Customer Service
Driving Innovation
Rubiscape's Impact in the
Customer Service Team
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Listening In: Insights with Audio Analytics
Beyond speech, audio reveals emotions, behaviors, and trends, driving better decisions.
Goal - To identify anomalies in customer-operator interactions.
- To identify factors affecting customer satisfaction .
- Behavioral analysis of Customer and Operator.
- To identify anomalies in customer-operator interactions.
- To identify factors affecting customer satisfaction .
- Behavioral analysis of Customer and Operator.
Technique - Audio processing, Audio Diarization, Speech to Text, Text translation, Sentiment Analysis, Topic Modelling.
- Audio processing, Audio Diarization, Speech to Text, Text translation, Sentiment Analysis, Topic Modelling.
Impact - Improvement in CSAT and reduced customer complains.
- Identify most frequently inquired new requirements by the customer.
- Early warning for customer issues and proactive corrective actions.
- Better operator performance
- Improvement in CSAT and reduced customer complains.
- Identify most frequently inquired new requirements by the customer.
- Early warning for customer issues and proactive corrective actions.
- Better operator performance
Delight Purchase: Mastering Sales & Service
Exceed expectations, build loyalty, and fuel repeat business with exceptional after-sales support.
Goal - To represent the root cause of failures.
- To determine the time for first failure of an equipment part and forecast number of future breakdown calls for that part.
- To identify interdependency of part failures.
- To represent the root cause of failures.
- To determine the time for first failure of an equipment part and forecast number of future breakdown calls for that part.
- To identify interdependency of part failures.
Technique - Statistical Analysis, Root cause Analysis, Reliability Analysis, Time Series Forecasting, Visualization.
- Statistical Analysis, Root cause Analysis, Reliability Analysis, Time Series Forecasting, Visualization.
Impact - Based on root causes of failure, location/manufacturer wise strategies can be planned to avoid early failure.
- Reduction in number of breakdown calls and associated cost.
- Early warning breakdown calls helps in taking preemptive measures.
- Identified sequence of patterns for failure of parts, helps in preventive actions.
- Based on root causes of failure, location/manufacturer wise strategies can be planned to avoid early failure.
- Reduction in number of breakdown calls and associated cost.
- Early warning breakdown calls helps in taking preemptive measures.
- Identified sequence of patterns for failure of parts, helps in preventive actions.
See-Through Repairs: AI Detects Damage
Pinpoint defects faster, save costs, and optimize production with intelligent damage detection.
Goal - To identify and classify damages such as scratches, dents or cracks in vehicles.
- To allow early identification of damages and timely maintenance interventions.
- To enable automated and accurate inspections for insurance claims.
- To identify and classify damages such as scratches, dents or cracks in vehicles.
- To allow early identification of damages and timely maintenance interventions.
- To enable automated and accurate inspections for insurance claims.
Technique - Image augmentation, Image processing, Image classification, Object detection, Visualization.
- Image augmentation, Image processing, Image classification, Object detection, Visualization.
Impact - Accelerated claims processing, reducing delays and administrative burden.
- Reduced post-purchase repair costs, to enhance ownership experience.
- Enhanced brand image, to attract and retain customers.
- Boosted customer satisfaction and loyalty.
- Accelerated claims processing, reducing delays and administrative burden.
- Reduced post-purchase repair costs, to enhance ownership experience.
- Enhanced brand image, to attract and retain customers.
- Boosted customer satisfaction and loyalty.
Unveiling Loyalty: Predict Customer Lifespan
AI models pinpoint high-value customers, driving targeted engagement and long-term growth.
Goal - To identify high, medium, and low-value customer segments.
- To provide personalized offers and experiences to customers.
- To allocate resources efficiently to businesses for targeting customers with the highest CLV potential and predict customer churn.
- To identify high, medium, and low-value customer segments.
- To provide personalized offers and experiences to customers.
- To allocate resources efficiently to businesses for targeting customers with the highest CLV potential and predict customer churn.
Technique - Feature Engineering, Segmentation Techniques, RFM Analysis, Clustering and classification modeling, Visualization.
- Feature Engineering, Segmentation Techniques, RFM Analysis, Clustering and classification modeling, Visualization.
Impact - Guided resource allocation, marketing strategies, and customer service efforts.
- Offering cross-selling and upselling opportunities to customers with CLV potential.
- CLV helps businesses identify risks associated with over-reliance that encourages diversification and risk management strategies.
- Guided resource allocation, marketing strategies, and customer service efforts.
- Offering cross-selling and upselling opportunities to customers with CLV potential.
- CLV helps businesses identify risks associated with over-reliance that encourages diversification and risk management strategies.
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