Virtually every consumer-facing travel brand is capturing critical data constantly from their site visitors but many are struggling to maximise its value says EyeforTravel and Datumize’s new Understanding Customer Behaviour Through Demand-Based Analytics white paper. This is because of the reams of information that are being constantly created across multiple channels and the need to be always on and live. These factors often prevent travel companies from getting down to the key metrics that matter and being able to fully extract and study them.
“Travel companies normally only have access to converted sales and aren’t able to track all the requests that customers are making though channels,” explains Datumize’s head of marketing Carlota Feliu.
“Some of them they can track, for example, through their own website. But the vast majority they are not capable of tracking this data with the technologies they are using. Everything that you want to do in demand forecasting starts with good data and good knowledge of your customers – without this, you won’t be able to understand demand, predict it, or increase it,” says Feliu.
She points to several key areas where brands can start to interrogate their data:
Inventory: Do you have the right offer at the right price in each area?
Availability: Do you have the stock available to action all requests, and in the right price range?
Experience: Are all software links in the chain performing as they should for a quick, smooth booking?
Vueling Airlines, a Spanish, low-cost provider, has around five million search queries a day, 50% of which come directly from customers and 50% from online travel agencies and other tour operators. But since its business goal is to answer all enquiries for a flight in a second or less, it was struggling to store and make use of all this demand data.
Jonathan Guerrero Corcho, innovation manager, explains that a Datumize solution – which monitors everything without adding any code to the main process or slowing anything down – means that the business can now understand more which kinds of routes and dates are most in-demand, with negligible noticeable effects to end users.
“We can see if a route is being asked for more times than we are operating on for those days and we can not only adjust the current schedule but we can adjust the next schedule,” he says. “We can say ‘this route is better to operate on Tuesday than Monday, as the numbers are saying that this route is more requested on Tuesday.’”
This kind of learning is particularly important for a business that does not operate the same flights each day, but a limited number of times a week.
- Real-world examples and case studies
- Industry survey data
- Data-based techniques and areas of focus that can improve business performance immediately
- Expert insight.
This white paper features insights from:
- The Travel Corporation
- Thomas Cook Hotels & Resorts