Hospitality Sales

Source and partnership

The project was supported in part by MBIE’s Tourism Data Partnership Fund.

Tourism Data Partnership Fund

ANZ bank provided the aggregated card transaction data. DOT Loves Data modelled and curated the data. The project was coordinated through an industry partnership led by the Restaurant Association of New Zealand and Hospitality New Zealand.

Tourism Evidence and Insights Centre (TEIC)

MBIE will publish interactive elements for this dataset on the Tourism Evidence and Insights Centre (TEIC).

Tourism Evidence and Insights Centre(external link)

Access the interactive charts on the data release page:

Hospitality Spend(external link) - Tourism Evidence and Insights Centre

Overview of the data

This hospitality dataset offers a transactions-based view of hospitality spending and patron activity. It distinguishes between locals, domestic visitors, and international visitors. This breakdown enables analysis of transaction values, volumes, and selected customer demographics. 

Data coverage

• Dates range from January 2023 to June 2025.
• Geography is divided down to the Territorial Authority.
• Sales are aggregated by International, Domestic, and Local spenders.
• Categories include accommodation, cafés and restaurants, caterers, drinking establishments, and fast-food restaurants.
• Metrics include totals, proportions, medians, and averages.

Privacy

Anonymisation rules and aggregation

Each data point represents a minimum of 4 entities, and no single entity contributes more than 80% of any aggregation. This ensures that individual consumers or businesses cannot be identified.

Stability considerations

Data with more suppression may be less stable. Finer geographies, smaller segments, or recent months may more variable. Users should focus on patterns and trends rather than exact counts.

Data download and dictionary

As part of our ongoing commitment to supporting tourism research, this page provides the data publicly.

Data format and files

The data are in comma separated value (CSV) format as tables. This format is the most efficient way of organising the data as a database and is aimed at specialist researchers with statistical tools and skills. 
 

 
This work is licensed under a Attribution 4.0 License(external link) – Creative Commons

Future data releases

The next data release will contain twelve more months of data. This will be released in late 2026.