AI Integration for Call Quality Monitoring and Coaching Workflow

AI-Assisted Call Quality Monitoring and Coaching

1. Call Recording and Data Collection

1.1 Implementation of AI Speech Tools

Utilize AI-driven call recording software such as Verint or NICE to automatically capture customer interactions.

1.2 Data Storage

Store recorded calls in a secure cloud environment for easy access and analysis.

2. Automated Transcription

2.1 Speech-to-Text Conversion

Employ AI transcription services like Google Cloud Speech-to-Text or Amazon Transcribe to convert audio recordings into text format.

3. Call Quality Analysis

3.1 Sentiment Analysis

Leverage AI tools such as IBM Watson or CallMiner to analyze customer sentiment based on the transcribed text.

3.2 Keyword and Phrase Identification

Implement tools like Speechmatics to identify frequently used keywords and phrases that indicate customer concerns or satisfaction.

4. Performance Scoring

4.1 Establish Scoring Metrics

Define key performance indicators (KPIs) such as call resolution rate, customer satisfaction score (CSAT), and average handling time (AHT).

4.2 Automated Scoring System

Utilize platforms like Gong.io or Chorus.ai to automatically score calls based on established KPIs.

5. Coaching and Feedback

5.1 AI-Driven Coaching Recommendations

Use AI to provide personalized coaching recommendations to agents based on their performance scores and identified areas for improvement.

5.2 Feedback Sessions

Schedule regular feedback sessions where supervisors can review AI-generated insights and discuss performance with agents.

6. Continuous Improvement

6.1 Ongoing Training Programs

Implement AI-driven training platforms like Lessonly or MindTickle to facilitate continuous learning for customer service agents.

6.2 Performance Monitoring

Continuously monitor call quality and agent performance using AI analytics to ensure sustained improvement and adherence to quality standards.