Experience Delivers

Transforming customer experiences by designing processes from the customer-in, enabling rich, meaningful interactions

So there’s a fantastic service in the Bay Area, that’s recently expanded to New York and Seattle and soon to expand into other cities – I’m talking Uber, and let me describe just why I love this taxi service and why I think it’s relevant to anyone in the business of delivering a great experience to their installed base of customers.

I registered for Uber, provided them my credit card details and installed an application on my phone.  Now, after a night out in the Bay Area, I launch the Uber application, it knows exactly where my location is, and I press the button to get me a car.  I immediately get a response telling me how long – it’s never longer than 4 or 5 minutes – who my driver is going to be, and his name.  I can watch him arrive real-time on a map, but to be honest, he’s usually there before I walk out the door.  He knows where I’m going, and when I get there, I step out the car, don’t even have my key in the door and I get an email thanking me for my custom, asking me to rate the driver, and sending me my invoice for the journey.  It’s an entirely cashless experience, including tipping the driver.  It couldn’t be simpler; it’s an experience exactly how I would want it … the cab is there for me, wherever I am, whenever I want it, and I don’t have to worry about not having cash or whether the driver is going to get upset about pulling over at a cash machine.  It’s the taxi cab experience I would have designed for myself.  It works the way I work.

Easy, right ?  Until you look at the science behind the experience.  Because those guys at Uber are Quants, make NO mistake about it!

Take a diversion from this blog post, and read the following post by the number heads at Uber:

http://blog.uber.com/2011/05/16/uberdata-mapping-san-francisco-new-york-and-the-world/

Uber have realised that the best imaginable cab experience boils down to 4 key metrics:

• Where are people coming from ?
• Where are people going to ?
• Where are our drivers at ?
• When do these patterns change … during what ?

These metrics informed the design of the customer experience, the experience itself has been instrumented to measure and report on these metrics real-time, and the metrics are then used to prove and improve the experience.  This is the essence of what I have often talked about as the goals of an “Experience Oriented Archiecture”, and my belief that there is an Art and a Science to a great experience.

Uber really have got to the heart of the science of where their drivers are when they pick up a fair, and have identified through real-time data, how to continually optimize the experience they are delivering to within the service levels they expect.  They may have drivers driving over to certain parts of the city if they don’t have a fair, they may have more drivers on during a Thursday evening near the California Academy of Science.  They don’t need human insight that Thursday night is date-night at the academy of science, the data, the collection of it, the real-time analysis and application of it ensures that on your first date in San Francisco, you’re not standing in the rain in Golden Gate park waiting on a ride home.

As you can see from the article entitled, “When Google Fails”, the team at Uber even realized when launching their service in New York, that the estimated journey times coming from Google were on average off by a factor of almost 4, due to crosstown traffic and congestion.   What Uber have shown, is that the more data they collected about their customer’s usage patterns, the more rides they accumulated, the ever more accurate their own algorithms are against Google estimates.

In other words, real-time metrics and intricate and elegant data-driven algorithms are allowing them to ever optimize the end user experience, a near-numerical Kaizen.

They continually tune and improve their quality of the very next experience, upon the the sum total of quality of all experiences delivered so far.  That to me, is the defining characteristic of applying Science, to the Art of Experience Design.

How does this manifest for me, as an end user ?  I have no idea just how smart those guys are. I don’t need to care about mean square errors and predictive modelling of traffic flow. I press a button on my phone, and within 4 minutes, the driver with the best rating shows up, takes me home, and doesn’t require cash.

The simplicity of the end user-experience, the art of taking passengers from where they are to where they want to be, is supported, indeed enabled and differentiated, by science, by a deep understanding of the metrics that matter, and recognizing that we can be too busy just looking at the numbers to forget we can influence them, too busy studying the data to forget that we can shape it to our advantage.

Check out Uber.  I’m a wildly happy customer.  And think about where a little bit of number crunching, measurement and optimization could go a long way to optimizing the kind of experiences that YOU are in the business of delivering to customers.

The curtain should be as simple, easy and effective to use as possible.  But think about putting a little science, sufficiently advanced such that is is indistinguishable from magic behind it.

 Steven Webster, Senior Director of Technology, Experience + Innovation.