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Oct 27 2017

3 steps to autonomous customer care

Twitter: @nokianetworks

The future of autonomous customer care is upon us. By bringing together augmented care, semi-autonomous care, and proactive care, communication service providers (CSPs) will be able to provide the most advanced, efficient, and seamless customer care experience possible.

But what we’ve learned is that CSP contact centers still discover about 70% of the problems that subscribers report to the customer service representatives (CSRs) are Wi-Fi related, which is a daunting challenge. Why, because WiFi is synonymous with “the internet” and for CSPs, Wi-Fi means increasing operational support costs to manage end-user experiences.

What it comes down to, is how proactively customer issues can be addressed before they arise. This may sound far-fetched at first, but in fact there’s a large amount of data available from customer trouble tickets and the network termination devices, modems, home routers and set-top boxes, that can be used to predict service outages or issues, even before they are detected by the customer. This is the basis for predictive analytics. These analytic solutions use algorithms to predict and initiate steps to correct issues before the customer is aware. They can also be applied during the customer interaction with the “digital employee” – Alexa or Facebook Messenger – in real-time, to zero-in on the nature of the issue faster.

Prescriptive analytics takes this one step further, by not only using algorithms to predict possible problems, but also to provide management systems, such as Nokia’s Service Management Platform (SMP), with what they need to swiftly and automatically prevent them.

Employee of the month is the “digital CSR”

As we have discussed in this blog series, this principle is made possible by the power of proactive care bots. These “digital CSRs”, as we like to see them, are the personification of predictive and prescriptive analytics.

Autonomous customer care begins with utilizing the machine learning (ML) and deep learning (DL) algorithms from prescriptive analytics to make CSRs more effiicient. Digital CSRs will continually learn from every call coming into your call center and will provide human CSRs with accurate responses time and time again.

The next step needs to address the majority of customer issues. In fact, by identifying just 20% of the issues — and programming interactive bots to manage them up-front or with the customer directly — CSPs can eliminate up to 80% of inbound help desk calls.

Finally, when bots are programmed to work proactively in detecting network issues, problems can be solved immediately. This “zero-touch” customer care is the best case scenario — when subscribers don’t address service issues because, well,  there are none.

Detection and correction of DSL problems also must be automated to avoid the costly steps of customer calls and manual interventions for fixing broadband service issues. The ability to point to the root-cause and repair loop problems in a proactive rather than reactive manner is key  Typical examples include coping with changing weather, varying loop quality and age, inconsistent indoor wiring, radio interferences and broadband services running on adjacent wire pairs, as well as   other error causing activity like  degraded or intermittent contact, crosstalk or bridge tap. DL techniques that drive the proactive care bots is especially important in such unpredictable DSL environments to help minimize customer complaints and subsequent truck rolls.

Working to make services more efficient through the use of DL techniques and its unique domain expertise, Nokia has built a model that attains a “lift of 70”, meaning that possible issues to the help desk can be predicted with 70x more accuracy. Now that’s a lot of investigative guess work eliminated

The future of customer care is autonomous

Taking the three steps I have discussed in this blog will have a major impact on your business. Through autonomous customer care, CSPs achieve 54% unexpected/above target savings in total support costs on average, not to mention greater customer satisfaction.

Bot technology is creating a new standard for customer care. We have pre-integrated Home and Access Analytics with our Connected Device Platform (CDP) and Service Management Platform (SMP) so that you can use predictions to support automation and actions that optimize the customer experience..

Download our Nokia’s autonomous customer care white paper to learn more.

Visit our Autonomous Customer Care website to learn more about how bot technology can bring your customer care to the next level.

Share your thoughts on this topic by replying below – or join the Twitter discussion with @nokianetworks using #AI #CSPCX #bots

About Tom Van Leeuwen

Tom is responsible for our analytics-driven digital home experience product. With a Ph.D in Computer Science, he brings valued experience and vision to the Nokia Customer Care portfolio. He’s also known to switch off the analytics in his spare time by running, enjoying small-scale agricultural activities in his garden, and focusing on family.