See all Nokia sites

Autonomous Customer Care

The evolution to zero-touch customer care

The goal of Nokia Autonomous Customer Care solution is to resolve customer issues in the shortest time, with the least number of steps and human interventions.

Machine learning algorithms and bot-based CEM touchpoints transform hands-on care to low-touch personalized care, proactively fixing problems before the customer is even aware of an issue.  As a result, customer experience is essentially no experience at all!
 

17 October, 2017

Swisscom Shares Operator Insight on
Enhanced In-Home Wi-Fi Experience

Register now

view the infographic

The promise of Autonomous Customer Care is profound.

Rather than waiting for subscribers to seek technical support using traditional channels, action can be taken proactively without the need for any interaction between the customer and the help desk.

Making customers more self-sufficient, providing CSRs with tools that result in faster, more accurate customer care and ultimately resolving issues automatically not only makes customers happier, but it also generates a number of significant operator business benefits.

Decreasing customer effort

The greater a customer’s effort in resolving fixed or mobile network problems, the greater the negative impact on satisfaction and NPS.  With Autonomous Customer Care customers benefit by:

  • Having issues resolved quickly, with fewer steps and aggravations
  • Less personal effort in managing many aspects of their subscriptions
  • Pre-emptive resolution of network service issues – before they are even aware there’s a problem
  • Pre-empts "silent churners", customers who do not complain but will churn based on a poor service experience.

Decreasing operator effort and costs

Enabled by machine learning and AI, interactive ‘bots’ can support operator CSR’s (augmented care) and will learn to take on direct customer care interactions (autonomous customer care). By seamlessly combining human and machine intelligence, human intervention and OPEX are reduced:

  • CSRs work faster and put their skills to better use by focusing exclusively on complex issues or by providing premium technical support
  • Decrease time spent on high call volume, low complexity issues
  • Increase agent compliance to best practices
  • Accurate, speedy issues resolution avoids rolling service trucks or shipping needless replacement equipment

This represents a massive impact to the contact center OPEX and Customer Satisfaction for fixed, mobile and converged CSPs.

Cutting Edge Technology

Digital transformation brings artificial intelligence (AI), machine learning (ML) and natural language processing (NLP) together, allowing digital service providers to significantly automate customer care interactions and reduce customer effort.

  • Initial care interactions with IVR enhanced through AI and NLP; better understand the customers intent when making that first call for help
  • Machine learning enables development of Dynamic Intelligent Workflows to adapt to unique customer context; and over time, to develop custom paths for resolution
  • Nokia Bell Labs algorithms build on workflow history, customer information and network status to select next-best action (NBA) for an agent to use in that specific customer situation

Leading Edge Predictive Analytics

Backed by Nokia Bell Labs innovation, Nokia Autonomous Customer Care provides continuous improvement of the troubleshooting process through analytics and machine learning 

  • Analysis of data captured from the network, CPE and trouble tickets allows the development of algorithms to better predict service disruptions and to take proactive actions to address issues
  • Bell Nokia Labs have developed an algorithm that correlates customer ticket records with network topology and services, allowing real-time detection when outage spikes are starting to happen
  • Proactive bots predict service-affecting issues, recommend solutions and execute proactive actions to fix them without any interaction between the customer and traditional support



Tolerance for legacy customer care solutions is waning. There is an appetite for change and emerging solutions using are generating substantial interest with consumers.

CSPs can use ‘bots’ to provide an enhanced omni-channel customer care solution. Powered by technologies like AI, machine learning and NLP, proactive bots can identify service-affecting issues and fix them automatically, without any interaction between the customer and traditional support channels.

The real value for autonomous customer care, however, will be found within the extensive library of use cases, known as the knowledge representation. It will be the ability to match subscribers’ intents to the appropriate remediation procedures that will provide the key to boundless autonomous customer care.