Understand the real catchment.
Separate the nearby coast from the visitors who drive across the country, and aim outreach at the markets already making the long trip.
What one remote point of interest reveals about the whole journey: who makes the trip, how far they travel, and how the country's air network reaches them.
What one remote point of interest reveals about the whole journey: who makes the trip, how far they travel, and how the country's air network reaches them.
In a city, a pin on the map mixes commuters, residents and passers-by. At the end of a coastal road, almost every device made a deliberate trip to be there, which makes a remote point of interest the cleanest place to start tracing a journey.
What can one remote place reveal about the journeys that bring people to it, once we follow the signal beyond the boundary?
We draw a polygon around the sanctuary and keep only the devices seen inside it. That cohort, not the surrounding region, is who we follow outward.
What can one boundary tell us about a year of visitation?
observed inside the boundary
recorded across the year
on average, during the visit
A precise starting cohort: devices seen at one real place over one year. It is a sample of visitors, not a count of admissions.
Monthly devices rise into the December–January holiday season, and four in five pings land between 6 am and 4 pm: the shape of a planned excursion, not a daily routine.
When does the audience show up, and what does the timing say about the trip?
264–281 devices a month at the height of the year-end holidays
of pings fall between 6 am and 4 pm
Timing already hints at a trip, not a commute. The next question is where these visitors come from.
Where a device most consistently spends its evenings or days shows where the visit fits in the trip. It is an inferred, recurring place, not a declared home or work address.
The nearest cantons lead one by one, but more than half the cohort is based 50–100 miles away, largely the Central Valley around San José. For most visitors, this is a long trip.
A remote wildlife sanctuary sounds like a foreign-tourist stop. The signal says most of the audience lives in Costa Rica, and travels a long way to get there.
Is this an international attraction, or a Costa Rican one with an international edge?
devices spend their evenings in Costa Rica
of the cohort is based 50+ miles from the sanctuary
The domestic long-distance visitor is the core audience. The international tail is real but small, so treat it as directional until it is benchmarked.
Costa Rica's international seats funnel through two gateways, both hours from the Caribbean coast. The last leg of this journey happens by road.
from 56 origin airports
seats a year into Limón, most of them from San José
The airport nearest the sanctuary carries 13,668 seats a year, about 0.2% of the country. Access for this audience runs through San José, then the road. Linking airports to the cohort is the next step.
The same connected evidence answers a different question for each participant in the visitor economy.
Separate the nearby coast from the visitors who drive across the country, and aim outreach at the markets already making the long trip.
Place the sanctuary inside the wider Caribbean-coast itinerary, and see which communities take part in its visitor economy.
Compare the observed audience with the gateway network to frame where ground links or regional air service could shorten the journey.
The sanctuary starts as one point on a map. Once we define the boundary, read the visit, follow visitors to their common locations and lay the air network over the top, that point becomes a view of demand, origin, behavior and access.
The value is not knowing that people visited. It is knowing how far they came, when, from where, and what it took to get there.
A custom boundary separates true visitors from passers-by.
Timing shows when the audience shows up, and how.
Common locations connect the visit to where visitors are based.
Air schedules show how the market can physically reach the place.
DPAI connects visitor movement and aviation intelligence to turn an observed place into a decision-ready market story.

Managing Partner, Data Powered Aviation Intelligence (DPAI)
View LinkedIn profile →
Advisor, DPAI · Chief Commercial Officer, BermudAir
View LinkedIn profile →