The travel and hospitality industry, with its innate spatial component is a top-10 growth driving industry for spatial analytics. An understanding of spatial patterns in people movements from the global to the hyper-local level is now critical for tourism stakeholders, such as state and local governments, attractions and major events, and even small businesses.
And the travel and hospitality industry isn’t simply leveraging the most common modern data streams in making investment and business decisions. The industry is also generating its own, uniquely useful data. This datastream can help those aforementioned stakeholders to make stronger decisions and harness the economic benefits that tourism uniquely provides.
The home sharing and and short-term rental market has exploded over the past several years. As of 2018, there were 23,000 vacation rental companies in the United States and 115,000 worldwide. The most well known of these companies, of course, is Airbnb. Estimates of the total number of U.S. ‘room nights’ booked through Airbnb in 2017 put the figure at approximately 108.1 million. According to Hotel Appraisers & Advisors, this number represents 8.1% of the total lodging market share in the US for Airbnb alone.
And the industry continues to grow! Airbnb is not alone in this market, with other players like VRBO (Vacation Rental By Owner), HomeAway, Tripping.com, and many more contributing to the growth of short-term rentals. Hotels too, despite their overall dominance of lodging market share and continued attempts at curbing short-term rental growth through lobbying for public policy changes, are recognizing that they need to compete on this new model as well.
Marriott, for example entered the market earlier this year with their Homes & Villas brand, which will operate in the US, Europe, and Latin America. And while this competitive development goes both ways (with Airbnb acquiring HotelTonight in March), what is made clear by Marriott’s adventures in short-term rental is that this new segment is not going away.
The great news for data scientists, analysts, and business decision makers across dozens of industries, is that short-term rental creates significant quantities of data that can and should be leveraged in spatial models for all sorts of decisions. In fact, a cottage industry of data providers and analytics firms, such as Transparent, have sprung up to help a wide range of clients as they look to make use of this data.
Learn more about short-term rental data from our webinar with TransparentCheck it out!
Applications for the combination of this new short-term rental data and the latest spatial analysis and spatial data science techniques are useful for many industries:
The 2019 UEFA Champions League final, one of the years most anticipated sporting events, took place on June 1st between English football sides, Liverpool and Tottenham Hotspur. The match was played at Madrid’s Wanda Metropolitano stadium, located in the city’s San Blas-Canillejas district, west of the city center, and was attended by 62,272 people.
Major events such as this, which are sure to draw significant tourism and traffic, provide an excellent opportunity to explore the utility of short-term rental data. Examining and analyzing the data, as Transparent did in this feature from El País, can help build post-event impact reports for the event planners, enable more efficient future event planning and logistics for cities, and inform business decision making in a handful of sectors.
The above map visualizes short-term rental capacity in Madrid. As expected, the number of short-term rental properties in and around the city’s center is high and significantly concentrated. But what the map also shows is how the short-term rental capacity within an hours walk of the stadium shifted dramatically in the run up to the event
Prior to May 2019, the short-term rental capacity within 60 minutes of the stadium was 95, and a fair percentage of that capacity is clustered at the western end of the 60-minute walk distance isochrone, closest towards downtown Madrid.
In May 2019, that capacity rose to 757, with short-term rentals far more evenly distributed throughout the districts around the stadium. Digging into the data further shows that the large percentage of these new rental properties that popped up are for single room rentals as opposed to whole house rentals.
This logically follows, as any residents in neighborhoods near the stadium were poised to make a quick buck in the run up to a major event. With short-term rental services, these residents get to jump into a market, previously inaccessible to anyone but hotels, and capitalize.
The beneficiaries of this new data stream are wide ranging, but the benefits start close to home. Short-term rental companies themselves can look at data like this in the wake of a major event and use it in several ways.
Cities and Governments, too, are clear beneficiaries of this data. They can use this new data stream to inform decisions and boost tourism plans, helping drive city revenue. Cities may also want to look at tourism and short-term rental data to manage resourcing of services. For example, in Madrid, this kind of data can allow the city to pinpoint increases in trash collection, police presence, traffic enforcement and more.
Traffic and mobility itself is also impacted by these major events. Understanding the volume of event visitors and their distribution around an event space can justify additional public transit and infrastructure to support traffic flow. This data can also be used in long term planning and projection for improvement and construction of transit infrastructure.
In Madrid, short-term rental data and details can also help with future major event proposals. Wanda Metropolitano Stadium has been involved in bids for both the World Athletics Championships and The Olympics in the past. This data can help inform and improve those proposals that have a massive impact on the city’s growth and international prestige.
The utility of tourism and short-term rental data is not limited to these sectors. As noted above, This data can be incorporated into real estate pricing models, taken into account by retailers and CPGs when making strategic point of sale decisions, leveraged by travel and hotel companies, and much more.
By 2020, it is projected that we will be creating 1.7MB of data per person on Earth per second. With so much data coming available, finding data streams that can be used intuitively to derive insights, and that can be integrated into modeling and spatial analysis is critical. The growing short-term rental field is a great example of new technologies and industries creating high quality data, that can help make decisions and can seed growth and advancement in multiple sectors.
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New data streams and analysis techniques are critical for industry growth today. Yet until recently, the Real Estate sector suffered from a lack of appropriate analytical t...Spatial Data
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