Modalis

Public Opinion Panel

Modalis is your go-to resource for highly reliable public opinion and consumer research. There is no risk of AI bots or ‘professional respondents’ – just real people providing real answers.

Every Modalis panel member is recruited by telephone using random digit dialing sampling. All panelists speak with a Modus representative before joining the panel. Launched in 2021, the Modalis Public Opinion Panel was developed using the same exacting standards as our groundbreaking Modus Business Panel.

Benefits of Modalis
  • Results you can rely on. There is no need to qualify your results with disclaimers that say “if this were a probability-based sample” – unlike most research panels, Modalis is entirely probability-based.
  • Highly professional design, execution and analysis.
  • You do good by conducting Modalis surveys – each survey generates donations for registered Canadian charities.

Even with the superior data quality from Modalis, pricing is highly competitive.

Features of Modalis
  • Statistically projectable
  • There are no direct financial incentives to completing surveys. This eliminates a key incentive that drives fraudulent representation typically found in other panels.
  • Each survey generates donations for registered Canadian charities – conducting a Modalis survey does good.
  • Because every panel member is recruited via telephone, we can conduct live interviews with any panelist.
  • Modalis is mulit-modal. We can conduct research via telephone, email/online, text messaging and even in-person.
  • As Modalis is truly representative, we can generate robust samples of lower incidence groups (e.g., immigrants, rural)
  • Response rates exceeding 25%.
Why use Modalis?

The key advantage to an omnibus survey is the shared costs. By using a shared survey platform, clients can add proprietary questions while sharing the survey costs with others. We are meticulous about how we position client questions within our omnibus surveys. It is very important to mitigate any sequencing bias, a key potential weakness of using an omnibus.