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.

Technique

  • 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

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.

Technique

  • 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.

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.

Technique

  • 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.

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.

Technique

  • 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.
 

Do even more with Rubiscape

AI-driven organisations around the world use Rubiscape to solve their most pressing business problems.



Customer Service

Drag, Drop, Discover:
Insights Made Simple.

Dive deep into your data, create stunning visuals, and gain actionable insights with ease.

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Customer Service

Build, Deploy, Manage:
Streamline AI Workflow.

Build robust, Scalable ML/DL models with ease , automated workflows & data empowerment.

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Customer Service

Wrangle, Blend, Analyze:
Data Orchestration Refined.

Develop data fabric and flow designs with low-code, pro-code and self service platform.

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Customer Service

Manage, Evaluate, Automate:
Edge Analytics Seamless.

Handle data or device management with integrated ML models and M To M application.

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