August 12, 2014
Analytics Create a Big ROI for DSL Service Providers
By TMCnet Special GuestJeff Scroggin, Vice President of Solutions Marketing, ASSIA Inc.
By taking advantage of recent advances in data storage and compute power, DSL service providers have uncovered new ways to improve the customer experience dramatically, and reduce operating costs by tens of millions of dollars a year. In particular, DSL service providers are taking a new look at how they collect and analyze DSL performance data.
Dramatically lower storage costs allow service providers to maintain much more detailed record of DSL performance statistics across the network, including measures of speed and reliability for each line over a period of months or even years. As a specific example, ASSIA’s dynamic spectrum management system (DSL Expresse) collects over 7TB of data each day across 68 million DSLs.
Historic DSL performance data holds intrinsic value that is transforming contact center operations. By applying complex analytics algorithms against this historical data, providers can much more effectively identify and respond to issues that impact the customer experience. Big data analytics represents a significant opportunity for service providers who, by 2018, will spend over $7.7B annually on solutions in this segment.
Evolution of a Proactive Support Model
Traditionally, contact centers have invested significantly in diagnostic tools to identify DSL performance issues reported by a customer. Today, big data analytics and detailed historical performance data help agents diagnose and resolve a much greater percentage of incidents on the first call and without the need for a field technician dispatch.
Providers are now implementing the ability not only to diagnose and resolve customer issues more effectively in the contact center, but also to predict and resolve those issues even before receiving a call from the customer. The end result is a much better customer experience, with significant operating cost savings as explained below.
New Uses for DSL Performance Data
The DSL service provider’s network operations department has traditionally tracked DSL performance data against key performance indicators for data rate and stability. This data helps the operations group ensure that customers are receiving the appropriate performance for their particular service products, both in terms of speed and reliability.
Recent developments in big data analytics show that 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 detect a missing microfilter in the home that degrades the DSL stability. Given this data, a contact center agent can guide the consumer through the process of installing the missing microfilter to restore broadband reliability.
Enhancing Contact Center Operations
Analytics for DSL performance data provides contact center agents with insight and actionable guidance to resolve performance-related issues more quickly and more accurately on the first call. The analytic engines improve “right the first time” results, while reducing the escalation rate to higher tier support technicians and also reducing repeat calls.
Analytics systems automatically aggregate and analyze data from a variety of sources and provide the agents with clear guidance for recommended action. Agents rely much less on guesswork or trial and error to resolve the customer problem. As a result, contact centers deliver a more consistent and proficient level of service and responsiveness across the entire organization.
Improving the Customer Experience
Effective use of data in the contact center ultimately leads to a better customer experience, where agents can solve issues more quickly and accurately, on the first call, without escalation, and without a technician dispatch.
A technician visit commonly costs from $100 to $150 and requires the customer to adjust her work schedule to stay home for half a day. And as is often the case, a new modem or technician dispatch may not actually solve the problem (for example an improperly configured Wi-Fi network within the home).
Ultimately, 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 provide for much more precise diagnosis of DSL performance problems in the contact center. In fact, expert system analysis of real-time and historical performance data can even identify intermittent problems that an agent may not easily detect during a call (and that otherwise might result in a technician dispatch).
In sum, big data analytics applied to DSL performance data has developed into a significant contributor to improving the customer experience. In a recent study, Analysys (News - Alert) Mason reported the factors that contribute the most to delivering an exceptional customer experience. The top factors include (1) improve customer service (32 percent), (2) improve reliability (24 percent), and (3) increase speed (18 percent). DSL performance data has traditionally contributed to improving reliability and speed. And now, the customer service organization can use this same data to resolve customer issues more quickly and effectively, and improve customer satisfaction. As a result, DSL providers can extract additional customer insight buried in terabytes of performance data collected each day.
Edited by Adam Brandt