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Destination Marketing Organizations (DMOs) want to know everything there is to know about travelers but the most valuable data is normally only known to the companies guests purchase from.
This is why DMOs find it difficult to spot trends in the short term rental (STR) market and why they turn to STR data providers.
These companies collect a raft of valuable statistics on everything from nightly rates and booking windows, to stay lengths and where tourists are coming from. DMOs can use this information to design marketing strategies, and identify areas for improvement and investment.
The problem is that the areas opened up for analysis by short term rental data specialists are usually vast. In fact, most short term rental data companies only allow DMOs and property managers to study standardized areas at the state, county or zip code level.
Why Is This A Problem?
The largest US zip code by land area is in Alaska and it covers more than 30,000 square miles — that’s bigger than Ireland. And, as zip codes get smaller, their population density goes up. Chicago’s 99734 zip code has the most people on the US mainland with 144,000 souls.
In short, these huge, inflexible parcels of land prevent users from zooming down to the granular level they require. Even smaller zip codes will often straddle multiple zoning uses, with a single area containing tourist spots, residential, business and industrial businesses. This can confuse the picture for DMOs even more.
Custom Mapping
This is where Key Data’s custom mapping tool comes in. This tool sits with the DestinationData product aimed at DMOs and helps break down the barriers to useful information by allowing comparative analysis of much smaller areas.
It lets DMOs create their own geographic boundaries to compare the short term rental data for specific areas. This is especially valuable for urban markets like Los Angeles and Atlanta, where individual communities can perform very differently.
Tourist bodies can use custom mapping to divide their regions into areas that make sense. Users can create a bespoke boundary for each beach community, for example, and design others for each specific city center location in their target area.
Custom mapping means that rental data can be compared to similar destinations, even if they are not nearby. DMOs see how their beach location is performing against a similar region in another state. This granular data is at its best when it reveals shifting patterns within tiny parts of a city.
In April, we revealed the ten US rental destinations with the biggest year-on-year growth. It was no surprise to see the list dominated by four areas in New York city and another three in the wider state.
One of these locations – Turtle Bay – is less than half a square mile in area, meaning that tools that rely on zip code level data would completely miss important trends.
A proactive DMO will subdivide this small area to see if certain parts are more popular than others. They could test whether locations near the East River are more popular than those closest to Central Park. And what’s the difference in average daily rates (ADR) between the north and south sides of Turtle Bay? You can do this with Key Data’s forward-looking data too.
In Summary
Examining customer trends at the macro level has its value, but being able to put specific competitors under the microscope is where the most valuable insights start to emerge.
Custom mapping allows DMOs to compare the performance of short term rental assets in their area to competing destinations by taking data analysis to the next level. Users can spot trends that they can apply to their wider portfolio, informing decisions on where, when and how to market to the travelers they really want to attract, and how to help their local property managers do the same.
Want to see how Destination Data and its custom mapping tools could supercharge your short term rental strategy? Book a demo with a member of our team today.
