Qualitative comments organized into themes
We interpret the data for you
The most challenging part of any research is interpreting the results. We separate what you need to know from what’s merely interesting to know. As a partner in your success, we 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.
Quality and quantity, you can have it all
We categorize hundreds of long-form qualitative comments into themes.
Impact analysis, understand the result of inaction.
Guaranteed quota sampling to address any survey bias.
Segments for cross-tabulation designed by our research team.
Why research experts are making the switch to Potloc
Compare us to traditional research methods
|Main features||Web panel||Phone survey||Intercept survey|
|Geotargeted retail trade areas||check_circle_outline|
|Respondents sourced via social networks||check_circle_outline|
|Supports use of media in survey||check_circle_outline||check_circle_outline||check_circle_outline|
|Survey designed for mobile devices||check_circle_outline|
|Comparative stats over time||check_circle_outline||check_circle_outline||check_circle_outline||check_circle_outline|
|Low cost per respondent||check_circle_outline Get a live comparison||check_circle_outline||check_circle_outline|
Frequently asked questions
How do you process data?keyboard_arrow_down
How do you address survey bias?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.