Welcome to the forefront of contact center technology! In this post, we’re excited to explore three groundbreaking demos presented by John Ortiz, Technology Sales Manager at MiaRec. These demos showcase the transformative power of generative AI in revolutionizing contact center quality assurance (QA), offering a glimpse into the future of automated excellence.
But before we dive into these innovative demonstrations, it’s important to grasp the significance of automated quality assurance (Auto QA). Understanding its pivotal role will illuminate how it overcomes the limitations of traditional QA methods and enhances overall contact center performance.
Auto QA is a transformative technology that automates the evaluation of contact center interactions based on predefined and customizable scorecards. Unlike traditional manual QA, where human reviewers listen to a small percentage of calls (often just 1%), Auto QA leverages AI to assess 100% of your calls. This technology addresses several pain points:
Now, let’s explore how generative AI further enhances Auto QA through three key features demonstrated by John Ortiz.
The first demo introduces the Additional Context Window, a new feature designed to refine the accuracy of Auto QA evaluations.
The Additional Context Window allows you to provide extra context for each scorecard question. This is particularly useful for subjective questions where interpretations can vary. For example, the question "Did the agent greet the caller appropriately?" can be vague without additional context.
By defining what "appropriately" means—such as thanking the caller, requesting their ID, and confirming it—the AI can evaluate the response more accurately and consistently.
In this video, John demonstrates how to use the Additional Context Window within the MiaRec platform. The video will showcase how adding context improves the objectivity of evaluations and enhances overall accuracy.
Our second demo features the AI Prompt Designer, a powerful tool for customizing and refining AI prompts used in Auto QA.
The AI Prompt Designer lets you build, test, and optimize AI prompts in a controlled sandbox environment. This feature allows you to create prompts for extracting specific data from calls and ensures they meet your needs.
You can import your scorecards into the Prompt Designer, test them with sample calls, and refine them based on the results. This customization helps achieve more accurate evaluations.
In this video, John provides a walkthrough of the Prompt Designer, demonstrating how to build and test prompts for specific call data, such as customer orders, and refine scorecards for better accuracy.
The third demo highlights the LLM-Based Sentiment Analysis, the latest advancement in sentiment analysis.
LLM-Based Sentiment Analysis leverages generative AI to understand the full context of conversations, rather than relying on keywords or simple language models. This new approach allows for a nuanced assessment of call outcomes.
This advanced sentiment analysis can accurately score calls based on the context of the entire conversation and the end results. For example, a call that starts negatively but ends on a positive note will be scored appropriately.
John will walk us through how the new sentiment analysis works, showing how it evaluates calls for customer satisfaction and effectiveness based on the entire conversation context.
Interested in integrating MiaRec’s Auto QA into your contact center operations? The process is simple:
John and the rest of the MiaRec team are ready to help you optimize your contact center’s quality assurance with cutting-edge AI technology.