We don't provide sample

and you shouldn't want us to

Panel Samples

Sample from panels has long been the standard for market research, and until recently this has been an acceptable research method. You probably thought it was the best one until now. Not to worry—we’re here to help set you straight.

Better Survey Responses

The sample is supposed to be a sample of the target population—a group of people representative of the group you want to learn more about—however, most market research providers staff panelists to fill the demographic criteria you set. Why is this bad? You create a survey, they provide a sample, and you get the feedback, right? Here are three ways to get better survey responses by rejecting stock sample and embracing a fully end-to-end solution.


The goal of doing a survey at all is to gain insights that lead to informed decision-making — whether it’s selling a product, validating an assumption, or building a case backed by a supportive study. When the same group of panelists are called upon to respond to every survey, you’re limiting the diversity and integrity of your responses.

Panel-based research methods give you access to career panelists who have been preconditioned to have an unconscious, but positive, bias in their responses, making their answers less representative of the real consumer population you are trying to survey. Sometimes if a survey has many layered elements of targeting criteria, a traditional survey provider doesn’t have enough panelists to fill the criteria and needs to “buy sample” from other providers, bringing more career panelists into the equation that they know even less about.

The research is fundamentally flawed from the invitation and it results in lower data quality quality research than it would if you had gone for a wider pool of survey respondents who were not being paid to take surveys.

Our approach

Here is our approach: lose the panels

Pollfish’s respondent pool is made up of real people using mobile devices (basically everyone these days).

By tapping into real users in their organic environment, we are getting their rawest, most unfiltered survey responses instantaneously. And, since there are over half a billion people in our network, we can create extremely narrow targeting criteria, meaning we never need to buy outside sample to complete a survey.

Create a survey

User Experience

Now that you’re done with panelists, you have to reach real consumers. Real consumers have no agenda, are a much larger group, and, therefore, are a better option for collecting quality data. However, it can be hard to get enough survey respondents participants quickly enough to create a representative sample, which is how panels got started in the first place.

User Experience

The best way to build your own custom sample of real users is to use a survey platform designed with the user experience in mind. This means surveys should reach consumers where they already are—on their mobile devices—not send them to their inbox or a third-party site. A well-designed survey experience that is intuitive, fast, fun, and easy is the best way to reach the most consumers and the best incentive to win their participation.

Pollfish surveys were built from the ground up with the mobile user experience at the forefront. Surveys reach participants while they are in-app, meaning there is no disruption to their mobile experience. Designed for optimal delivery, length, and easy submission, the survey platform is designed as much for the survey-takers as the survey-makers.

Fraud Detection

At this point you’ve rightfully abandoned panels and understand the value of a survey designed with your target audience in mind, but you still need to ensure protection against fraud. While you’ve navigated away from unconscious bias with panelists, it’s still possible that you may encounter users who are impatient and click rapidly through, who write nonsense into open answer questions, or who choose a single answer throughout and didn’t provide real feedback to the questions.

With panels, insincere survey responses often cannot be discounted—it costs too much to find new respondents and onboard them into the process. They get paid either way, and it’s your data that suffers.

With an integrated application using AI technology, combined with a large enough pool of survey respondents, fraudulent responses can be removed without sacrificing sample size. Pollfish does this. Our proprietary machine learning algorithm and native mobile integration gives us a major advantage in detecting and preventing fraudulent responses across all 160K+ apps we work with. We collect unique user IDs to verify every respondent, monitor time spent on surveys, repetitive responses, and attempts to submit surveys more than once. With this advanced level of fraud detection and our massive network of respondents, we only accept real answers from real consumers and pass that quality data on to you.

Fraud Detection
Fraud Detection

This is why Pollfish doesn’t use sample

(and you shouldn’t want us to)

We target real consumers on their mobile devices, while they are engaged in apps they already have installed. Our natively integrated survey platform is unrivaled in fraud prevention, using our proprietary machine learning technology to detect and weed out suspicious responses. We’re obsessed with the user experience—and with a globally distributed network of over half a billion people, we have to be. We are reaching more respondents, in an organic setting, and with better fraud detection than any competitive survey provider. By surveying real users and rejecting sample, we gain better data from real populations, leading to better quality insights for you.

Make the switch and get better data by building your survey in Pollfish, and start collecting real insights instantly.

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