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March 7, 2018

The impact of big data on the snow tourism industry

4 minute read

As the 2018 Winter Olympics come to a close and the UK recovers from a blast of icy Siberian weather nicknamed ‘the beast from the east’, snow is very much in our collective consciousness. This could be good news for snow tourism – businesses based around winter sports like skiing and snowboarding – which as an industry could definitely use the boost.

Snow tourism is a sector whose fortunes are inextricably tied to one natural and largely unpredictable factor; snowfall. Faced with the rapidly-changing climate conditions of recent years, snow tourism is suffering from less snow and the inability to predict it, contributing to an industry that is “overall rather stagnant, when not declining.” According to a 2017 study, snow-dependent businesses in the Alps could lose a huge 70 per cent of their snow cover by 2099.

Big data is beginning to revolutionise every market there is, but could it help the snow tourism industry recover? We’ve taken a look at the potential for big data to better predict snowfall in the future, as well as some of the other ways businesses in snow tourism are already using data to improve their services.

The power to predict snowfall is on its way

Snowfall is notoriously difficult for meteorologists to predict. Data-led modelling programmes have improved over time, but we’re still a way off being able to accurately forecast how much snow will fall and when.

To that end, NASA set up camp at the recent Winter Olympics in PyeongChang to research snowfall in mountainous areas in order to better predict snowstorms. Scientists analysed the amount and type of snow that fell in the run up and during the Olympic and Paralympic games, using data collected by instruments on the ground with satellite data and weather models to trial various untested formulas for snowfall prediction. As well as giving researchers information to take away and work with, real-time data was put to use straight away for the benefit of the games, helping Olympic organisers better plan events with approaching weather in mind.

Elsewhere, the National Oceanic and Atmospheric Administration are developing a climate model on an enormous scale to help predict snow accumulation (or snowpack) as much as eight months in the future. The model combines years’ worth of historical data in snowy areas on everything from ocean temperatures, currents and salinity to wind direction and atmospheric temperatures to identify potential weather patterns looking ahead. There’s still work to be done, but the hope is to predict mountain snowfall a season in advance, which means snow tourism businesses could finally provide reliable snowfall predictions that enable guests to plan their holidays with confidence.

Optimising the snow tourism experience with big data

Even though they don’t yet have the ability to accurately forecast snowfall, some snow tourism businesses are already using big data in other ways to enhance their guests’ experience.

In Vail, Colorado, ski resorts are making use of radio frequency identification (RFID) technology in guest tickets, allowing them to provide quicker and smoother movement around the resort, while also gathering invaluable data about how guests interact with the facilities, identifying any friction points that can then be addressed to ease queuing and congestion. Further to this, some resorts are using RFID data about their guests’ activities to personalise and ‘gamify’ their time on the slopes, combining the digital interaction of social media and the challenge aspect of a computer game to add a fun, competitive element to a ski holiday. Guests can create personal profiles and track their own stats on various runs, vertical feet skied and even the number of famous viewpoints they’ve managed to photograph, earning badges and points for milestones met. With each member of a group using the system, guests can compete with friends and family for in-game glory, and keep track of each other’s whereabouts out on the mountain. As a result, guests spend longer on the slopes, engage more extensively with the resort and are encouraged to return to vie for victory, and all while the resort collects data on guest preferences and how effectively its facilities are working.

Could ‘smart resorts’ be the future of snow tourism?

Bringing together current snowfall forecasting and an interactive information resource, a few resorts have already attempted to use big data to provide everything tourists may need in one solution. Montgenèvre in the French Alps is one such ‘smart ski resort’, where planners have drawn on a scalable ‘smart city’ strategy to give guests a one-stop app that includes real-time, customisable 3D maps, facility information, snow reports, avalanche warnings, and info on other leisure pursuits based on personal preferences, delivered through free resort-wide wi-fi.

Designed to make guest experience as seamless and cohesive as possible, the app acts like a digital personal assistant in your pocket, helping to foster a feeling of community, improve guest loyalty and boost the economic value of the town as a whole. At the same time, resort managers can analyse population flow statistics throughout the year combined with anonymised mobile data to continuously improve services for guests.

Over time, we’ll almost certainly see more big data in action within the snow tourism industry, and the scope for data-led services will become really exciting once scientists crack the snowfall prediction conundrum. As with any sector, big data has the potential to improve the experience of snow tourism for guests and businesses alike, helping to bridge the gap between what guests want and need and how businesses can deliver it.

Here at Quant, we specialise in using data to reveal new ways to boost business, whatever industry you happen to be in. If you’re curious how this could work for you, why not give us a call? We’d be happy to explain how we could put data to use for your business.

Posted by Pinar Dost

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The impact of big data on the snow tourism industry

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