Relevant and timely data is critical to support business decisions.
Improving data and insights is a priority of Australia’s long-term strategy for the visitor economy, THRIVE 2030. Our Tourism Research Australia (TRA) team leads this work. We are Australia’s official provider of quality tourism intelligence across international and domestic markets.
As technology advances, new data sources or 'complementary data' emerge. These new data sources offer insights traditional surveys can’t. They can strengthen or complement official statistics, like our National Visitor Survey (NVS).
We have started publishing monthly domestic mobility data, while we continue to publish data from the NVS. Mobility data measures domestic visitor movement. It is de-identified, aggregated mass movement across geo-locations using pings from mobile phones, Global Positioning System (GPS) and mobile applications (apps).
Check this page in the middle of each month for updated domestic mobility data. We report data from the previous month.
Mobility or movement data is one type of complementary data. It is a leading information source for a growing number of countries. This is because it is:
Governments can use this type of data to better understand movement of people. It can inform policy development, resource allocation and disaster response.
Our mobility data model measures domestic visitor movement. The model combines data sources including:
We have been Australia’s trusted authority on tourism data and statistics for 35 years. Our main data collections form part of Australia's System of National Accounts. The ABS uses our data as input to wider statistical metrics. This includes ABS metrics like exports and household expenditure.
We’ve partnered with data science provider DSpark on this domestic mobility data model. The model uses domestic tourism definitions recommended by the United Nations World Tourism Organization (UNWTO).
The graph below shows the close correlation between:
Domestic intrastate visitor nights by month, 2019 onwards
Data used in the model is de-identified and aggregated to preserve confidentiality and privacy.
We and our data partners do not use or receive personal identifiers for the input data.
Data has been extrapolated (modified) through benchmarking and imputation.
Estimates must meet minimal sample thresholds for confidentiality and data reliability. Where these thresholds have not been met, data is masked and not reported.
Data complies with guidelines from the Australian Government’s Office of the Information Commissioner (OIAC) and CSIRO’s Data61.