A lire sur: http://www.cio.com/article/717414/How_to_Use_Big_Data_to_Stop_Customer_Churn?source=CIONLE_nlt_entapps_2012-10-01
While still in its infancy, Big Data helps companies on the cutting edge of customer experience figure out why some customers leave and how to stop others before they do.
By Allen Bernard
Thu, September 27, 2012
Thu, September 27, 2012
CIO
—
Your customer service representative answers a call from an irate
customer. "This darn thing I bought just doesn't work!" he exclaims.
"I've tried and tried to get help from your service folks, but they're
always late and they can't fix it either. I've had it with you guys. I
want my money back!"
There's silence as your rep calmly listens to this obviously unhappy customer—and pulls up a raft of information about him, ranging from a few years' worth of transaction data (from the data warehouse) and service call information (from the service department databases) to call history (from the CRM system) and what he's said about your company on Twitter, Facebook and the blogosphere. There may also be a stream from previous online chats or, thanks to cookies, a list of where he's been when searching your website.
Case Study: How Assurant Solutions Used Analytics to Save Customers From Call Center Hell
All this information is compiled so the rep can see, through a visualization tool, that this is actually a good customer who's just having a bad day: He hasn't been troublesome in the past, he frequently Tweets and therefore has a high Klout score (which makes him a social media influencer, presumably with lots of followers), he gave you a Facebook "like" and he spends a fair amount of money with you.
"Big Data gives you a more in-depth understanding of what people are doing and how they are engaging with the organization. Ten to 15 years ago companies were just storing transactional data," he says. "Now we are tracking more behaviors. We give people logins, we store cookies. When they come back, we know who the customer is…what pages they click on and what they're looking for."
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There's silence as your rep calmly listens to this obviously unhappy customer—and pulls up a raft of information about him, ranging from a few years' worth of transaction data (from the data warehouse) and service call information (from the service department databases) to call history (from the CRM system) and what he's said about your company on Twitter, Facebook and the blogosphere. There may also be a stream from previous online chats or, thanks to cookies, a list of where he's been when searching your website.
Case Study: How Assurant Solutions Used Analytics to Save Customers From Call Center Hell
All this information is compiled so the rep can see, through a visualization tool, that this is actually a good customer who's just having a bad day: He hasn't been troublesome in the past, he frequently Tweets and therefore has a high Klout score (which makes him a social media influencer, presumably with lots of followers), he gave you a Facebook "like" and he spends a fair amount of money with you.
"This
is a significant advancement for organizations that, until now, had to
rely on customers' frankness and candor to understand the issues."
This
gives the rep the green light to offer this customer a refund, a free
return shipping label and a coupon for 20 percent off his next purchase.
The customer is happy—and, even better, he's decided you aren't so bad
after all. Case closed.Big Data Holds Big Promise for Improving Customer Experience
Customer service reps don't have a red light, green light dashboard view quite yet, but for companies on the bleeding edge of big data analytics, the scenario described above is happening today, says Eric de Roos, senior director of product management for business intelligence vendor MicroStrategy."Big Data gives you a more in-depth understanding of what people are doing and how they are engaging with the organization. Ten to 15 years ago companies were just storing transactional data," he says. "Now we are tracking more behaviors. We give people logins, we store cookies. When they come back, we know who the customer is…what pages they click on and what they're looking for."
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