Our membership categories include:
- Publishers (Newspapers and Magazines)
For more information on the category of membership your organization falls under, or to become a member please email us at email@example.com
Topline and summary results are available in the Member’s Area of this website upon each release. The full Vividata database is issued by our licensed software suppliers.
Scheduled release dates are:
|Scheduled Release Dates|
For information on the Fieldwork Periods for each release, take a look at our full Data Release Schedule.
One of the training resources we provide to our members is our Media School. The Media School guides you through the wealth of data available on our survey, the methodology behind the survey, and how to analyse, interpret, and communicate insights you gain from the data we provide.
We also offer customized presentations and hands-on workshops to our members. Our flexible in-person or online training allows us to tailor a program to suit your needs. To schedule training or to register for the Media School, please contact us.
For a complete list of the publications measured, take a look at our Markets & Publications page.
The new Vividata study has captured a sample of Canadians that is different from previous studies. Comparisons with Statistics Canada benchmarks indicate the sample is representative of the Canadian population. Respondents are recruited by home phone and cell phone, and oversampling of 18-24s is done by river sampling. The new recruitment methods ensure more complete coverage of residents living in multi-unit dwellings, those without a home phone, 18-24 year olds, and senior managers and professionals. Respondents are interviewed 7 days a week year round, and include even the smallest communities coast to coast.
Online panels consist of people who have been recruited for the purpose of completing many surveys over a long period of time. They are rarely a representative sample of consumers. Vividata contacts individuals using a random, probability based sample of over 40,000, age 12+ who are recruited ONLY for this study.
Respondents are invited to participate online, and are also provided with low tech options. Most choose the online option, resulting in a sample that is mostly internet-capable.
|7 Issues Per Week (Daily)||Read Yesterday|
|4-6 Issues Per Week||Read In Past 2 Days|
|3 Issues Per Week||Read In Past 3 Days|
|2 Issues Per Week||Read In Past 4 Days|
|Weekly||Read In Past Week|
|Biweekly||Read In Past 2 Weeks|
|Monthly||Read In Past Month|
|Bimonthly||Read In Past 2 Months|
|Quarterly||Read In Past 3 Months|
For daily newspapers, AIR is available for both weekday, and weekend (Sat/Sun) editions. The above is a generalized explanation of how AIR is calculated for publications.
The concept of recent reading is that someone counts as a reader of a publication if they have read any issue within the appropriate qualifying interval. Qualifying interval is “yesterday” for daily newspapers and “past month” for monthly magazines. Recent reading is the most commonly used methodology around the world. In the Vividata study, respondents are shown an image of the front cover logo and asked when they last read any issue of that publication.
The unduplicated audience of print and digital platforms.
To view a step by step guide on how to read a Vividata crosstab report, click here.
Allergy And Sinus Remedies: Personally used in past 6 months?
However, a number of the questions are based on the characteristics of the entire HOUSEHOLD. For example:
Food Shopping: Household shopped for groceries in past 6 months?
The default setting for weighting in the software is “Population”. However, when analyzing questions based on household usage, the weighting scheme should be changed to “Household”.
Jewellery: Personally bought in past 12 months?
Subsequent questions related to this category will only have been asked of those who “screened in” by answering yes. For example:
- Amount Spent
- Types Purchased
- Where Purchased
The initial filter question should be placed as a column when looking at data. This will provide more targeted data as non-users are being eliminated.