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Handling the Challenge of
Automation with Data Analytics

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enhancing-call-quality-and-compliance-with-ai-powered

Enhancing Call Quality and Compliance with AI-Powered Analysis for a Leading Travel Company

Introduction

A prominent travel company, handling over 700 hours of customer service calls daily, faced significant challenges in ensuring quality and adherence to guidelines across English and Spanish conversations. The manual analysis of these calls was not only time-consuming but also limited in scope, leading to potential gaps in service quality and compliance. To address these issues, the company sought an AI-driven solution to automate call analysis and enhance overall customer service efficiency.

Challenges

The travel company encountered several hurdles in maintaining high standards of call quality:

  • Volume and Diversity of Calls: Analyzing 700+ hours of calls daily, especially in multiple languages, was an overwhelming task for the quality assurance team.
  • Inconsistent Quality and Compliance: Without comprehensive call analysis, inconsistencies in service quality and adherence to protocols remained unaddressed.
  • Resource-Intensive Process: The manual postmortem of calls required significant manpower, diverting resources from other critical customer service functions.

Solutions

To overcome these challenges, the company implemented an AI and LLM-based call analysis system with the following features:

  • Advanced Speech Recognition: The system included multilingual speech recognition capabilities to accurately transcribe calls in both English and Spanish.
  • AI-Driven Sentiment Analysis: Leveraging LLMs, the solution analyzed the sentiment and tone of conversations, identifying areas for improvement in customer interactions.
  • Automated Compliance Checks: The AI system was trained to recognize and flag deviations from established service protocols, ensuring consistent adherence to company guidelines.

Impact

The adoption of the AI-powered call analysis system led to transformative outcomes for the travel company:

  • Efficient Call Analysis: The system enabled the company to analyze 100% of call recordings, a significant improvement over the manual process, ensuring comprehensive quality and compliance oversight.
  • Improved Service Quality: Automated sentiment and compliance analysis helped identify training needs, resulting in a measurable improvement in customer service quality.
  • Resource Optimization: By automating the call analysis process, the company was able to reallocate staff to more value-adding customer service roles, enhancing operational efficiency.

The integration of AI and LLMs into the call analysis process not only streamlined quality assurance and compliance checks but also played a pivotal role in elevating the overall customer service experience within the travel industry.

Improvement in decision-making processes by

57%

Reduction in
risks by

67%

Decline in manual errors by

77%

Increase in the overall efficiency of business by

55%

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