Overview
A retail and e-commerce enterprise aimed to improve customer service efficiency and consistency across multiple communication channels including chat, email, voice, and social media.
The objective was to increase first contact resolution, improve customer satisfaction, reduce handling time, and lower service costs while ensuring consistent support quality across all channels.
Challenge
Customer support operations were fragmented and inefficient across channels:
- Disconnected support systems across chat, email, voice, and social platforms
- High response and resolution times due to manual handling
- Inconsistent customer experience across different channels
- Large volume of repetitive queries overwhelming support teams
- High cost per contact due to increasing ticket volumes
This resulted in poor customer experience, high operational costs, and low service efficiency.
Solution
- An AI-powered multi-channel customer service system was implemented to unify and optimize customer interactions:
- Unified Omnichannel Support Layer
Consolidates customer queries across chat, email, voice, and social platforms - AI Virtual Agent for First-Level Resolution
Handles common queries and resolves issues without human intervention - Agent Assist Copilot
Supports human agents with real-time suggestions, context, and responses - Intelligent Routing & Prioritization
Directs queries to the right channel, team, or resolution path - Conversation Understanding Engine
Maintains context across channels for seamless customer experience - Automated Deflection System
Resolves queries via self-service before they become tickets
- Unified Omnichannel Support Layer
KPIs Impacted
- CSAT (Customer Satisfaction Score)
Improved through faster and more consistent responses - First Contact Resolution (FCR)
Increased via better routing and AI-assisted resolution - Average Handle Time (AHT)
Reduced through agent assistance and automation - Cost Per Contact
Lowered by reducing manual intervention and improving containment - Deflection Rate
Increased through self-service and AI resolution layers
Results
- 10–25% improvement in CSAT
- 15–35% increase in first contact resolution
- 20–40% reduction in average handle time
- 15–30% reduction in cost per contact
- 25–60% increase in deflection rate
Business Impact
- Faster and more consistent customer service across all channels
- Reduced operational cost of support teams
- Improved customer retention and satisfaction
- Scalable service model without proportional increase in headcount
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