Next Call Prevention

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Predict and meet future customer needs

What are some of the primary reasons customers call your contact center? In many cases, it’s that follow-up question customers forget to ask while on the line the first time. And, according to the NICE 2012 Consumer Channel Preference Survey, more than half of calls are from frustrated customers who were unable to accomplish a task via your self-service channels. Can you eliminate these calls? Absolutely.

 

Service organizations collect terabytes of customer “big data” from millions of interactions every day—data that provides valuable insight into customer history and current account status. Using the right analytics tools, this data can be used to literally predict the future, too, and take customer service to a higher level. NICE Next Call Prevention does just that. 

Next call prevention: Using a unique combination of speech analytics, text analytics and contact analytics, NICE Next Call Prevention identifies repeat contact patterns, correlates one contact reason to another or to a customer lifecycle event, and enables agents to handle common secondary issues in the first call. For example, customers who call to upgrade to a smartphone are most likely planning to access email on the device. If this need isn’t addressed during the first call, customers are likely to call again soon. By proactively asking them if they will be using email on their new device, that next call can be avoided.

 

First call prevention: NICE Next Call Prevention also identifies triggers—self-service weaknesses, customer lifecycle events (like a move or contract expiration), faulty processes, ineffective documentation and system inefficiencies—that generate first-time calls to the contact center. And it provides insights and tools with which organizations can take action to fix them, eliminating these calls, too.

 

NICE Next Call Prevention provides:

  • Big Data management infrastructure, processes terabytes of raw data from multiple channels and millions of customer records
  • Cross-channel pattern identification, cross-references analytics insights with customer lifecycle events, isolating common, recurring contact patterns
  • Customer-specific next call predictor, predicts customers’ next actions or questions based on their history and past behavior
  • Predictive real-time guidance, guides agents in real time to offer customers a response to a predicted need
  • Self-service improvement isolates issues originating in the self-service channel that result in calls to the contact center, allowing organizations to take immediate corrective action.

With its first-of-its-kind combination of predictive analytics, real-time, visual dashboards and action-oriented functionality, NICE Next Call Prevention enables your contact center to reduce the amount of avoidable calls and raise customer service levels.

 

  • Innovative combination of NICE Interaction Analytics, transaction analytics and sequencing capabilities to accurately predict downstream service issues and future customer needs
  • Advanced data visualization that clearly depicts key findings
  • Ability to take data-based steps that impact critical contact center statistics, including call volume and customer satisfaction, in real time
  • Integration with NICE Workforce Optimization, providing a single central portal for frontline users and analysts

NICE Next Call Prevention combines NICE speech analytics, text analytics and contact analytics to uncover common patterns and foresee future customer needs and address them. Specific capabilities include:

 

  • “Big Data” management infrastructure enables processing of terabytes of raw data from multiple channels, millions of customer records.
  • Cross-channel pattern identification cross-references analytics insights with customer lifecycle events, isolating the most common, recurring contact patterns that lead to calls to the contact center.
  • Customer-specific next call predictor predicts customers’ next actions or questions based on their history and past behavior.
  • Predictive real-time guidance cues agents in real time to offer customers a response to a predicted need after resolving the primary issue.
  • Customer notification, based on pattern identification, enables agents to easily and automatically create and send notifications to customers, alerting them to irregular consumption events (like impending account overages) or the nearest significant lifecycle events (such as contract expiration).
  • A cross-organization tasks module enables supervisors to easily create and automatically distribute tasks to relevant personnel across the organization based on patterns the system identifies, alerting others to process or procedure problems that are creating secondary issues for customers.
  • Self-service improvement isolates issues originating in the self-service channel that result in calls to the contact center, allowing organizations to take immediate corrective action.