Making Smart Use of Data


Data

It starts with knowing why you're collecting it — understanding what matters. That drives you to figuring out why the experience hits the mark. Increasingly, by experience we mean the full Monty — multichannel and multi-touch, if you'll indulge me in buzzword bingo.

Most compelling data

By far, the most compelling data, the kind of metrics that appeal to people beyond the marketing suite, is data about self. Because it's tied to identity, and value.

Behaviors are one of the components that shape identity, along with
context
. A source of feedback that allows someone to tweak how they're
doing based upon data points ends up igniting a couple of key components
of personal drive: mastery, and purpose. There is no limit for better in this system.

Doc Searls has been on a roll lately and this post on what people can do with data that companies can't tops it. One application for retail, where I've been spending a lot of time recently, thinking about facilitating experiences across environments — online, in-store, and on the go.

Think of what you could do if you had all your spending in electronic
form, and not just on paper receipts and invoices, or buried ten clicks
deep on Web pages  You could look for ways to spend less money, or spend
it more wisely.

You could share back some of that data to retailers
whose loyalty programs wear blinders toward what you’ve bought
elsewhere: intelligence that might get you more favorable treatment from
those retailers
, while also providing them with better market
intelligence.

It appeals to me.

While on one hand I'm a market of one, I don't know anyone who would push back at better offers and treatment. Do you? It's a give and take — and you start with the giving part. I'm shocked to see how few do it.

Why does Lufthansa not know me every time a book a flight? I use the Miles and More program. They must not know me, or it would be incredibly rude to not award me miles when I submitted vouchers its staff gave me to three sites! Dumb systems, aren't they?

I know where I am better than their back end system.

Best predictor of success

Test, test, test. Then test some more to optimize the experience.

Hypotheses are just that, theories. Go get yourself some proof by looking at the data after figuring out which data matters beyond right here, right now.

If you've been the victim of premature cancellation of a program, you know what I'm talking about. You've seen your competitor sail by and take the lion share of sales.

It's a mistake not to disprove assumptions. Take a look at this example on pricing models published at Jason Cohen's blog. Counter-intuitively, sometimes the best approach is right in the middle.

When it comes to pricing, people's valuations are based upon their own systems and anchors. Have you ever found yourself in a situation where you would have paid (almost) any price to figure something out? That's what I'm talking about.

Learning from history

This is a very important point with data and query sets. We forget so fast. Remembering helps us not repeat the same mistakes — see how we learn vs. education system-ic#.

no one on the inside has any clear idea about how to change the way our
institutions work while leaving our benefits and privileges intact

Social is not exempt. We're still talking about people, after all.

 

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Valeria is an experienced listener. She is also frequent speaker at
conferences and companies on a variety of topics. To book her for a
speaking engagement click here.


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