Rising customer expectations of memory and context
Biggest mistake we make with social media: going for the Like

The first two lessons from L.L. Bean

L.L. Bean has always been a leader in using customer data. When following, the challenge is to figure out what you can afford to imitate. They've been doing it since 1912, when the business was launched using a list of people with hunting licenses. Not just a group of hunters, but a list of men holding nonresident Maine hunting licenses. That's a very targeted list of people with cold, wet feet, and little preparation on how to avoid the discomfort.  Tq121119jb

The first lesson, I think, is that having a lot of data is less important than having strategic data you can use. The founder of L.L. Bean didn't even have a solution before he began. He just threw out a 'minimal viable product' which turned out NOT to be viable, but he offered a full guarantee and kept coming back to his customers with better solutions. 

The next lesson is to make sure that data is connected to people, and that you keep people in mind when you're using the data. Assume the diversity is an opportunity for personalization. Assume that people grow and change. Remember that people share that data because they trust you. Use the data for mutual benefit. 

Backchannel: Big Moose is Watching You, 2014-Nov-3 by Virginia Heffernan 

Superb data, superb marketing, boots in beta: That was enough to found a company on.

So it should have been no surprise — and still it was — to see mild-mannered Chris Wilson, Senior Vice President of something called Direct Channel at L.L. Bean, at the Javits Center in Manhattan this month, discussing data. Many in the audience — programmers from around the world — had never heard of the Bean boots. But they knew about the company’s ravenous appetite for data. Specifically, they packed the standing-room-only Bean session at the Strata + Hadoop World “Make Data Work” conference to hear about L.L. Bean’s 10+ TB on-premise enterprise data warehouse and its newer deployment of (still more extensive) cloud data, fully 100 TB, which can be collected and used in realtime by customer-service reps on the phone, online and in stores.

Also on stage was Doug Bryan, a data scientist from RichRelevance, which has partnered with Bean to a create a data-centric, single view of each online Bean consumer, as lavish and lifelike as a portrait by John Singer Sargent.

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