Volume Planning
Aggregate your planning with predictive modeling.
What-If Scenario Analysis
Modify goals or constraints to rerun optimization on the fly.
Cross-Skill Identification
Identify the most needed skills for maximizing productivity.
Customer Care
Higher Call Center Performance with Best-In-Class Call Center Solutions.
Why re-invent the wheel? Our solutions focus on increasing productivity. Repeatable successful solutions built to produce high returns for our clients investments.
Call centers face a lot of challenges including but not limited to a high rate of call abandonment, long customer wait times, high agent idle times, too many call transfers, and high agent turnover rates. An efficient call center staffing can resolve many call center challenges. The Customer Care Solution is a best-in-class call center solution that can resolve all of these challenges. This integrated solution combines best-in-class optimization solvers and open-source data science tools to minimize costs through a reduction in staffing.Â
Customer Care Solution Features
ChatGPT and Next-Gen Chatbots
With the integration of ChatGPT and advanced chatbot systems, your call center can seamlessly transition from Level 1 support to high-level query resolution.Â
Scheduling Optimization
The backbone of any efficient call center operation is optimal agent scheduling. The Customer Care Solution ensures that the right number of agents are scheduled at the right time, minimizing customer wait times and abandoned calls.
Seamless Transition
Our system identifies scenarios where human intervention is optimal, offering a personalized and human-centric approach when necessary. This integration ensures that customers receive the best of both worlds – instant AI-driven solutions and the expertise of human agents.
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Customer Care Solution Benefits
Understanding Customer Intent and Providing Augmented Conversations
Our solution uses machine learning to understand the intent behind customer calls in real-time. This allows service representatives to:
- Quickly identify the caller’s intent, such as scheduling a payment or requesting an extension
- Engage in conversations aligned to that intent as well as business objectives
- Offer customized solutions tailored to the caller’s situation
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For example, if a customer calls about being late on a payment due to starting a new job, the system can quickly identify the intent as “schedule payment” and relay that to the service rep. The rep can then guide the customer through payment deferral options, reducing handle time and providing a positive experience.
Leveraging Machine Learning for Batch Analysis of Call Transcripts
Our solution employs an advanced machine learning workflow to analyze batches of call transcripts and continuously improve intent recognition capabilities:
- Explore data and discover dominant topics using unsupervised clustering
- Annotate data to label calls with identified intents and introduce an intent hierarchy
- Develop supervised models to classify intents based on the annotated training data
- Deploy models to enable real-time intent identification during live calls
- Track and visualize intent changes as calls progress using sliding windows
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This allows the system to continuously learn from data, refine intent categorizations, and provide more accurate real-time recommendations to service reps over time.
Seamless Integration Across the Analytics Lifecycle
Our solution seamlessly integrates Watson AI capabilities across the full analytics lifecycle from data acquisition to model deployment:
- Speech to text transcription via Watson Speech to Text
- Clustering and topic exploration in Watson Studio
- Annotation and labeling using Watson Knowledge Studio
- Machine learning model development in Watson Studio and Watson Machine Learning
- Real-time scoring of intents using deployed WML models and Watson Discovery Service enrichment
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This end-to-end integration accelerates time-to-value while leveraging best-in-class IBM AI technologies for optimized call center operations.
