Dropped calls and frustrated customers have long plagued companies. Having insight into these problems and the ability to track them proactively have matured, however.
To cure these common ills, many have turned to analytics, previously thought of as the domain for number-crunching. Even better, most companies have the data necessary for improving customer service; they just need to take the next step and start parsing it, according to experts.
It's no secret that data can improve customer service decisions and the customer experience. In a recent study conducted by Demand Metric Research Corp., 81% of surveyed companies with an analytics program in place said it is moderately to significantly important -- and 54% say that their analytics are influencing or enabling better decision making. "The best [analytics] are those that show us where we need to go and let us understand how customers are responding," said Jerry Rackley, chief analyst at the London, Ontario-based marketing and analyst firm.
Improve customer service with social media analytics
Twitter and Facebook have become legitimate platforms for customer concerns, and companies that ignore social media channels do so at their own peril. But just responding to complaints isn't enough; diving into analytics to detect patterns can better respond to customers and head off problems at the pass, according to Rackley.
"It's a deliberate effort to listen using social media channels, and not just listen but respond," Rackley said. In a typical scenario, companies that don't listen to comments on social media are oblivious while their brands are being tarred and feathered or praised, while companies that are listening have active listening centers with real-time information being fed to them so they can proactively engage their customers. "The long-winded answer is that social media analytics seems to be the area where we're seeing a lot of engagement and customer care," he said.
Social media provides an unfiltered view of the customers, according to Steven Ramirez, CEO of Berkeley, Calif.-based consulting firm Beyond the Arc. "You get a better sense of the intensity of the problem," he said. The big wins come when companies analyze social media feedback for recurring patterns and can pinpoint emerging issues.
Leverage existing CRM system data
On the other side of the coin is the existing data that so many companies have sitting idle in CRM systems, just waiting to be analyzed. "When [companies] start to embrace analytics, they're finding that a lot of the data is already there," Demand Metric's Rackley said. The company's CRM system holds data about all the touchpoints customers have come in contact with and provides information about pipelines, sales cycles and response rates. But the tools to analyze data may not be in place -- or companies may resort to the humble spreadsheet, and these situations have a negative effect on analytics since they don't foster collaboration, he said.
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Using analytics that already reside in a CRM system helps identify which customers are at risk of defecting, according to Beyond the Arc's Ramirez. "Companies could begin to build some predictive models that look at a multitude of different factors [and] generate predictive models," he said. These can then be used during customer calls to notify agents that this customer needs special handling, perhaps an offer to keep that customer.
Get to the heart of customer issues
For some companies, the ability to get to the bottom of why customers are calling and to handle concerns efficiently is reason enough to implement analytics. Commerce technology firm eBay Enterprise dug deeper into correlated issues and link analytics with satisfaction surveys not only to verify theories about why customers contacted the company but also to understand what customers want based on surprise keywords, according to Robin Gomez, director of operational excellence.
For example, customers were searching for the keyword flashlight, which confounded eBay Enterprise's staff. However, as the team delved deeper into the query, they learned that customers were actually using a flashlight to find the serial number on a product. This led to eBay Enterprise advising the client to reposition the serial number, Gomez said.
Helping customers help themselves
Analytics has also helped identify ways to create self-service opportunities for customers, according to Gomez. "We do a lot of first-contact resolution, [which requires] understanding process flows. We had process flows for troubleshooting while on the phone, effectively looking at large delays in time," he said. Those delays could be attributed to representatives walking customers through fixes, which led to eBay Enterprise creating self-help videos and posting them on its website.
The ability to review metrics such as call transfer history has also helped the company empower customer service agents and resolve calls faster. EBay Enterprise zeroed in on why agent transfer rates were higher and realized that it could authorize the agent to resolve some common issues, which led to a 100% approval rate and decreased transfers to second-tier agents. "Why should [the agent] have to transfer the call when [the next agent] is going to approve it based on these characteristics? Just have the front agent do it," he said.