How can we leverage data from our predictive analytics software?
How can we leverage the data collected from our predictive analytics software to help our customer service reps build customer profitability?

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That's an excellent question – in many cases what we see are companies who are collecting vast amounts of data from predictive analytics software and don't do anything with it, or don't do as much with it as they could. The company who doesn't use the information it has about a customer has no competitive advantage over the company that doesn't have customer data. And so, the question is, how do we leverage that data? Here's the key: Take the information you have about a customer and figure out what he needs from you next, and when, and how, and through what channel. In many cases, what we see are companies that only want to think of how to use this precious customer information to help complete sales right away. In a recession, that is particularly tempting, but the real power of this situation comes when, as a company with this valuable information, we're able to think in terms of how we can use this information to figure out what the customer needs from us next and find the next right product for the customer, focusing not so much on the market share as on our share of each customer's business. We can use that information in many ways throughout the company – one of those ways is to help the customer service reps.

At some great companies what we see is a lot of information that comes right up on the screen whenever the call center agent accepts an inbound call or makes an outbound call. A lot of that information helps answer questions so it's not necessary to ask the customer again. It also makes it possible to have a more intelligent conversation and it even provides smart dialogue suggestions so that the company is sharing with the agent the next most important question that we need to ask in order to serve this customer well. We're not going to go out and bother that customer to get that information, but when he calls us then we're ready to ask the question. That makes the customer know that we care about him, it makes the agent's job more pleasant, and it also helps the agent concentrate on the problem at hand and not on getting a bunch of data the customer has already given.

There is a lot of power available through predictive analytics, and through dashboards the agents can see the value of the customer. So, as you look at the lifetime value of the customer, you can watch the value of that customer go up and down, even during the call. Using this information, you can know what makes sense and what's working for a particular customer.

There are lots of ways that we can push this information forward in a way that helps the call center agent. At some companies that have done this the best, we've seen huge reductions in the attrition rates of the agents, because it's simply more rewarding and fun to work for a company where your knowledgeable about helping someone who calls and you're empowered to do that, rather than working for a company where the whole idea is to get off the phone as fast as possible and drive as many calls as possible thorough an "efficient" call center in an hour.

 

This was first published in December 2008