Three Lessons Watson Taught Us to Improve Customer Service


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Well, I had to do it.  I had to rip off the headlines and apply it to our customer service problems.

In case you call a rock your comfortable abode (or have a life outside of the echo chamber of Twitter that does not include watching Jeopardy), the news is that IBM created a super-computer that — what’s the best way to put it… trounced, annihilated, destroyed, humiliated… I know — summarily defeated two human opponents playing Jeopardy (this is a trivia questions-and-answers game that is very popular in the United States, and quite hard for most normal human beings to master – not me, of course).  The computer played against the top two jeopardy mega champions: Ken Jennings (who won every game for almost six months straight), and Brad Rutter (who won the largest sum of money in the game’s history).  Here is a wrap-up article by Ken Jennings that explains most of what you need to k now about this event.

Why does it matter to Customer Service?

It took IBM 25 scientists and four years to program the computer to understand the language used in jeopardy, select and store the necessary knowledge (if could not be connected to the Internet, federal regulations — ever seen the movie “Quiz Show”), and have it learn the rules and regulations of the game – in addition to train it to play the game.  Four years, 25 language scientists.

The problem to be solved is far larger than your customer service implementation, right? Right? Well, this is where the lessons learned come in – if you take the time to analyze the results…

Lesson One – Constraint. The scientists started with the premise that the game show could ask any question, about anything, from any time and any place.  That is a lot of knowledge to condense and feed a computer.  They had to, somehow, constraint the knowledge base; to define better what they had to understand, where the answers may be, and where to find it.  Watson had 15TB of data available.  Far more than your standard customer service setup for sure, but a minuscule, tiny, insignificant amount compared to the 3.6 ZettaBytes (don’t try, cannot even picture it) we consume each day, or the more than 20 petabytes that Google processes every day (just for your information, that number was 10 petabytes less than 12 months ago).  As you can see, there was lots of constraint shown in choosing the 15TB of data that Watson had available to generate answers.  Same principle applies to your service and support solution – I am sure that the knowledge base with 120,000 articles is a source of joy for your organization – but keeping articles in there than tell you how to solve your Windows Bob, Newton, or CP/M problems only muddle the process of finding the right answer.  Chose the knowledge you need to use wisely, and be very, very good at keeping that number small and manageable; trim unnecessary and add necessary swiftly.  It is far worse to not find the one you need that to have 119,999 you don’t.

Lesson Two – Simplify. Bells and Whistles are awesome – you can do lots of things to call attention to something good you are doing, try to make it more powerful, more attractive, and further reaching.  Bells and Whistles, however, don’t prove to be a solution.  The key to Watson winning was not only having the right knowledge, but understanding the process.  Now, think about the many decisions you as a human would have to make if you were playing Jeopardy, and the speed at which you would have to execute those actions.  If you could simplify the process, reduce the number of steps, and focus on the core of what you are doing you’d be far ahead of the game.  You can do this with your customer service setup: simplify the process, make sure that both customers and agents can get to THE answer faster and easier.  The researchers at IBM sought the best examples of how to play Jeopardy (Ken Jennings in this case) and reduced the complex model they had built to accommodate his specific style of play – simplification at its best. Simplifying makes it also far simpler to maintain a solution  if you already know what is not necessary to have.

Lesson Three – Learn. What can I say about learning and training your systems that I have not said? the world of support is divided into two: those that learn from their operations, errors, and successes – and those that are no longer in business.  A client of mine in the old days deployed a very costly knowledge management solution, but “forgot” to add the necessary routines to learn from its mistakes, grow the solution by trial and error.  By the time they figured out they needed it, almost 3 months later, it was impossible to control the monster they had created and they had to go back to the starting block.  Learning from the successes and failures of your solution, whether automatically or not, is what is going to make your certainty increase, the right answers show up more often, and your knowledge base remain simple and effective.  Virtually everywhere you read about Watson it says how he learned from playing, and it became better the more it learned.

Finally, one word of warning – among the many interviews that IBM researchers and scientists gave during the three day monster-computer-demolition-event, one of them said that the real excitement was not that Watson could win playing Jeopardy, or that they could program it to do so – but that they had real-life applications waiting to take on using the same technology.  At the top of the list: Customer Support.

I don’t, for once, welcome our computer overlords (that was Ken Jennings closing phrase after being “p0wn3d” by the computer).  Apparently, neither does Andy.

What do you think? What were your impressions of Watson versus Humans? Over-hyped and under-delivered? Over-delivered and Under-hyped? Mixed? Would love to hear your thoughts — and whether or not you welcome your computer overlords.

Republished with author's permission from original post.

Esteban Kolsky
ThinkJar, LLC
Esteban Kolsky is the founder of CRM intelligence & strategy where he works with vendors to create go-to market strategies for Customer Service and CRM and with end-users leveraging his results-driven, dynamic Customer Experience Management methodology to earn and retain loyal customers. Previously he was a well-known Gartner analyst and created a strategic consulting practice at eVergance.


  1. Esteban,

    I feel compelled to respond, not because my name is Watson (it is), but because I enjoyed the clear parallel you’ve drawn between the Computer that Played Jeapordy, and the Best Practices of Customer Support and Knowledge Management!

    In fact, those three tenets which you identify – constraint, simplify and learn – can be applied to virtually any endeavor, to make it more successful.

    Thanks for a creative and pragmatic post.

    Your truly,


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