AutoQA

AutoQA stands for automated quality assurance. It's an AI-powered solution that automatically assesses customer service interactions across multiple channels to evaluate agent performance and quality. Unlike traditional manual QA processes where only about 2 percent of conversations are reviewed, AutoQA provides 100 percent coverage of your support interactions, giving you a complete and unbiased overview of what's happening in customer conversations.

AutoQA evaluates interactions across all major support channels, including voice, chat, text, email, and screen capture. It handles multiple categories and languages without requiring additional resources or model training.

AutoQA typically evaluates tickets and interactions based on three key areas: resolution completeness, which assesses whether the agent provided a complete solution to the customer's problem; communication, which evaluates how well the agent communicated with the customer; and language proficiency, covering grammar, spelling, tone, and overall language quality. Some platforms also evaluate additional dimensions like technical proficiency, process adherence, soft skills (empathy, tone), and procedure compliance.

Tickets are typically scored 12 hours after they close.

Yes. Many AutoQA platforms allow you to create custom QA criteria and rubrics. You can set customized rules, define the signals that matter to your support operation (both quantitative and qualitative), and select weightage for scoring to align with your business needs.

Absolutely. If you or another reviewer disagree with how AutoQA scored a ticket or interaction, you can always manually edit and override any aspect of the score. Your manual changes will be reflected in your AutoQA reports.

Yes. AutoQA scores the quality of all support interactions across both human and AI agents. Some platforms separate and track AI agent interactions independently from human agent interactions so you can evaluate them separately.

The 'Solution' category identifies whether an agent offered a solution to the customer's problem. However, it's important to note that AutoQA does not discern whether the solution was the *correct* solution—only that one was offered. You have the option to manually override scores if a solution doesn't align with your internal standards.

Data protection varies by platform. For example, platforms using OpenAI's GPT-4o process your data under a strict Data Processing Agreement (DPA) with a zero retention policy, meaning your data is never used to train their AI models.

The behavior when merging tickets can vary depending on your AutoQA platform—check your specific platform's documentation for guidance on this scenario.

Yes. Many AutoQA platforms use generative AI to provide customized feedback and coaching for both managers and agents based on individual performance metrics, including tone, empathy, and procedure adherence. This helps teams improve their skills and customer service delivery faster.

AutoQA can access historical data spanning 1.5 to two years, which helps AI models learn your support patterns and improve predictions and recommendations.