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Data Story Regional Destination Intelligence Program

Know how your region is really performing, sector by sector.

Destinations are data-poor. Operators rarely share commercial performance, so RTOs and DMOs steer on lagging indicators like arrivals and bed nights. This program builds a trusted, anonymised data pool across every operator sector, and turns it into a monthly read on how the region is trading.

Queenstown, New Zealand  ·  A monthly destination intelligence program for RTOs and DMOs
The gap

Destinations manage a visitor economy they cannot see

Individual operators hold the real commercial signal, and rarely share it. Destination managers are left with lagging public data, so marketing spend, destination management and the case made to government and investors all rest on intuition.

The program closes that gap by giving operators a benchmark against their peers, and giving the destination genuine visibility from the businesses actually trading on the ground.

What it is

A monthly, anonymised read on the whole visitor economy

Each month, operators submit a short, sector-appropriate return. It is anonymised, aggregated and turned into a shared intelligence report covering capacity, occupancy, yield, revenue trends and booking-channel distribution across the region.

Collect

Monthly operator returns

A short return per operator, under 10 minutes, tailored to each sector. Online form, CSV upload or a direct booking-system connection.

Anonymise

Trust built in

Identity is separated from data at submission. Nothing individual is ever published, only aggregated sector-level results.

Report

A monthly intelligence bulletin

A destination scorecard, sector deep-dives, booking-channel analysis and forward-looking demand, written for managers.

What it covers

Every operator sector, on one comparable basis

Operators are segmented into six sectors, each with its own metrics, so a winery is measured like a winery and a lodge like a lodge.

Accommodation

Hotels, lodges, holiday parks, serviced apartments, short-stay rentals.

Attractions & activities

Adventure, wellness and thermal, nature and wildlife, snow and mountain, cultural sites.

Food, beverage & hospitality

Restaurants and cafes, wineries and breweries, food experiences, bars.

Transport & transfers

Guided tours, scenic flights, water transport, rental vehicles, shuttles.

Visitor retail & services

Visitor centres, tourism retail, equipment hire and lessons.

Events & conferencing

Venues, event operators, incentive and corporate groups.

The metrics

The commercial signals that actually drive decisions

Universal signals from every operator, plus the measures each sector runs on, all indexed so no business ever discloses a raw dollar figure.

Occupancy and utilisation

How full the region is running, by sector, against capacity.

Revenue and yield, indexed

ADR, RevPAR and yield per visitor as an index against the prior year.

Booking-channel mix

Direct, OTA, walk-up and trade, so the destination sees where demand is flowing.

Lead time and demand pace

How far ahead bookings are landing, as a forward read on the next 30 to 60 days.

Visitor origin

Domestic against international, sector by sector.

Trading sentiment

Operator confidence against expectations, as an early signal of a turn.

Why now

An early read on how AI is moving bookings

AI search and AI trip planning are reshaping how travellers discover and book, and the shift is landing first in the booking channels.

The program tracks the split across direct, OTA and walk-up every month, so a destination gets an early, evidence-based read on how AI is changing the flow of bookings across its sectors, while the change is still happening rather than a year later.

Trust

Operators share because their data is protected

Confidentiality is the program's foundation. It is engineered so a single operator can never be identified in a result.

Never a raw dollar

Operators submit indexed values and directional signals, never absolute revenue.

Minimum of five

No sector result is published unless at least five operators contribute to it.

Dominance suppressed

If one operator would dominate a metric, it is suppressed or lifted to a higher level.

Identity separated

Names and contacts are split from the data at submission and held apart.

Who it serves

One data pool, four audiences

Operators

A benchmark against sector peers, so pricing, capacity and marketing decisions are made with evidence.

RTO and DMO leadership

Real visibility from the businesses trading on the ground, to ground marketing and destination-management calls.

Boards

A destination scorecard that tracks the region's health month on month.

Government and investors

Evidence to advocate for the region and to support the case for investment.

Rollout

From scope to a full monthly bulletin

A staged build that proves the model on a pilot cohort before opening to the full operator panel.

Phase 1

Foundation

Tailor the operator taxonomy and schema, stand up the secure pipeline, recruit a pilot cohort.

Phase 2

Pilot

Run the first monthly cycles, test collection and anonymisation, produce the first reports.

Phase 3

Full launch

Open recruitment to the full panel across every sector and publish the first full bulletin.

Phase 4

Optimise

Add booking-system integrations and build year-on-year trends as the data compounds.

Who builds it

Built by a tourism marketing agency, on real destination work

Data Story is a tourism and experience marketing agency working with regional tourism organisations across New Zealand.

Destination Queenstown WellingtonNZ Lake Wānaka Love Taupō Tairāwhiti Gisborne Horowhenua District Council