In this article, you'll find information to help interpret your ClickScapes Trends, ClickScapes Summary Profile, ClickScapes in Ranking Variables, and ClickScapes Extract reports in ENVISION; definitions for report headers and examples of what these mean.
ENVISION users can find this information without leaving the platform by clicking the "How to Read" button located in the top-right corner of your reports.
ClickScapes Trends ENVISION
Identify trends across individual mobile apps and websites, including interest categories, for Canadians.
The data are available for weekly and monthly time periods. The output contains data for counts of visitors and number of visit days for each variable across each time period selected. Two files are created for each area of interest selected: a PDF document and an Excel file. Both offer views of the same data points; the PDF provides trend lines, while the Excel file contains the corresponding data tables.
Visitors: The count of total households that visited a website, app, interest category, or company within the specified time frame.
% Chng Visitors - PoP: Percent change of visitors from one period of time to another.
Visit Days: The number of days a website, app, interest category, or company was visited in the specified time frame, including the total visit days for the time frame. The days reflect the total days and do not need to be sequential. The total number of days is represented in a separate trend line graph (Total Visit Days) as part of the PDF output.
% Chng Visit Days - PoP: Percent change of visit days from one period of time to another.
% Share of Visit Days: The proportion of total visit days for a time period for each selected website, app, interest category, or company.
In the example below, the website whirlpool.com welcomed 2587, 2273, and 2943visitors for January, February and March, respectively, in 2024. This corresponds to a negative percent change of visitors from January 2024 to February 2024 of -12% (((2273 - 2587) / 2587) * 100) and then a positive percent change from February 2024 to March 2024 of 29% (((2943 - 2273) / 2273) * 100).
ClickScapes Summary Profile ENVISION
ClickScapes Summary Profile - Variables
Combine several ClickScapes Trends variables together for a single week or month. Create your own custom categories or subcategories of websites/apps/companies/ interests within ClickScapes and understand the average number of days the sites were visited across the digital properties.
ClickScapes Summary Profile - Time Periods
Create a summary profile of one ClickScapes Trends variable for a combination of weeks or months. Combine time frames to align with your organization’s calendar, and understand the number of days in your time frame the site was visited.
SG: Each segment is assigned to one Social Group (SG) based on the urban-rural context, home language (English, French and non-official), affluence, family status, age of maintainer and ethnicity. The SGs are Urban (U), Urban Fringe (F), Suburban (S), Town (T), or Rural (R).
LG: The Lifestage Groups (LG) categorize household composition according to the presence of singles, couples and families. The LGs are Young (Y), Family (F), and Mature (M).
Code: Refers to the segment’s Socioeconomic Status Indicator (SESI): A composite ranking score based on factors such as average household income, discretionary income, educational attainment levels, dwelling value, average net worth, and household size.
Name: The name of the PRIZM segment.
Count: The number of daily visits made by each segment.
%: (Count/Total Count * 100) The percentage of daily visits made by each segment versus all segments.
Base Count: The total households for each segment in the benchmark area.
Base %: The percentage of the base count in the benchmark area within the segment.
% Pen: (Count / Base Count) The average number of visits per base count unit.
Index: ((% / Base %) * 100) Measures if the households or population in the segment are more or less likely to exhibit a behaviour when compared to the benchmark. An Index of 100 is average. Indices above 100 are above average or over-represented. Indices below 100 are below average or under-represented.
In the example below, the bar chart represents the Index value. Target Segments are usually identified by selecting segments with significant % and Index values.
For the Time Periods tool, the bar chart and values are based on the number of ClickScapes variables for the PRIZM segment composition for an aggregated set of time periods.
For the Variables tool, the bar chart and values are based on the number of individual month or week time periods selected for the PRIZM segment composition of visitors across an aggregated set of ClickScapes variables.
ClickScapes in Ranking Variables ENVISION
Count: The count of households in the selected input that visited a website, app, interest category, or company within the specified time frame.
%: For Visitors, this is the percentage of households in the selected input that visited a website, app, interest category, or company within the specified time frame. For Visit Days, this is the average number of visit days per household in the selected input for the website, app, interest category, or company within the specified time frame.
Note: Visit days are the number of days a website, app, interest category, or company was visited in the specified time frame (regardless of the number of visits on the same day). The days reflect the total days and do not need to be sequential.
Base Count: The count of households in the benchmark that visited a website, app, interest category, or company within the specified time frame.
