Making the most of ski season with location intelligence

From expensive snow gear to delicious food and drink to high-end Christmas presents, consumer spending skyrockets in December. It’s also the time of year when skiers, snowboarders and other winter travelers get ready for their mountain getaways.

This high-spending group of winter sports enthusiasts are a coveted demographic for many brands across verticals. Hotels and ski resorts, airlines, mountain stores, outdoor recreation retailers, and winter apparel brands all want to reach these consumers to increase bookings and sales this winter.

But how can all these brands make sure they reach the right consumers—and stand out among the competition—during the busy holiday season?

Find the Snow-lovers

Mountain resorts and winter sports brands may know—in theory—who their ideal consumers are: from the mountaineer to the snow-lover, the casual skier to the hard core guy who lovingly waxes his skis after each use. The parents who introduce their kid to skiing at age four. The women who take a “girls’ weekend“ trip to the mountains each January. But how can brands make sure they’ve correctly identified these ideal consumers?

Location data can help brands identify and refine the right audiences this winter. For example, they can use historical location data to figure out which people went on a ski vacation last year. People previously seen at ski resorts and mountain-based hotels are likely candidates for a mountain getaway this year, too. An airline that flies into Aspen’s local airport in Colorado, for example, can identify the out-of-towners who flew in last year or stayed at a nearby resort.

To refine these audiences further, brands can continue to use historical location data in other ways. For example, a retailer like The North Face can use geo-fencing to find out which of the consumers who went on a ski vacation were also seen shopping with a competitor like Columbia or Patagonia.

Advertising in the Run-up to Ski Season

How can brands make sure their location data is working even harder to help them understand—and target—consumers? They can couple their location-based insights with other sources of data, including past purchases and search histories.

Let’s say a brand knows that a family-of-four stayed at a resort near the slopes in Killington, Vermont last year and visited a Patagonia location this November. This information may be enough to produce a pretty effective ad campaign, but there’s more the brand can discover about this family that can help them personalize their ads further. For instance, what they are interested in buying, and how old are the kids? By taking a look at the family’s online search histories and recent purchases, they may discover, for instance, that the family is in the market for snow boots for their 10-year-old girl and a six-year-old boy, or that dad wants a new set of skis while mom just needs another set of gloves. With such granular data, brands will be better equipped to serve personalized—and highly effective—ads.


Brands that get through to the mountaineers and winter sports enthusiasts this holiday season shouldn’t say goodbye once the vacations are over. Advertisers can follow up with these consumers long after the snow has melted to build and maintain relationships that will last all year round.

By continuing to use location data, they can gain further insights into the consumers, including whether or not they take advantage of post-Christmas in-store sales, how they spend their summer vacations, and what other sports they enjoy throughout the year. Such insights can help brands target these consumers during the spring, summer and fall—and give them a leg up the following winter. They can even give next year’s winter sales an early boost by offering early-bird booking discounts—long before most brands even start thinking about winter 2019.

The best part is, these real-world location and movement data insights can not only be used to help inform mobile marketing campaigns, but a brands overall marketing strategy.

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