Opticks Powered by Vividata (Gender)

Opticks Powered by Vividata (Gender) is Canada's premier gender-based behavioural database at the neighbourhood level. It offers over 6,700 variables for those identifying as male or female across 52 population-based categories. Respondents to Vividata's syndicated study from those genders are used to generate the lifestyle and media behavioural estimates that pertain to each group. Separating male and female data helps to answer two important needs:

  • Identify if men or women are more likely to purchase or partake in an activity.
  • Understand which female or male group is likely to do it more.

Note: While EA respects all gender identities, the current version of Vividata (Gender) only includes male and female genders. Limitations in reporting about other gender identities are primarily related to low sample sizes.

Opticks Powered by Vividata (Gender) helps companies, government agencies and not-for-profits better understand their customers for a range of media and marketing applications. Opticks Powered by Vividata (Gender) is an add-on option to our Opticks Powered by Vividata product, and users must be Vividata members.

Below are some additional resources linked for your reference.

What's New

This release of Opticks Powered by Vividata (Gender) introduces over 2,400 new variables for each gender. These new variables speak to themes such as advertising sentiment, travel attractions and travel events, as well as nearly 600 new psychographics including themes such as cannabis, sports betting and home décor/improvement.

ENVISION Tutorials

How-to-Read ENVISION Reports

Additional Resources

What you should know before using this data:

  • Opticks Powered by Vividata (Gender) was derived from all population-based variables from our Opticks Powered by Vividata product and modelled by gender.
  • Each Variable ID is appended with either “_M” or “_F” to denote male- or female-based variables, respectively.

The same data can be used to answer two different questions by changing the base variable. Total Household Population 14+ should be used as a base when trying to understand which male or female gender is most likely to score highest for a certain behaviour. If analysis and marketing campaigns are gender specific, Total Household Population Male 14+ or Total Household Population Female 14+ should be used as the base. For instance, CPG companies can use Opticks Powered by Vividata (Gender) to understand which female or male segments are more likely to purchase certain personal care products.

ENVISION uses Total Household Population 14+ as a default base for Opticks Powered by Vividata (Gender). To access the Total Household Population Male 14+ or the Total Household Population Female 14+ bases within ENVISION, we created custom tools and provided various options. These include:

  • Profile Variable vs Variable feature found within the Profiles – Variable tool. This feature allows users to select custom variable benchmarks. This can also be used for consumption profiles, where the users can select the appropriate male or female incidence variable as the base.
  • Variable Rankings Tools have been created for Trade Area, Target Group and customer-weighted reports.
  • Mapping with custom benchmarks can be done by creating User Defined Variables.
  • Executive Dashboards have also been made available.

Sample Size Considerations

  • Opticks Powered by Vividata (Gender) splits population variables by male and female, making it possible to have variables with low responder samples. To reflect this low sample reality, a new classification schema was developed. Users should always use low-sample variables with caution.
    • (!) is used to indicate survey responder sample sizes between 250-499.
    • (^) is used to indicate sample sizes that are less than 250.
  • Opticks Powered by Vividata (Gender) is weighted to Male and Female Population 14+. ENVISION reports provide this count in addition to the % Penetration and Index fields. As data users, it is important to consider all metrics instead of focusing solely on variables with high Index scores. Segments with small counts should not be used unless they are used for niche products or on a case-by-case basis.