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.

What is Auto QA?

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:

• Limited Visibility: Manual QA provides limited insights into call volume, making it difficult to gauge overall agent performance accurately. Auto QA eliminates this issue by offering comprehensive visibility into every call.
• Scalability: Evaluating every call manually is impractical. Auto QA scales effortlessly to cover all interactions, enhancing customer experience and satisfaction.

Now, let’s explore how generative AI further enhances Auto QA through three key features demonstrated by John Ortiz.

Additional Context Window

The first demo introduces the Additional Context Window, a new feature designed to refine the accuracy of Auto QA evaluations.

What It Is:

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.

How It Impacts Accuracy:

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.

Watch the Demo:

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.

AI Prompt Designer

Our second demo features the AI Prompt Designer, a powerful tool for customizing and refining AI prompts used in Auto QA.

What It Is:

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.

How It Enhances Auto QA:

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.

Watch the Demo:

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.

LLM-Based Sentiment Analysis

The third demo highlights the LLM-Based Sentiment Analysis, the latest advancement in sentiment analysis.

What It Is:

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.

How It Enhances Auto QA:

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.

Watch the Demo:

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.

Getting Started with MiaRec’s Auto QA

Interested in integrating MiaRec’s Auto QA into your contact center operations? The process is simple:

1. Discovery Call: Begin with a call to assess your contact center’s fit for the solution.
2. Free Trial: Test a customized MiaRec instance with your real call data.
3. Setup and Support: After a successful trial, move to production with full support and ongoing assistance.

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.