts for a defined follow-up period. Include refunds and chargebacks when they become known. Track your own incremental delivery cost as well, especially if an offer includes time-intensive personal work.

Use aggregate campaign labels rather than names, email addresses, or sensitive personal information in URLs. Geographic reporting should help compare campaigns without building unnecessary personal profiles. The goal is enough information to make a business decision.

A practical comparison: cheaper visits can produce a worse result

The following example is entirely hypothetical. It illustrates campaign economics; it is not a result from the state report or an expected return.

Campaign A: $400 in promotion produces 800 qualified visits and 20 first-time paying fans. Their first 30 days generate $480 in creator receipts after platform fees and refunds. Incremental fulfillment costs $120.

Campaign B: the same $400 produces 500 qualified visits and 25 first-time paying fans. Their first 30 days generate $700 in creator receipts after platform fees and refunds. Incremental fulfillment costs $175.

• Cost per qualified visit: A costs $0.50; B costs $0.80.
• Visit-to-paying-fan conversion: A converts 2.5%; B converts 5.0%.
• Customer acquisition cost: A costs $20 per new paying fan; B costs $16.
• Contribution after promotion and incremental fulfillment: A loses $40; B contributes $125, before fixed overhead and taxes.

The contribution calculation is creator receipts minus incremental fulfillment costs minus promotion costs. For A, that is $480 - $120 - $400. For B, it is $700 - $175 - $400.

On those receipts and fulfillment costs, the first-30-day break-even acquisition cost is $18 for A and $21 for B, before fixed overhead and taxes. A paid more than its observed contribution per fan could support. B paid less.

The example shows why clicks alone are an incomplete success metric. However, 20 or 25 customers would not prove a permanent geographic advantage. One unusual purchase can move a small cohort's result. Unattributed transactions, late refunds, different placement quality, and repeat purchases can also change the comparison.

Give every acquired cohort the same observation window: 30 days after acquisition, for example, rather than whatever portion of a calendar month remains. Exclude existing fans from the new-customer count. Treat future renewals as unknown until observed instead of assigning an optimistic lifetime value to make today's spending look profitable.

Run an experiment you can afford to learn from

1. Write the hypothesis. Name the audience, permitted channel, offer, and outcome you want to improve. Note why geography is worth testing.
2. Choose the comparison. Use the same creative, landing page, pricing, and broadly comparable timing where possible. Record unavoidable differences in placement or delivery.
3. Set a spending and loss limit. Choose an amount your business can absorb if the test fails. A state's share of national spending is not a sensible rule for allocating your budget.
4. Verify measurement first. Check campaign labels and the outbound journey. Decide what can be attributed, what will remain unknown, and how long receipts will be observed.
5. Review the whole funnel. Look for the stage where performance changes. Many visits with few offer clicks suggest a different problem from strong outbound interest with few attributable purchases.
6. Repeat before expanding materially. Use a second observation period to see whether the result persists. Change one major factor at a time so the next test answers a clear question.

If a small geography cannot generate enough relevant visits within your limit, broaden the experiment or choose another audience. Do not keep buying repeated exposure just to force a result. An inconclusive test is useful when it tells you that the available reach or measurement cannot support the decision.

Even a carefully managed comparison is not automatically a causal experiment. Different states can receive different inventory, auctions, device mixes, or delivery patterns. Record those differences and describe your conclusion narrowly: this campaign worked better under these conditions.

Use the research in your content without promising earnings

Market research can support an educational post, a creator-business presentation, or a conversation with a potential partner. Keep the source, forecast label, time period, and definition beside any number you reuse. Link to the primary methodology so readers can judge it themselves.

Separate the market observation from your offer. The research does not establish that your audience will earn more, that your service reaches the highest-value fans, or that a particular niche is underserved. Those claims need evidence about your actual product and customers.

For your own content calendar, the strongest follow-up might be an honest account of a measured experiment: why you tested an audience, what the funnel showed, what could not be attributed, and what you changed. That is more useful to another business owner than repeating a large national number without a decision attached.

Connect the map to a business you control

This is the kind of question planned for Book 3: Funnel & Marketing, which is upcoming: how discovery becomes interest, how interest reaches your home base, and how to evaluate the traffic sources feeding it.

You can start now with one page, one clearly described offer, and one measurable traffic experiment. Use the Net Income Calculator to examine the wider economics, and record platform and supplier exposure in your Dependency Inventory.

The state rankings give you a reason to ask better questions about geography. Build your next decision around what your own funnel can demonstrate: an audience you can reach appropriately, an offer people choose, and customer receipts that justify the cost of serving them.