By Jeff Scroggin
By taking advantage of recent advances in data storage and compute power, DSL service providers have uncovered new ways to improve the customer experience by resolving broadband performance issues faster and more accurately. At the same time, these advances help providers reduce operating costs by tens of millions of dollars a year.
As data storage costs have decreased dramatically, service providers can maintain a highly comprehensive record of DSL performance statistics across the network, such as detailed data for sync rate, maximum achievable rate, margin, attenuation, retrains, and interference, to name a few. For each line, the service provider may collect this information daily, hourly, or multiple times a minute.
By processing this data with complex algorithms designed specifically for big data analytics, providers can more effectively identify and respond to performance issues that affect the customer experience. This historic DSL performance data holds intrinsic value that can transform contact center operations, and providers are investing in new ways to mine that data. Research firm Ovum estimates that by 2018, telecommunications service providers will spend more than $7.7 billion annually on big data analytics solutions.
Transform Customer Care
Traditionally, the service provider’s network operations department has tracked DSL performance data against key indicators for speed and reliability. This data helps the operations group ensure that customers are receiving the appropriate performance for their particular service products.
Recent developments in big data analytics show this same performance data proves invaluable in contact center operations to help diagnose and resolve performance-related issues. For example, by analyzing historical and real-time performance statistics, expert system algorithms can automatically isolate the most likely cause of a performance issue and recommend the best solution. Recommended actions may include running an automated profile optimization in real time, replacing a problematic home gateway or modem, asking the customer to check for a missing microfilter, dispatching a field technician to fix a wiring issue in the network plant, or even verifying that the issue is not DSL-related (and likely a home Wi-Fi or network configuration issue).
Enhance Contact Center Productivity
Big data analytics using DSL performance data provide contact center agents with insight and actionable guidance to resolve performance-related issues more quickly and more accurately on the first call. Analytic engines improve “right the first time” results, while reducing escalations, callbacks, and unnecessary dispatches.
As an example, a recent customer study showed significant improvements in dispatch decisions by applying expert system analytics to DSL network data collected by a dynamic spectrum management (DSM) system. Using an advanced analytics engine that evaluates data across millions of DSLs, a service provider reduced error rate for dispatch decisions by 84 percent, with an overall 34 percent reduction in monthly dispatches. Consequently, the provider is able to reduce dispatch costs by tens of millions of dollars each year across the entire network.
Improve Customer Experiences
Effective use of big data in the contact center ultimately leads to an improved customer experience, where agents can solve issues more quickly and accurately on the first call, without escalation and without a technician dispatch.
Without the benefit of analytics to identify trends on a single line as well as across a neighborhood of lines, agents historically have relied on default measures such as replacing the gateway or modem or dispatching a technician. In the short term, these options satisfy the customer by demonstrating that someone is taking action to solve the problem; however, both options present a significant cost to the service provider and consumer. For instance, a technician’s visit commonly costs from $100 to $150 and requires the customer to adjust his or her work schedule to be at home. And frequently, a new modem or technician dispatch may not actually be necessary to solve the problem (as in the case of an improperly configured Wi-Fi network in the home).
By analyzing the terabytes of performance data collected across the DSL network, the service provider can deliver an improved customer experience by solving the problem during the first call, without the requirement for follow-on activities. And new data analytics capabilities offer contact center agents even more precise diagnoses of DSL performance problems. Expert system analysis of real-time and historical performance data can identify intermittent problems that an agent may not easily detect during a call, and with a combined historical and real-time view, the agent can avoid repeated (and costly) technician dispatches to detect and resolve the problem.
A Winning Combination: Reliability, Speed, and Customer Service
In conclusion, big data analytics applied to DSL performance data offers a significant opportunity to improve customer satisfaction. In a recent study, Analysys Mason reported the factors that have the greatest impact on delivering an exceptional customer experience are improved customer service (32 percent), improved reliability (24 percent), and increased speed (18 percent).
DSL performance data has traditionally contributed to improving reliability and speed under the network operations’ bailiwick. Now the customer service organization can use this same data to resolve customer issues more quickly and effectively, as well as improve customer satisfaction. As a result, DSL providers can extract additional customer insight buried in terabytes of performance data collected each day and use this insight to deliver greater value than ever before.
Jeff Scroggin is the vice president of solutions marketing at ASSIA.
[From Connection Magazine – Nov/Dec 2014]