Why US members see more studies than everyone else

If you join a survey or research panel from the United States, you will usually get more study invitations than someone who signs up from Singapore, Portugal or Kenya. Same app, same signup form, same effort. The difference is where you live, and it is built into how the whole industry is funded.

I run my operations from Singapore, so I see this from the wrong side of the gap. This article explains what is going on in plain terms, so you can set realistic expectations before you spend a weekend wondering why your dashboard is empty. Nothing here is a promise of income. It is a description of how supply and demand work in this corner of the internet.

what it is

The effect is simple to state. Panels and survey marketplaces send studies to members whose profile matches what a paying client asked for. Most paying clients ask for people in the US. So US members match more studies, more often.

Three terms help here:

• study: one survey, task or interview that a researcher wants completed
• quota: the number of completes a researcher needs from a specific type of person, such as US adults aged 25 to 34
• targeting: the filters a panel applies so that only matching members get an invitation

When people say “US members see more studies,” they mean the invitation volume per member is higher, not that US members are treated better. It is a demand story, not a favouritism story.

how it works

Follow the money backwards from the survey in your inbox.

A company, university lab, agency or political group wants answers from a particular kind of person. They go to a panel or a marketplace (Prolific, Amazon Mechanical Turk, Dynata, Cint and others are the well-known names) and buy completes. They specify who they need, how many, and how much they will pay per complete.

The panel then does three things:

1. it checks its member database for people who match the targeting
2. it sends invitations to a slice of those people, often more than the number of completes needed because not everyone responds
3. it closes the study once quotas fill

Notice that the panel can only invite people it has on file. A researcher who wants 500 US adults needs a pool of US adults. A researcher who wants 500 adults in Singapore needs a pool of Singaporeans, and the pool is smaller, the buyer list is shorter, and the quota gets filled faster relative to the number of members waiting.

the buyer side is lopsided

A large share of commercial market research, academic psychology, product testing and polling is commissioned by organisations based in or selling into the US and a handful of other rich markets. If you want a sense of how big and concentrated that world is, ESOMAR, the global market research association, publishes industry material and codes of conduct that show how the sector is organised.

Academic researchers matter too. Many of them draw on US participants because their ethics boards, funding and target populations are US based. Prolific describes its participant pool and screening tools on its site, and you can see from the filter options how often “country of residence” is the first thing a researcher picks.

the supply side is the other half

More US members also exist on these panels, but that does not cancel the effect. Demand per member is what counts. If US buyers want far more completes than there are US members to supply, each member gets more invitations. If a smaller country has a thin buyer list and a modest member count, each member gets fewer.

There is also a data quality angle. Buyers know that survey fraud is a problem, and some of them restrict to the US precisely because they believe it is easier to verify identity and screen out bad actors there. That is a buyer belief, not a guarantee, but it shapes the filters they pick.

payment per study follows the same logic

Researchers in high-income markets can usually afford to pay more per complete, partly because their own clients pay more. That is one reason the same task can pay differently depending on panel and member location. I go into that in why the same study pays more on one panel than another.

why it matters

This is not trivia. It changes what you should expect and how you should plan.

• expectation setting: if you live outside the US, a quiet dashboard does not mean you did something wrong. It often means there are simply fewer studies targeted at your country. I wrote a companion piece on exactly this from the other side, why Singapore sees fewer surveys than the US.
• time budgeting: if invitations arrive in bursts, you cannot count on a steady supply. Members in high-demand countries can sometimes check a few times a day. Members elsewhere may see long gaps. Plan around the gaps instead of refreshing constantly.
• shortcuts that backfire: the obvious thought is to pretend to be in the US. That is a bad idea for reasons I cover below, and it can end with a closed account and unpaid balance.
• panel choice: some panels are heavily US weighted, others lean toward the UK, Europe or global samples. Picking a panel that actually has buyers for your country matters more than picking the one with the loudest marketing.

common misconceptions

“US members are paid to be loyal, so they get more studies”

No. Loyalty programmes exist on some panels, but the volume gap is mostly about buyer demand. If you are curious what loyalty and tier systems actually change, bonus tiers and loyalty levels: what they really add walks through it.

“if I use a US VPN I will see the same studies”

This is the one I would push back on hardest. Panels check more than your IP address. They compare your profile answers, device signals, payment details and behaviour against what you said at signup. A mismatch is exactly what fraud systems are built to catch. Most of the time a VPN makes things worse, not better, and I explain why in VPNs usually make it worse. Misrepresenting your location can also break the panel’s terms and lead to a ban. See why survey accounts get banned for the usual triggers. This is not legal advice, so read the terms of any panel you join.

“the panel is hiding studies from me”

Almost never. The panel earns when studies complete, so it wants to invite everyone who matches. If a study does not show up for you, the likeliest reason is that your profile did not match the targeting, or the quota filled before your turn. Panels do not gain anything by holding invitations back from qualified members.

“more studies means more money”

Not automatically. Invitation volume and earnings are different things. A member who gets many invitations but screens out of most of them spends time without payment. A member with fewer invitations but good matches can do better per hour. You can measure your own rate without trusting anyone’s claims: note the time you spend on each study, including screeners and the ones that disqualify you, add up the payments the panel shows in your account, and divide. Do that over a couple of weeks and you have a number that is yours, not a marketing figure.

where to go from here

If this explained your dashboard, these are the natural next reads:

• the Singapore side of the story: why Singapore sees fewer surveys than the US, which covers what a smaller market looks like in practice
• pay differences between panels: why the same study pays more on one panel than another
• device choice: mobile versus desktop, which device sees more studies, because some studies are restricted by device type and that affects what you can open
• cash out rules: why payout thresholds exist, which matters more when invitations are scarce and balances build slowly

You can also browse everything on the blog index.

The honest summary is this. US members see more studies because more buyers want US respondents, and panels follow the buyers. If you are outside the US, the practical move is to choose panels that serve your country, keep your profile accurate, and measure your own hourly rate before deciding whether it is worth your time. If a panel ever holds back money you are owed, that is a separate problem, and when a panel withholds payment covers what to do.

Written by Xavier Fok

disclosure: this article may contain affiliate links. if you buy through them we may earn a commission at no extra cost to you. verdicts are independent of payouts. last reviewed by Xavier Fok on 2026-10-05.