Last night we released an update, which allows users to drill down into the Air Segments Advance Purchase graph and the Average Ticket Price Comparison to Lead in Time graph in the Air Spend dashboard.
This feature allows users to understand the relationship between the types of fares booked (i.e. fully flexible and restricted economy airfares) and how far ahead travel is booked. The hypothesis is, the closer you book to the departure date, the more expensive the fare will be i.e. travel will be in a higher fare class. Now you can test this.
Click on the Bars
When you click on the bars within the graphs, the drill down refreshes to display the fare type description. You can then click on the fare type description to display the actual class of travel (see below).
The Air Segments data is based on individual segments within the itinerary, and the Air Spend data is based on the first segment of the ticket.
When a change is made to a booking requiring the ticket to be reissued, most travel management mid office systems have the ability to tag the transaction as an exchange or an additional collection (adcol). If they can do this, and more often that not they can, we are able to update the original policy code to ‘Exchange Ticket’ when we import data into Travel Analytics.
Identifying exchange tickets in this manner, allows Travel Analytics to display the data in the policy compliance chart within the Global Dashboard, making it simple for the customer to find information on changes.
Moreover, when the customer clicks on the Exchange Ticket segment within the chart, a table opens with a list of all the changes, including: booking reference, traveller name, airline and the cost. And they can even download the data into Excel.
It is a great feature, and a fast way for customers to access the data they required to understand the cost of changes to the business.
The accommodation dashboard has two options to download data. The first is the Accommodation Spend Data download, which provides a comprehensive data set if you want to do a warts and all interrogation of the customers hotel data.
However, if you only want a summary of the spend, including: location, hotel name, room nights, spend, average nightly rate and preferred flag, then look no further than the second option – Spend by Hotel Excel download.
It is a great way to get the data you require quickly without having to set up pivot tables to do it.
When you select ‘International’ from the trip type filter on the Air Segments dashboard, the chart in the top left of the dashboard displays the number of trips – or stopovers (if we use industry jargon) – within a country i.e. USA, China, United Kingdom etc.
And if you click on the individual countries displayed in the chart, a list of cities (destinations) will appear.
The question is how do we determine a destination or stopover? We use the recognised industry (IATA) standard; any break in a journey for longer than 24 hours is regarded as a stopover.
Fortunately for us, the air segment data we receive from the Travel Managers makes it easy to calculate a stopover, as they provide us the date, arrival and departure times of each segment within the itinerary. This allows us to calculate the order the flights to determine if the traveller spent longer than 24 hours at a destination.
So when your travel insurance premium is up for renewal, simply log into Travel Analytics and navigate to the Air Segments dashboard, and all the information you need on the number of trips to countries throughout the world is there at your fingertips.