Daytime Population is an authoritative estimate of the population that occupy a geographic location during daytime hours. This Esri Advanced Demographics dataset for Canada is sourced from data supplied by Environics Analytics.
The dataset consists of ten variables that differentiate between population at home and population at work. Daytime Population can be contrasted with Census data, which captures information about a region's nighttime population. All Daytime Population counts are based on Canadian DemoStats and Businesses data, as well as other verified sources.
Data source
Release: | November 2024. |
Data Vintage: | 2024 |
Data: | Data is provided by Environics Analytics. |
Base Level Geography: | Postal code. |
Geography levels
Daytime population variables are available at the postal code level of geography.
Daytime Population reference documents
Refer to the following reference documents:
Example use cases
Information about daytime population can be critical to retail strategists, market analysts, and corporate executives who wish to understand daytime demand, customer traffic, and population in their trade areas. This dataset could also be useful to urban planners and network analysts.
Sample questions that can be answered using Daytime Population data may include:
- What percentage of my trade area population are Daytime Population?
- What is the average age of my trade area population?
- What kinds of sites in my trade area have the highest daytime demand potential?
Example use cases for Daytime Population include:
 | Restaurant managers use Daytime Population data to determine potential demand for each location, helping them make informed decisions for daily operations such as adequate staffing, food supply purchases, and menu plans. |
 | Banking strategists use Daytime Population data to analyze their customers and determine which of their branches have high at-work or high at-home populations during regular business hours. This information helps marketing analysts and branch managers introduce targeted services and identify which branches might benefit from more ATMs. |
 | Healthcare providers servicing stay-at-home seniors use Daytime Population and PRIZM® market segmentation data to locate areas with a high concentration of people over age 65 who are at home during regular working hours. PRIZM® data helps providers communicate with those seniors more effectively. |