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Contact Center AI Solutions can Carve a Lasting Growth Trajectory!
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87% of contact center leaders believe that AI boosts agent productivity.
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AI-powered contact center solutions can help mitigate the high agent attrition rate (20-30%), often caused by inadequate training.
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87% of CX leaders report that conversational AI-powered contact center solutions have effectively reduced agent burden.
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Real-time agent assist tools in contact centers have been observed to help boost CSAT by 65%.
An AQM Ecosystem Built for Revenue Growth
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Key Business Benefits of VQC’s Agent Quality Management
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How VQC Ensures Greater Contact Center Value Creation?
VQC’s generative AI and conversation intelligence-powered model streamlines your QC with multiple levers to create a profound business advantage.
Purpose-built AI to Accelerate Contact Center Outcomes
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Industries We Serve
AxlRev’s AI & ML-driven technology delivers exceptional results across various industries
Our revenue acceleration solutions are designed to address industry-specific challenges and opportunities, ensuring that businesses across multiple sectors can achieve their revenue growth goals effectively. With our advanced sales enablement tools, you can transform your operations and drive revenue in the following industries
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Collections
Efficiently track and follow-up with defaulters and streamline debt recovery processes.
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Healthcare
Streamline patient interactions and elevate customer care with AI-enhanced solutions.
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BFSI
Drive revenue in banking, financial services, and insurance through automated insights.
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Telecom
Optimize customer engagement and support with data-driven strategies.
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E-commerce
Boost sales, conversions, and customer retention with AI-driven insights.
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Technology
Lead the tech industry with AI-powered solutions for revenue acceleration.
FAQs
What is AI-powered QC?
AI-powered Quality Control (QC) refers to the usage of AI algorithms and technologies to assess, monitor, and enhance the quality of interactions between a contact center agent and customers. It involves the automated analysis of various metrics such as call recordings, agent performance data, and customer feedback to identify areas for improvement and ensure adherence to predefined quality standards and compliance.
How does AI-powered QC improve quality control processes?
AI-powered QC enhances quality control processes by leveraging advanced data analytics, conversation intelligence, GenAI, NLP, and LLM techniques to analyze large volumes of data in real-time. It enables the identification of trends, patterns, and anomalies in agent interactions, allowing for proactive intervention and targeted coaching to improve performance. Moreover, AI-powered QC can automate repetitive tasks such as call scoring and evaluation, freeing up valuable time for quality assurance teams to focus on strategic initiatives and areas requiring human judgment.
What types of industries can benefit from AI-powered QC?
VQC can be implemented across a wide range of industries and organizations. Currently, we have demonstrated expertise in helping clients in the telecom, IT, healthcare, collections, BFSI, and e-comm industries.
What are the key features of an AI-powered QC system?
VQC has a powerful list of game-changing features including
- Sentiment Analysis: Decoding emotional undertones for tailored CX.
- Unique Keyword Mapping and Voice of Customer: Creating a dynamic map of evolving customer preferences.
- Call Summaries: Simplifying complex conversations into actionable insights.
- AI Speech-to-Text: Transforming spoken words into actionable data.
- AI-Powered Call Scoring: Objective evaluation of calls for performance assessment.
- Automated Transcripts: Efficiently document customer-agent conversations.
- Dialer and CRM Integration: Integrate with the CRM and CIM systems of your choice with scope of further customization.
- Agent Performance Management: Automating brand guideline compliance for aligned interactions.
How accurate is AI-powered QC compared to traditional QC methods?
Automated QC is far more accurate than traditional QC methods. Traditionally, only 5-10% of calls were analyzed using human QC FTEs, whose feedback was inaccurate and lacked standardization due to bias and human errors. AI QC covers 100% of calls and analyzes them using sentiment analysis, voice of customer, compliance standards, pitch adherence, and several other agent performances and CX KPIs.
Can AI-powered QC be integrated with existing quality control systems?
Yes, VQC can integrate with your current QC mechanisms and CRMs.
What are the potential cost savings associated with implementing AI-powered QC?
AI-powered QC has showcased up to 75% cost reduction on QC FTEs, process efficiency, and 100% QC coverage and accuracy. Beyond that, the improved QC insights enable CS teams to improve their service quality and uncover further revenue outcomes.
How does AI-powered QC handle complex data sets and variability?
AI-powered QC handles complex data sets and variability using advanced conversational AI, genAI, machine learning, and NLP algorithms. These algorithms are trained on diverse datasets to recognize patterns, anomalies, and context-specific nuances within interactions. Through continuous learning and adaptation, AI can effectively analyze and interpret variations in data, ensuring accurate evaluation and actionable insights for improving quality control processes in contact centers.
What are the main challenges of implementing AI-powered QC?
Main challenges of implementing AI-powered QC:
- Data quality and availability: Access to sufficient and high-quality data is crucial for training accurate AI models.
- Model interpretability: Understanding how AI algorithms reach decisions is essential for trust and regulatory compliance.
- Integration with existing systems: Seamless integration with legacy systems and workflows can be complex and time-consuming.
- Privacy and security concerns: Safeguarding sensitive customer data and complying with regulations such as GDPR or HIPAA is paramount.
- Training organization-specific language models (LLM): Customizing AI models to understand industry-specific terminology and nuances requires significant resources and expertise.
How can companies ensure data privacy and security with AI-powered QC systems?
Ensuring data privacy and security with AI-powered QC systems:
- Encryption: Utilize encryption techniques to protect data both in transit and at rest, safeguarding it from unauthorized access.
- Access controls: Implement robust access controls and authentication mechanisms to restrict data access only to authorized personnel.
- Anonymization: Remove personally identifiable information (PII) from datasets used for AI training to mitigate the risk of data breaches.
- Regular audits: Conduct regular audits and assessments to identify and address security vulnerabilities and ensure compliance with relevant regulations.
- Secure infrastructure: Deploy AI-powered QC systems on secure infrastructure with built-in security features and protocols to prevent unauthorized access and data breaches.
Why settle for anything less than extraordinary?
Partner with Vsynergize and unlock the true potential of your business. Boost Your Productivity | Expand Your Global Reach Unleash Your Innovation | Achieve Unparalleled Success.