Adam Roderick is a smart dude. I first met him at Mountain Travel Symposium this year, and have since learned just how much awesome stuff Aspenware, of which he is CEO, actually does.

Inspired by their work on EpicMix and ideas shared by Hotel Tonight’s Sam Shank, Adam put down his thoughts on what he feels are just some of the possibilities are that arise from tracking every skier on the mountain.

Here’s what he said about EpicMix and the future of ski data.

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Apps like these are awesome, but they are not the end of the rainbow. They are an important step towards something even bigger. It’s not about the social networking, the gamification, or even operational efficiency. Today’s technology enables companies to do things with their customer experience they have never been able to do in the past.

Phones and wearable devices tied to an individual make data collection possible like never before. Think about this. Where you are, how long you spend there, how fast you are moving, who you are with. Even data such as what you purchased (mobile wallet), what you looked at (e.g. Photos taken or barcodes or QR codes scanned).

All Together Now
Now, tie the mobile device data to data from other channels through single sign on providers like Facebook and Twitter, and you can start to see things like what you are interested in, who you communicate with, your sentiment and expertise around certain topics, your passions, your personality.

My point is that gathering data about where a person is and when they are there (such as when they board a chairlift) is just a beginning. Based on context, you can start to derive WHY they are there, and that context is what opens up all the possibilities.

Exhibit A
For example, if at 1pm the system sees Jake heading into the village at the base of the resort, and the system knows he has been skiing all morning, then we can assume Jake is hungry. Once we know WHY Jake is showing a certain behavior, we can direct him to a partner restaurant, or direct him to a restaurant that is unusually slow for the day.

If the system keeps purchase history, it can derive the type of food Jake will most likely be interested in, and make a personalized recommendation. String together a series of events like this, and Jake will have a wonderful, personalized experience throughout his day.

Exhibit B
Another example: If Shannon buys a day pass (data from the e-commerce or financial system) and is a first time skier (data from CRM or social network) but leaves after only two hours (data from mobile device), went extremely slowly down a blue run just prior to leaving (data from mobile device or wearable device), what does that tell us?

Shannon probably had a bad first day.

Next Step
Now that we know WHY she is leaving, we can take appropriate action to improve her experience with our product. By offering a refund and free ski lessons, we could convert Shannon from someone who may never ski again into a lifetime customer.

I’m sure from here you can imagine the possibilities within your company’s customer experience.

So although today’s hype is all about apps, what matters is the combination of the mobile device, contextual awareness, data aggregation, and data analysis. There are enough data sources–from internal business systems and external sources like social networks–and analytical tools that we can start to create personalized, almost magical customer experiences. Companies that think and act this way will be extremely differentiated and have an advantage over competitors who ignore the tech trends that are making this possible.

About Gregg & SlopeFillers
I've had more first-time visitors lately, so adding a quick "about" section. I started SlopeFillers in 2010 with the simple goal of sharing great resort marketing strategies. Today I run marketing for resort ecommerce and CRM provider Inntopia, my home mountain is the lovely Nordic Valley, and my favorite marketing campaign remains the Ski Utah TV show that sold me on skiing as a kid in the 90s.