SurveyMonkey is the world’s most popular survey platform, and our original research is fueled by the millions of people who take user-generated surveys every day. Our research team has the unique opportunity to ask for their views on evolving trends and current events—and get unmatched insights.

Over 1.5 million people take user-generated surveys on the SurveyMonkey platform each day. We select a random sample to voluntarily take part in our research surveys. We call this our "river sample," a type of non-probability sampling. 

After completing their initial user-generated survey, respondents see a “thank you” page inviting them to take an additional, optional survey. These are created by SurveyMonkey researchers and are often conducted in partnership with media outlets and other organizations.

Some of our surveys are recurring, running quarterly or yearly. Others are one-time, topical surveys about current events such as elections. 

While most questions included in our surveys are shaped by a specific research topic, we always ask respondents about their demographics, including gender, race/ethnicity, age, geography, and education. This allows us to weight results to be representative of the overall population and dive deeper into what specific groups think about a topic.

We have several weighting schemes that we use depending on our sample size and population of interest. We require all respondents to answer the survey questions used for weighting. 

We use the Census Bureau’s 2019 American Community Survey (ACS) to generate estimates that reflect the most up-to-date demographic composition of the US in terms of age, race, gender, education, and geography. 

To construct national weights, we perform multi-stage raking—the standard weighting method used by Pew Research Center, as well as many public pollsters and market researchers. We first define state/division geographic units according to state-level population sizes and Census division classification. States with more than five million residents are defined as stand-alone units, while smaller states are grouped together within a Census division to form secondary geographic units.

At the first stage of raking, the sample is weighted to adult population sizes of state/division geographic units to generate initial weights. The second stage of raking adjusts the initial weights by gender, age, race, and education within each Census region to match targets obtained from the ACS.

For national weighting outside the US, we typically use estimates from the Organization for Economic Co-operation and Development (OECD) to adjust for age and gender.

SurveyMonkey research surveys don't have a probability-based design, so we do not report a margin of error term. (Only surveys that use probability-based designs can calculate and report a margin of error estimate for each statistic they produce.) 

Instead, we utilize a “modeled error estimate.” This is calculated using a bootstrap confidence interval, which has the same interpretation as margin of error. In all our blog posts or reports on our original research, we’ll always include a methodology statement with information on when the survey was in the field, the total number of respondents, a brief description of our weighting, and the modeled error estimate for the survey.

Note: Our research surveys are generally administered to our river sample, not a panel. SurveyMonkey customers do not have access to our river sample, but can tap into our platform’s integrated global panel of respondents anytime. Our methodology statement will always indicate the way we obtained our sample of respondents and weighted our results.

Keep up with our latest research, including ongoing studies and fresh insights for business leaders.

Small business confidence: Every quarter, in partnership with CNBC, we ask small business owners about their business environment and expectations for the future. (See all CNBC|SurveyMonkey research)

Workplace trends: From work culture to hiring strategies, our research uncovers how people are working—and what you can do to stay ahead.

AI trends: Stay ahead of critical AI developments, understand who’s using AI and how, and get insights to adjust your strategies.

Explore more research

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