BC Weekly Domestic Visitor Insights
Measuring Canadian Travel Patterns
Domestic Overnight Visitors - Year over Year Variation 2021 - 2022
June 27 2022 to July 3, 2022
The Measuring Canadian Travel Patterns research data created by Environics Analytics helps the Canadian travel and tourism industry understand the impact of the worldwide COVID-19 pandemic as it relates to Domestic Overnight Visitors within Canada, its provinces, territories, and tourism regions.
British Columbia Highlights: June 27 - July 3, 2022
Average Domestic Overnight Visitation to BC for Week 25 (June 20 - June 26, 2022) is up 10.7% compared to the same week in 2019
When comparing Week 24 (June 13 - June 19, 2022) to Week 25 (June 20 - June 26, 2022) Thompson Okanagan, Cariboo Chilcotin Coast, Kootenay Rockies, Vancouver Island, and Vancouver Coast and Mountains saw an increase in visitation. Northern BC, saw a decrease
British Columbia increased 22.2% when comparing Week 24 (June 13 - June 19, 2022) to Week 25 (June 20 - June 26, 2022)
Notes:
Data is based on the movement of mobile devices travelling within BC from BC or the rest of Canada who has spent one night 60 kms from their mobile device's home location. Therefore it includes all mobile movement - work and contractor travel, relocations within six months' time, visiting friends and relatives and people moving around their own regions.
The baseline of comparison is 2019, with percentages above 0% indicating higher rates of visitation in 2022 than 2019, and percentages below 0% indicating lower rates of visitation in 2022 than 2019.
Weekly comparisons may not reflect the exact same date between the two comparison years, especially now they are 3 years apart. Therefore holiday weekends may fall on different weeks and result in higher peaks in the current year.
METHODOLOGY
Environics Analytics uses privacy compliant, anonymized mobile movement data to identify devices whose Daily Common Evening Location is 60 km or more away from their Yearly Common Evening Location.
Data is aggregated and compared on a weekly basis versus the previous year and week.
Data is limited to devices that we can reliably infer their Daily and Yearly Common Evening Locations.
Data has been standardized and normalized leveraging demographic data and PRIZM, their neighbourhood classification system.
