ForwardKeys for DMO's is a platform for destinations, tourism boards, Conventions and Visitors Bureau, or any entity that is mandated with the task of marketing and promoting a destination. ForwardKeys is a tool and source of data for DMOs to quantify and qualify travellers flying to their markets. Daily update and future travels visibility brings the freshness required by marketers to permanently close the loop with the market, and anticipate market trends.
It is one thing to understand how many people are travelling and will travel to your destination. But there are many reasons why you also want to understand how many people will actually stay at your destination for every day, week or month. With ForwardKeys, you can quantify the amount of travellers that have been or will be staying at your destination. That information is very valuable for operation services, but is also a fundamental parameter to
Do you want to know, for a period of time I particular, if the Australians book sooner than the Japanese? Or if the Singaporean stay longer at your destination? Or simply how long Americans flying business class stay at your destination?
ForwardKeys will be a major source of information to analyze and monitor the behavior of lots of target group. Those findings will allow you to fine tune your future communication plans, and invest smarter to promote your destination.
ForwardKeys booking database includes reservation made for future travel dates. This information allows marketers to understand trends for future arrival dates. But ForwardKeys also includes an algorithm that forecasts future arrivals, that once compared to the number of hotel rooms available at destination, allows defining a future occupancy.
To forecast future arrivals, ForwardKeys algorithm uses a lot of information available in the database, such as number of travellers same day last year and previous year, pickup trends between current day and forecasted period for last and previous year, current pickup trends, and reservations completed. As a result, we can anticipate the number of travellers arriving to destination (within our sample of data).
Once we understand how many travellers are going to arrive at destination at any given date in the future, we can cross reference this information with traveller's respective length of stay (when available). That allows us to calculate how many travellers are staying at destination at any given date. That information can then be compared to the number of beds/rooms available at destination, to suggest an average occupancy across the market.
This information is not only useful to understand and monitor unconstrained demand against you market to adjust their occupancy forecasts at budget level, as well as adjusting rates and sales rules to reflect the reality of the market.