Roy Morgan wins three-year contract to deliver domestic tourism statistics for Austrade
From 2025, Roy Morgan will provide Austrade with the world’s best practice survey methodology, big data integration and modelling techniques to deliver accurate domestic tourism statistics.
Roy Morgan has reimagined the future of domestic tourism statistics to move Austrade and its stakeholders to the forefront of tourism intelligence with a new platform that will drive the future of Australia’s tourism industry, estimated to be worth in excess of $160 billion.
Portia Morgan, Head of Client Services at Roy Morgan, says:
“Using face-to-face interviewing, which is the gold-standard for surveying the population, enhanced with big data and cutting-edge data science techniques, Roy Morgan will be delivering a future-proofed system that will be cost effective, reliable, and accurate.
“Roy Morgan has been delivering survey-based tourism insights via our Holiday Tracking Survey for 20+ years and we are thrilled to be working with Austrade and the broader industry to provide a deeper of understanding of how many people are travelling, where they go, what they do and how they spend their valuable tourism dollars.”
Collected and distributed via Roy Morgan’s Single Source program, these critical tourism metrics will now be actionable for media agencies and media publishers, and connected with deeper profiling insights such as Helix Personas, enabling more targeted and effective marketing campaigns.
For comments or more information please contact:
Portia Morgan
Head of Client Services, Roy Morgan
Email: askroymorgan@roymorgan.com
Office: +61 (3) 9223 2436
Mobile: 0421 058 572
Margin of Error
The margin of error to be allowed for in any estimate depends mainly on the number of interviews on which it is based. Margin of error gives indications of the likely range within which estimates would be 95% likely to fall, expressed as the number of percentage points above or below the actual estimate. Allowance for design effects (such as stratification and weighting) should be made as appropriate.
| Sample Size | Percentage Estimate |
| 40% – 60% | 25% or 75% | 10% or 90% | 5% or 95% | |
| 1,000 | ±3.0 | ±2.7 | ±1.9 | ±1.3 |
| 5,000 | ±1.4 | ±1.2 | ±0.8 | ±0.6 |
| 7,500 | ±1.1 | ±1.0 | ±0.7 | ±0.5 |
| 10,000 | ±1.0 | ±0.9 | ±0.6 | ±0.4 |
| 20,000 | ±0.7 | ±0.6 | ±0.4 | ±0.3 |
| 50,000 | ±0.4 | ±0.4 | ±0.3 | ±0.2 |