Base %: For Visitors, this is the percentage of households in the benchmark that visited a website, app, interest category, or company within the specified time frame. For Visit Days, this is the average number of visit days per household in the benchmark for the website, app, interest category, or company within the specified time frame.
Note: Visit days are the number of days a website, app, interest category, or company was visited in the specified time frame (regardless of the number of visits on the same day). The days reflect the total days and do not need to be sequential.
% Pen: ((Count / Base Count) * 100) Of all households that visited a website, app, interest category, or company within the specified time frame, % Pen is the proportion that is found in the selected input.
Index: ((% / Base %) * 100) Measures if the households in the selected input are more or less likely to visit the website, app, interest category, or company when compared to the benchmark. An Index of 100 is average. Indices above 100 are above average or over-represented. Indices below 100 are below average or under-represented.
In the example below, approximately 49,813 households in Kingston, ON visit loblaws.ca in Q1 of 2024, which is 62.2% of the total households in Kingston. Of all households in the benchmark of Ontario that visited loblaws.ca (3,569,831), 1.40% were found in Kingston; this is the penetration rate. With an Index of 104, households in Kingston are about as likely to visit loblaws.ca as households in Ontario.
In comparison, looking at visit days, households in Kingston, ON spend approximately 247,615 days total visiting loblaws.ca in Q1 of 2024. This is an average of 3.09 visit days per household.
ClickScapes Extracts ENVISION
The ClickScapes Extract Tools provide comprehensive ClickScapes data as a downloadable .CSV report so you can take a detailed look at your Customer, Trade Area, and/or Target Group browsing behaviours.
Note: Depending on the type of extract, you may not see all of the below fields.
Order: Corresponds to the order in which the Variables have been listed in the variables list.
AreaName: The name of the Benchmark selected for the extract and where the home or mobile network is located. In a Trade Area extract, this is the name of the Trade Area selected for the extract and where the home or mobile network is located.
BaseAreaName: The name of the Base or Benchmark selected for the extract and where the home or mobile network is located.
TargetGroup: The name of the Target Group that this row of data applies to.
VarId or VarCode: The unique code identifier for each Variable.
VariableName or VarDesc: A description of the Variables selected for the extract, including the variable type (website vs. app), and URL visited.
Category or CatDesc: The category to which the website, app, or company is assigned.
Count: The count of visit days by the selected input for the website, app, or company in the Benchmark. Visit days are the number of days a website, app, interest category, or company was visited in the specified time frame. The days reflect the total days and do not need to be sequential.
PctComp: The proportion of the total selected input visit days for the category for the website, app, or company in the Benchmark.
BaseCount: The count of visit days by the total Benchmark for the website, app, or company in the Benchmark. Visit days are the number of days a website, app, interest category, or company was visited in the specified time frame. The days reflect the total days and do not need to be sequential.
BasePctComp: The proportion of the total Benchmark visit days for the category for the website, app, or company.
PctPen: The proportion of the total Benchmark visit days for the selected input for the website, app, or company.
Index: A measure of comparison between the proportion of visit days in the selected input and the proportion of visit days in the Benchmark. An Index of 100 is average. Indices above 100 are above-average or over-represented. Indices below 100 are below average or under-represented.
DateRange: The user-defined time period selected for the extract, in weeks or months.
In the example below, people in Kingston visited the Travel website airbnb.com for approximately 341,594 days from January to March 2024. For the entire Travel category, this makes up 4.27% of visit days for this time period. Comparatively, all visitors in the Benchmark (Ontario) contributed approximately 27,123,037 days to this same website, which is 4.56% of total visit days for this time period. Of all Benchmark visit days to this website, 0.0126% were from this Trade Area; this is the penetration rate. With an index of 94, people in Kingston are about as likely to visit this website compared to people in Ontario.
ClickScapes PowerBI
In this article, you'll find information to help run ClickScapes Power BI dashboards.
Three dashboards are available, although the Profile page is dependent on a PRIZM license.
You can export the dashboards to PowerPoint or PDF Formats with the Export button at the top of the page. For help and support on the ClickScapes Power BI dashboard, click Contact Support at the bottom of the page.
Using the ClickScapes Power BI Dashboard - Overview Page
When you open the ClickScapes Power BI Dashboard, you’ll see the overview page. The purpose of this page is to show the most popular websites or apps within a Tier 1 or 2 Interest Category and geography of interest. It will show who visits the most and the overall trend within the category.
Let’s review each section.
In the screenshot of the Overview dashboard, the dashboard is filtered to the CMA Geography Level, focusing on the Vancouver CMA in British Columbia. We’re viewing the Tier 1 Automotive category and using the Monthly. timeframe for November 2025.
