44M

Questions processed

179

Enterprise clients worldwide

9.2

Net Promoter Score (NPS™)

We translate raw data into business solutions for you

The most challenging part of any research is interpreting the results. As a partner in your success –and upon your request, we can crunch the numbers for you and create a digestible presentation of findings, so you can easily make data-driven decisions on the fly, and share the results directly from our platform.

People illustrations working on laptops and interpreting data graphs

Get the full picture with high-quality insights

check_circle_outline

Our research team applies weightings to address any survey bias, and creates data segments for cross-tabulation.

check_circle_outline

We canvas your data to identify trends, benchmarks, and opportunities for you to take action.

check_circle_outline

We categorize hundreds of long-form qualitative comments into themes and apply our sentiment analysis technology for easier classification.

check_circle_outline

Our experts deliver strategic recommendations and highlights that offer guidance for your decision-making process.

Discover sampling on social networks

Launch your next study via Facebook, LinkedIn, Twitter, and more.

Sampling on social networks is what makes Potloc different

Compare it to traditional research methods

Potloc
Main features Online Panel (CAWI) Phone survey (CATI) Intercept survey
Non-incentivized surveys check_circle_outline check_circle_outline check_circle_outline
Incidence rate < 10% check_circle_outline check_circle_outline
Geo-targeted areas, up to 1km radius check_circle_outline check_circle_outline
High data quality check_circle_outline
Guaranteed quota sampling check_circle_outline check_circle_outline check_circle_outline check_circle_outline
Non-customer analysis check_circle_outline Get a quote check_circle_outline check_circle_outline check_circle_outline

Frequently asked questions

How do you process data?

First, we clean data to ensure quality and robustness. Next, we ensure that it is a representative sample and we apply weighting where necessary to achieve acceptable minimums for the requested sample. Finally, we define robustness for analysis. Our expertise lies in defining which sub-samples are worth analyzing.

What statistical tests do you use to validate data significance?

We use a variety of statistical tests to verify if the sub-sample variation to the mean is statistically significant and relevant to your business problem. Some of these include but are not limited to, linear regression, key square test, correlation, and cross-tabulation.