Sales Intelligence AI for sales insights and conversation intelligence AI-powered

RingCX continues to streamline Quality Management with AI-powered scorecards

Share

Facebook Twitter Linkedin Copy link post URL copied
2 min read

Traditional Quality Management often feels like a burden, requiring a supervisor to review every interaction and manually fill out a scorecard. However, with most teams already stretched thin, the task of reviewing calls becomes overwhelming. Tarrytown Expocare Pharmacy, for instance, found it a struggle to review just 1% of their daily calls. 

AI Quality Management

A few months ago, we introduced automated AI Quality Management with an out-of-the-box ready AI scoring model that saves considerable time for customers like Tarrytown Expocare Pharmacy. RingCX provides consistent, unbiased analysis and a complete view of performance for all agents. Compared to traditional Quality Management solutions, RingCX AI Quality Management provided a significant leap in technology with its ability to automatically review and score every call.

While RingCX provides turnkey AI Quality Management, some businesses want customizable scoring based on their own quality checklists. These checklists might include ensuring agents greet customers by name at the beginning of a call or verifying they say “Thank you” at the end. However, they still need the same benefit of automated AI scoring to streamline their workflows.

That’s why we have introduced AI-powered scorecards for RingCX.

AI scorecard for contact center

AI Powered Scorecards

AI-powered scorecards eliminate the need for time-consuming, manual supervisor review by automatically filling out the scorecard for each call and calculating a score. This enhancement allows supervisors to track overall agent performance based on their unique business needs and quality management policies. AI-powered scorecards are a breath of fresh air, relieving businesses from this manual review process.

When defining a scorecard, each question can be assigned a weighted ranking. For instance, “Did the agent say Thank You?” might contribute 10% of the total score, compared to “Did the agent explain the refund policy?” making up 25% of the rating. This flexibility allows businesses to prioritize aspects of their quality checklist according to their unique needs.

Image of new RingCS AI scorecard

Scorecards are applied contextually based on the type of call. Multiple scorecards can be configured within the system, and RingSense will automatically determine the correct scorecard to apply for each call. Supervisors can still review and even override the AI score. Overridden responses are fed into RingSense, improving the scoring performance over time.

RingCX continues to disrupt the market by automating Quality Management for every business, whether they want to leverage the prebuilt model or customize it to their needs.

Originally published Jul 11, 2024

AI Quality Management

Learn how RingCX can help your business with AI Quality Management today

RingCX quality management

Share

Facebook Twitter Linkedin Copy link post URL copied

Related content