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No more flat, boring consumer reports

Dig deeper into your data by manipulating it on Potloc’s interactive dashboard: run data crossings, generate charts, reply to your respondent's comments, and clearly identify the actions that will drive meaningful change for your organization.

Potloc dashboard showcasing insights on competitive analysis, customer satisfaction, shopper's habits and where customers live

Consumer data, made easy


Visualize your data with our intuitive interface: Generate charts in your preferred format, see where your respondents are coming from on an interactive map. Go high level or as granular as you want.


Manipulate and filter your data: create cross-tabulations by social demographics, clientele typology, level of satisfaction, or any other metric you want to include in your study. Identify trends and leave your own annotations.


Spark a conversation: See respondent's comments, filter them by socio-demographic profiles and see where they are coming from on an interactive map. Identify key differences between trade areas or locations of interest.


Share results: export charts and graphs in .JPEG, .CSV, or .XLS, and use them in your presentations. Create a highlight page with only the results you want to share, or invite your team and external stakeholders by choosing the access level you want to grant.

A consumer research report that gets you answers.

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Explore our public dashboards:


Shopping behaviors in a Covid-19 world

How consumers are reacting in the face of a global pandemic?

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Public Studies
Man with mask

COVID-19 Canada

Giving a voice to Canadian health workers who are attending the COVID-19 crisis.

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Public Studies
Covid-19 Canada

The Remote Work Paradox in France

Effects of remote work on gender equality and the future of work

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Public Studies
Roland Berger

Frequently asked questions

The results of your study are available on our interactive dashboard. You can peruse your key insights at a glance, or dive deep into your respondent's socio-demographic profile.
Each survey can be shared with individuals in your organization by using the “Share” function in the dashboard, where you can choose the level of access you want to grant. You can also create a shareable page with just the key highlights of your study for a quick, simple, high-level glance, without all the granularity.
On the dashboard, you’ll find the initial survey along with a detailed socio-demographic profile of your respondents that includes maps with their location. You’ll be able to see results for each of your questions with charts and graphs that you can dissect and display in various ways, as well as your Net Promoter Score (NPS). Respondent’s comments are organized in various categories, and a “Key results” section outlines insights that help you get the big picture before you drill down into more specific results.
Yes, as many as you want. Understanding consumers should be an ongoing task and not just for when you’re in trouble. You can gather customer feedback over time and see your net promoter score (NPS) progress with each of your initiatives.
We acknowledge them! We know what biases we deal with and we know exactly how to address them. There are 4 types of survey bias when we launch a study:
  1. 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.
  2. 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.
  3. 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.
  4. 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 the quality of our data.

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.