Meet our Agent QA Reviews feature: Faster evaluations and targeted feedback

With our data-driven QA review process, there’s no more wasting time manually sifting through agent conversations.

Meet our Agent QA Reviews feature Faster evaluations and targeted feedback

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Agent performance drives customer happiness; it can make or break your customer satisfaction (CSAT) rating and net promoter score (NPS). Yet, time and time again, we’ve seen contact centres relying on random spot checks that only cover a small percentage of each agent’s customer interactions. This approach – often combined with manual quality assurance (QA) processes spread across multiple tools, spreadsheets, and CRMs – misses valuable opportunities to improve agent performance and service quality. 

That’s why we’ve enhanced our agent QA functionality with a new review feature – to provide targeted, more efficient evaluations. Our built-in scorecards aren’t just a singular tool for completing evaluations; they’re part of EdgeTier’s comprehensive Agent QA Reviews tool. The system starts by doing three things: it reads all your interaction data, uses AI to analyse each message for meaning and sentiment, and picks up on problematic areas, like when customers ask for a manager. It then labels these conversations to give visibility as to where agents need help. 

As a result, assessors don’t need to waste time manually sifting through conversations. Instead, they can focus on reviewing interactions that need attention, using the new QA scorecard as a tool to provide targeted feedback in a digestible manner directly to agents. Consider it the final piece in your agent QA puzzle. 

Let’s get into the details.

Meet our Agent QA Reviews feature Faster evaluations and targeted feedback

Introducing EdgeTier’s AI-powered Agent QA Reviews feature with built-in scorecards

Our new feature helps consolidate the entire QA process and connect the dots between your data, reviews, and reporting by accessing our AI capabilities. Here’s a closer look at how it works:

Centralised QA for efficient and productive processes

On top of juggling multiple systems, building and maintaining complex spreadsheets is time-consuming and inefficient. With our built-in scorecard, all the main parts are seamlessly integrated into the same platform, allowing you to view metrics, conversations, and evaluations side-by-side. Speed up reviews and ensure no important details are overlooked.

Customisable criteria for tailored evaluations

In the past, teams invested significant effort into building their own QA scorecards, but they lived outside of their other systems, which slowed down the review process. Our built-in scorecards are 100% customisable with tailored questions, categories, and scoring weights so that you can still align to your organisation’s unique standards but in a more streamlined manner. Whether it’s adapting to different teams, languages, or interaction styles (e.g., chat, email, or phone), this tailored approach allows you to maintain flexibility without the clunkiness of fragmented systems.

Fair and consistent reviews across teams

When there are multiple assessors, ensuring reviews are unbiased can be difficult as each person may interpret criteria differently. Our Reviews feature helps improve consistency by leveraging AI to tag interactions based on key indicators like sentiment, compliance issues, or tone. This ensures assessors are guided toward the most relevant conversations while the scorecard helps provide clear, standardised guidelines to follow during the review process. This approach fosters fairness and keeps agents motivated with fairer and consistent feedback.

Deliver targeted, actionable feedback to agents

Feedback from agent evaluations can live in spreadsheets for months, delaying performance improvements and slowing down customer satisfaction gains. We’ve overcome this hurdle by giving assessors the option to send feedback directly to agents as soon as the scorecard is completed. Now, there’s full transparency, and agents have the opportunity to correct issues as they’re spotted, resulting in faster improvements and a higher standard of customer service.

Integrated data for enhanced reporting and insights

When data is siloed across multiple platforms, it becomes difficult to extract meaningful insights and act on them quickly. Our built-in scorecard ensures all review data is instantly captured and stored within the greater EdgeTier system, making it accessible alongside metrics from all your other CX processes –  including any details pulled through third-party software integrations. This approach ensures you’re pulling reports with the most cohesive and up-to-date information available for faster decisions based on real-time data.

Introducing EdgeTier’s AI-powered Agent QA Reviews feature with built-in scorecards

Continued growth with EdgeTier’s unified customer insights

So, why is the EdgeTier Reviews feature so powerful? It ties into our system’s advanced AI-monitoring abilities to take the guesswork out of evaluations. 

It looks like this: Right now, if you’re relying on spot checks – roughly four or five conversations for each agent per month, you could be missing out on key interactions and pertinent information regarding agent behaviour. However, the EdgeTier system can already review 100% of your customer interactions and automatically label them based on sentiment and/or selected phrasing. For example, if a customer responds with “I don’t understand what you’re saying” or “I’m confused”, then the system flags the interaction for customer frustration. 

Now, you can take action on these insights. Assessors can sort conversations based on sentiment to find ones that need attention, then complete the reviewing process using the built-in scorecard, send feedback directly, and instantly save all the data in the same system for further analysis and reporting. 

The big win? A proactive approach to agent QA, where your team immediately focuses on the things that matter. It’s streamlined and efficient to help save time, increase output, and improve service quality overall.

Using the Reviews feature to make AI insights actionable for agent QA

How to use our Agent QA Reviews feature

Now, you know how the new feature is unique and why it’s important, but exactly how do you use it? We’ve designed the process to be incredibly user-friendly, so getting started is quick and simple:

  • Select an Interaction: Use EdgeTier’s AI monitoring to source the conversations that need the most attention. For example, the system will detect if a specific agent generates high levels of customer confusion when dealing with refund queries, and then highlight the conversations where this happens.
  • Complete the Scorecard: Review the conversation directly in the EdgeTier platform – your custom criteria and guidelines are built into the scorecard.
  • Send Feedback: The assessor can automatically send feedback to the agent once the review is completed.

It’s really that easy – we promise! Don’t believe us? We’re happy to jump on a call and show you.

Skip the random spot checks and boost efficiency with AI-powered agent QA

It’s time to say goodbye to outdated, complicated QA processes and welcome a new streamlined era with EdgeTier. Our AI-powered Reviews feature simplifies evaluations by making it easy to find the right interactions, improve rating consistency, and provide complete visibility into agent performance with an all-in-one centralised system. With customisable scorecard criteria and timely agent feedback, you can focus on coaching and development rather than wasting time on random spot checks.

Ready to see our Reviews feature in action? Request a demo today.

Customer Focused Leaders Trust EdgeTier

  • EdgeTier Assets - Car Trawler Logo

    "EdgeTier is no ordinary software product... It has completely changed how we work at CarTrawler."

  • novibet

    "It has reduced the time for the quality assurance process as it provides clear data and a very robust direction on where to look and what matters the most."

  • codere logo

    "We now have highly detailed understanding of agent performance, not just on key agent metrics, but also on how customers react to our agents and the emotions of our customers feel when talking to our team."

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