We’ve filtered this page to show Websites (not Apps), and the metric displayed is % Change vs. Previous Timeframe, rather than the other option % Change vs. Previous Year. Year.
After selecting your criteria, the category summary at the top of the page displays your chosen ClickScapes category and time period. It shows that there are 511 websites in this category, along with the total number of Visit Days. The percentage shown under Visit Days represents the overall trend compared to the previous timeframe. In this example, there were 19.2 million combined Visit Days, which is 6.3% higher than the prior period.
On the right side of the page, you’ll see a simple trend line illustrating the all‑time number of Visitors to this category. Hover over the trend line to view the specific dates associated with each data point.
At the bottom of the page are details for the Top 10 Websites within our category of interest, ranked by Visit Days.
At the centre is a list of the top ten websites with the total Visit Days, the % Change from the previous time frame, and the total number of Unique Visitors with % Change. Clicking on a column header will re‑sort the data in ascending or descending order.
Clicking a website from this list will filter the results and refocus the Top 5 PRIZM Segments and Pie Chart for the specific website selected. Click the website again to return the results to the default.
On the right side are the Top 5 Segments. Click any one website to see which website are visited the most.
On the right is the Pie Chart showing each top website’s percent share of the category. Drill down into any one of the websites by clicking on it from the Pie Chart or the key. The PRIZM segments and Table will adjust accordingly. Click it again to remove the filter and return to the default view.
Drill down further into your analysis on the next two pages of the Dashboard.
Using the ClickScapes Power BI Dashboard – Trend Analysis Page
This page allows users to analyze the visitation trend of any app, company, website or Tier 1 or 2 categories over time. It can help answer questions such as:
- How did my recent marketing campaign influence traffic to competitor websites?
- How has the percent share of my website changed over time?
Your selections and filters from the Overview page are retained on this page. However, we will make some changes to the trends visualization. Let’s review each section of the Trends Analysis.
In the screenshot below, we’ve filtered the dashboard to the CMA Geography Level, focusing on the Vancouver CMA in British Columbia. We’ve drilled down and selected the Tier 2 category – Car Sharing from the Tier 1 Automotive Interest Category. We’ve selected Websites for our Type/Entity options and selected Quarters for the timeframe. You can choose individual company websites or Apps as needed.
View the trend by Count, Percent Share, Percent Change from the Previous Timeframe, or Percent Change from the Previous Year.
Choose to visualize visitation with all or a selection of PRIZM segments. And finally, use the slider to narrow your time frame as required.
The entities selected for the time frame appear on the chart and in the legend at the bottom. Hover over the data points to get more specific Visitor counts.
Using the ClickScapes Power BI Dashboard – Profile Page
This dashboard provides a PRIZM Profile of multiple entities, and aggregates Visit Days for a given time period. This dashboard helps answer the questions:
- What segments contribute the most Visit Days to my website or my competitors’ websites?
- What segments contribute the most Visit Days to an entire category of websites?
- What is the segment composition of Visitors to website or apps over a specific time frame?
While your previous Trend Analysis selections are saved for this profile page, you can adjust any parameters to tailor the analysis to your specific needs. While you can view the profile for all car-sharing websites in aggregate (from the Trends Analysis) in our example below, we are focusing on the Turo.com website. We have opted to view the Profile by Visit Days, not by Index.
This view makes it easy to see which PRIZM segments drove the most Visit Days to Turo.com over the selected timeframe.
Use Quick View to specify how you wish to view the profile – by Index ranges, Lifestage, Social Group or the Top N number of segments by their Index.
Finally, create Target Groups that reflect your strategy and analysis directly from this dashboard. Using the information from the profile, build your targets.
Each of your Target Groups are shown along with summary information about their Visit Days.
- Index = 100 → representation is exactly average
- Index > 100 → segment is more concentrated in the Target Group
- Index < 100 → segment is less concentrated in the Target Group
Count: The number of Visit Days contributed by the segment or Target Group.
%: (Count / Total Count * 100) The proportion of the Visit Days from each segment or Target Group.
Base Count: The total number of households in the geography.
Base %: (Base Count / Base Total Count * 100) The proportion of the total households in the geography.
% Pen: (Count / Base Count * 100) Of all households in the geography, % Pen is the proportion who are contributing Visit Days.
Index: (% / Base % * 100) Measures whether the segment or Target Group is overrepresented or underrepresented in that variable compared to the benchmark population.