Sometimes companies wonder how, with all their data, they still sail off course. In the field of customer service analytics, vendors play a game of trying to “out-data” the other guy. There is a better approach – more effective and more efficient than sitting through endless vendor presentations involving over-mining of an underwhelming but voluminous set of base data.
There are many reasons why the game is played the way it is today. To justify bringing in an analytics company, many corporate buyers act in a risk-averse, as opposed to benefit-attracted, modus operandi.
Both vendor and the corporate buyer of the vendor's services want to be able to show reams of data and analysis to show that discretionary budget dollars are producing something. But lots of "something" does not equal results.
A case in point is traditional quality assurance monitoring, which certainly produces more data than any senior manager has time to go through. But no matter whether QA is done in-house or through an outside vendor, it is almost ubiquitously criticized for missing the big picture of why customer satisfaction isn't improving. In fact, with a high value customer who has a thorny issue, adherence to standard scripts often fans the flames of the customer's ire.
Both vendor and the corporate buyer of the vendor's services want to be able to show reams of data and analysis to show that discretionary budget dollars are producing something. But lots of "something" does not equal results.
A case in point is traditional quality assurance monitoring, which certainly produces more data than any senior manager has time to go through. But no matter whether QA is done in-house or through an outside vendor, it is almost ubiquitously criticized for missing the big picture of why customer satisfaction isn't improving. In fact, with a high value customer who has a thorny issue, adherence to standard scripts often fans the flames of the customer's ire.
And so busywork rules supreme, while insight founders for sponsorship within the corporation. I’ve been on customer analytics assignments where I get the “aha” moment with a client after analyzing a small number of customer service calls. But we end up presenting slide after slide of data showing how much work we did rather than focusing simply on what we found that can help the business improve.
But lets put the politics aside and analyze the nature of customer service transactions for a minute. In your business, you may have interactions with customers that average a minute or two or over half an hour. Within a transaction of any length, what I’ve found is that there is a dynamic of the interaction, detectable early on, that sets the stage for a positive or negative customer experience.
I don’t discount the value of QA operations in making sure that agents say things the correct way, that they adhere to scripts when necessary, and open and close the conversation in a pleasant manner. But all that data they collect is not the primary determinant of customer’s satisfaction with the interaction. The primary determinant is whether the agent is in synch with the emotional context of the customer.
Customer Satisfaction is Worthless, Customer Loyalty is Priceless: How to Make Them Love You, Keep You Coming Back, and Tell Everyone They Know
Customer Satisfaction is Worthless, Customer Loyalty is Priceless: How to Make Them Love You, Keep You Coming Back, and Tell Everyone They Know
I will continue this topic in my next post, this is my teaser for the topic of the emotional context of business transactions. Think about gifts that you have given to family members, maybe your spouse or children. Have you ever given a gift where you were sure they would like it, you perhaps spent more than you thought you would, took time to wrap it nicely, and then…they express disappointment? Maybe their disappointment is quite subtle, but you FEEL it. What went wrong?
Well, producing loads of data would not help you. What you experienced was the same thing that I call “the emotional context of business transactions.” To avoid such unpleasant experiences requires an exploration of the emotional context of the customer. I’ll take you there in my next post.
