Data analysis that gets you a clear action plan
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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.

Get the full picture with high-quality insights
Our research team applies weightings to address any survey bias, and creates data segments for cross-tabulation.
We canvas your data to identify trends, benchmarks, and opportunities for you to take action.
We categorize hundreds of long-form qualitative comments into themes and apply our sentiment analysis technology for easier classification.
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.
Get an estimateSampling on social networks is what makes Potloc different
Compare it to traditional research methods
Main features | Online Panel (CAWI) | Phone survey (CATI) | Intercept survey | ||
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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?
keyboard_arrow_downHow do you address biases related to the use of Social Networks?
keyboard_arrow_down- Coverage bias: Since we use social networks to target consumers, we definitely need them to meet certain conditions. They must have access to the internet, have a social media account, and be an active user. However, Canada’s adult population is 28.1M and 24.3M of them are active on Facebook. Coverage bias affects older populations as well so we might see an under-representation of men, older people, and less-educated people or with a low socioeconomic status.
- Facebook’s ad algorithm bias: Facebook’s advertising tool algorithm is set up in order to minimize cost-per-click (CPC). It basically pushes our survey ads primarily to the least expensive audiences. This might show an under-representation of men and older people.
- Cognitive load bias: Answering a 6-8 minute survey online is demanding from a cognitive standpoint, so some people might find the task too difficult to complete. This might result in an under-representation of older people, and less-educated people or with a low socioeconomic status.
- Self-selection bias: Unlike web panels, we have to communicate on the subject of the survey. People who click on our ads have an interest in that specific subject. And we never offer any incentives to respondents. People who complete our surveys do it because it matters to them that their voice is heard. So, what do you think is worse: Having respondents naturally interested by the subject vs. respondents seeking incentives? We think this actually increases our data quality.
All methodologies have a bias, few are transparent. We address survey bias head-on by sampling enough people to ensure we hit the targeted quotas.
For example, it is known that women answer more surveys and social media platforms have a higher representation of young people. However, it surprises most that there are sufficient elderly people on social media to collect needed responses.
Traditional survey methods like phone, intercept or web panels, apply weight to their results and are not transparent about the impact on the data collected.