GENERATIVE AI FOR SERVICE & SUPPORT TEAMS
Enhance customer service and streamline support with generative AI
Empower your teams to focus on building customer loyalty and retention, and stop wasting time on time-consuming tasks like ticket categorization and response generation.
Deliver exceptional customer service and support at scale
As service and support teams scale, they’re confronted with mounting challenges—rising ticket volumes, greater customer expectations, and increased competition.
Keeping teams up-to-date on changing products and policies is a challenge, leading to poor customer service.
Time is wasted on manual, repetitive tasks like data entry, which are prone to human error.
Critical data is trapped in separate systems, leading to inefficiencies and poor responsiveness.
Ticket categorization and follow-ups are tasks that take time away from resolving complex issues and providing personalized support.
GENAI FOR SERVICE & SUPPORT
Transform service & support with GenAI
Vertesia's generative AI solutions are built to transform your customer support operations.
Accelerate issue resolution
Improve service forecasting
Strengthen quality control
Analyze customer sentiment
Prevent customer churn
Unify the business
Proven use cases for service and support teams
Built in collaboration with service and support leaders, our solutions help teams resolve issues faster, reduce ticket backlogs, and deliver consistent, high-quality customer experiences.
Accelerated CSR training
Real-time sentiment analysis
Ticket summarization, prioritization, and routing
Personalized and on-brand response generation
Proactive churn risk identification
Intelligent demand forecasting
Automated performance reporting
Proactive maintenance planning and communications
Intelligent call transcripts
Comprehensive knowledge bases
Translation and localization of existing documentation
Skills matching and gap analysis
Customer service automation
Customer service departments face a high volume of inquiries, leading to long wait times and ineffective responses. Additionally, limited data analysis hinders the identification of opportunities for improvement.
Step 1: Data integration & analysis
The platform integrates with customer service platforms to collect and analyze customer interactions. LLMs process this data to understand customer needs and identify patterns.
Step 2: Automated response generation & personalization
LLMs analyze incoming customer inquiries and automatically generate personalized responses based on the defined context. The platform ensures that responses are consistent with brand voice and customer service guidelines.
Step 3: Agent support & service optimization
LLMs provide customer service representatives with real-time support by suggesting relevant responses, identifying potential solutions, and escalating complex issues. The platform analyzes customer interactions to identify trends, areas for improvement, and opportunities for service optimization.
Churn prediction & prevention
It is difficult to predict and prevent customer churn. Businesses are relying on reactive retention strategies that may not be effective in addressing the underlying causes of churn. Limited insights and predictive capabilities hinder the ability to identify at-risk customers early on and implement timely interventions.
Step 1: Data integration & analysis
The Vertesia platform processes customer data from various sources, including demographics, purchase history, customer support interactions. LLMs analyze this data to identify patterns and indicators of at-risk customers.
Step 2: Churn risk prediction & segmentation
LLMs identify customers at risk of churning based on data analysis and predictive models. The platform provides key characteristics of at-risk segments.
Step 3: Proactive intervention & retention strategy
The Vertesia platform provides recommendations for proactive interventions and personalized retention strategies for each unique customer segment.