Date Published: December 10, 2009 - Last Updated 5 Years, 107 Days, 22 Hours, 21 Minutes ago
Have you ever been on the phone with a customer care agent where you found yourself repeating the same question multiple times to the same person? Have you ever been continuously put on hold? Did you ever call again to make sure you were told the right information? Customer care centers handle millions of calls every day, and while far from the norm, these experiences happen.
While frustrating, this is something that can easily be fixed with technology and training. When ACS implemented speech analytics, we were quickly able to identify those agents that had difficulties with listening to what the customers were asking, those that put callers on hold, and those that seemed unsure of themselves and the information they were giving customers. Once identified, they were put through additional training. By focusing on this group, we were able to see improvements in call handling times and overall gains in quality, which were validated in customer satisfaction surveys.
While it is the goal of every agent to deliver a great experience on every call from the start, it is impossible to have a team of quality analysts listening to each call to ensure this is done. In the past, without spending a small fortune, providers only had the ability to monitor a handful of customer interactions per agent per month. This led to a limited view of what is truly happening within call centers and forced businesses to make assumptions as to reasons for success based on a review of only a fraction of the interactions.
Call centers don’t have the ability to incorporate the overwhelming majority of customer insights because they don’t have the ability to leverage unstructured sources of customer communications. Customer care centers that act on this information will have an advantage over call centers that don’t. This new information could save clients millions of dollars.
Better Call Data Faster
Speech analytics tools can dramatically increase the number of calls that are reviewed, leveraging the existing infrastructure and investment to deliver improved outcomes. Simple statistics tells you the larger the sample size the more reliable the data and the smaller the margin of error. This provides more accurate and more valuable information.
Call classification becomes an automated process reducing call processing time. The automation allows for faster identification of trends impacting the call center, whether this is change in volume of particular call types or changes in the processing time. Additionally, the system attaches the related calls to the data in each category, allowing you to easily listen to calls associated with a particular wireless device.
Speech analytics products ensure that decision makers receive more accurate data in significantly less time. These programs assess data from a larger sample size of calls, giving businesses more confidence in the data collected. This information can be leveraged to improve customer service for any business, which reduces customer churn. In this business climate, size and speed matters.
Targeted Quality Monitoring
Quality analysts no longer randomly pick calls in the hopes of finding ones with opportunities to improve our experience and result. They now spend their time on calls that truly need coaching. They do this simply by reviewing call categories where there are longer calls, quality concerns, and other areas for improvement. Organizations can gather that information from customers more easily, thus allowing managers to take information back to decision makers to improve, clarify, and fix policies and procedures that do not support the customers. This process is also useful in improving new hire training programs. By utilizing past experiences from current callers and making necessary changes in the initial training, there shouldn’t be a need for remedial training in the future.
Taking the call data and filtering it through speech analytics is just one part of the equation. The best companies take this process one step further and marry this data with actual customer satisfaction survey results. By comparing and contrasting both the calls and the survey data, organizations get a more complete picture of the customer experience. This has been extremely helpful in identifying call types that typically scored lower on surveys, and finding a portion of these categories tended to lead to lower overall scores.
By isolating these calls and now putting a stronger focus on improving these particular calls since we can “move the needle” on these outlier categories, we generate the largest lift in our scores. In one specific example at ACS, we took this particular approach in one of our sites to see if customer satisfaction survey results could be improved. The site selected for this test was an average site, with satisfaction scores in the middle of the pack. However, by adopting this approach over a two month period, this center is now leading the pack on customer satisfaction. It is this specific outlier management activity that has made that possible.
ROI for the Call Center and the Enterprise
The investment in speech analytics can yield financial dividends. Large organizations could realistically save hundreds of millions of dollars a year by reducing customer churn. Because it costs so much more to earn new customers than it does to retain existing ones, companies looking to save millions of dollars a year can utilize speech analytics to retain current customers and keep them satisfied.
Consider this example of a consumer products company that churns through 1% of its 20 million customers a month, which equates to a loss of 200,000 customers a month. Assuming that each customer was subsidized with $250 worth of rebates, “free” products, etc, this company is losing $50 million a month - or half a billion dollars a year through churn!
Part of the value in speech analytics comes from the speed with which new information can be mined. When a new product is launched, the system can be easily updated to identify what percentage of your customers are asking about the new device, giving you concrete data on the day the product is released. The system can also be used to track compliance of script changes. This provides the ability to know with confidence at what point the scripting is being adhered to so any expected impacts can be tracked from the date where 95% of customer service representative are using the new scripting.
The biggest benefit of using speech analytics is being able to identify which customers are likely considering other service providers. Using questions that are predictive of customer churn, the system can identify those customers, enabling providers to proactively contact them to resolve any issues and persuade them to stay. This is the ultimate customer retention tool.
Numerous studies show that customers whose problems are resolved during the first call are much less likely to defect from the company. The risk of churn increases proportionally to the number of calls required to resolve the issue, up to ten fold if the issue is never resolved.
What is exciting about speech analytics is not what has already been accomplished as measured by performance improvement and survey results, but what remains to be achieved in the future. We are just beginning to scratch the surface with speech analytics. There is room for even greater improvement and ability to drive desired outcomes. Speech analytics has the ability to predict which customers are promoting a company and those that are more likely to speak ill of it. Organizations can leverage this information to build programs and incentives to ensure loyal customers are maintained while others are rewarded with improved customer service.