Predictive analytics for call center operations

An optimized call center is essential to any organization—especially for product-based companies offering 24/7 support to customers. With close attention to the year-over-year fluctuations, such as what time of the day service calls are received or what type of skills are required, your business can better strategize. Restructure operations and efficiently handle customers with consolidated insights from past and real-time interactions. Let predictive analytics determine the next steps to redefine existing customer service options.

Call center analytics use cases

Solutions - Call Center Dashboard - Future Trends

Insights that help get to the root problem

CASE STUDY

Avoid underestimating or overestimating call volumes with forecasting algorithms to improve customer experience

Challenge

Nothing spells bad service to customers more than when a service delay is experienced. This is a problem our Telecom client was trying to steer clear of: How to reduce the time it takes an agent to answer to a surge of customer service calls at a given time.

Solution

With 90 days’ worth of call trend data, Analance determined the number of expected concurrent calls during a time period and ensured that calls do not exceed a site’s capacity with Seasonal Decomposition as the algorithm of choice.

Make data-informed decisions with predictive insights

Identify Unhappy Customers

Identify unhappy customers

Identify indicators of customer dissatisfaction by intelligently analyzing call center data such as unusual silence, abrupt call endings, call misrouting, and untimely account closures.

Prevent Customer Churn

Prevent customer churn

Identify predictors of customer churn and gain control over influencers to enhance customer satisfaction, increase revenue, and better employee satisfaction.

Understand Sentiments

Understand sentiments

Identify customer sentiment influencers by analyzing social media data and improve quality of service based on real -time evidence instead of instinct-based decisions.

Build Meaningful Metrics

Build meaningful metrics

Identify, build, and monitor meaningful metrics related to call times and efficiency to tie them back to service quality.

Optimize Customer Service

Optimize customer service

Identify patterns in customer queries and reduce redundancies with self-service call routing and FAQs.

Better Resource Management

Resource management

Identify segments by geography, time, and channels to better assign agents based on meaningful insights.

Want to learn more?

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Why enable predictive analytics?

Analance empowers organizations with data analytics for better storytelling and predictive insights that help scale business outcomes.