How to use Voice AI to improve and scale quality assurance

Increase your ROI through high-performance quality assurance powered by Voice AI

Ernest Lee

Marketing and Communications, AI Rudder
how to use voice ai to improve and scale quality assurance

Anyone who manages a call centre knows how challenging it is to keep the quality of customer interactions consistent across the organisation. Stories of customers calling a helpline thrice and getting different answers each time are far too common to be good for the customer service industry. The difficulty lies in the nature of the service itself—most interactions are done using voice calls. With that, precious information are stored as unstructured data in voice recordings. This makes it much more difficult to observe patterns and calibrate individual agent performance.

Another challenge is how quality checks are traditionally carried out. Until fairly recently, quality assurance (QA) in call centres are undertaken manually by managers and team leads. They listen in on a sample size of conversations or recorded calls that are selected at random and make notes against static scorecards. Engagement channels are often linear and feedback are given to each agent individually. By the end of the month or the quarter, the QA manager will have to repeat the entire process of evaluation for each agent, which takes far too much time to be scalable.

Fortunately, there is now a way to supercharge QA activities and deploy them at scale, thanks to Voice AI technology.

Audit 100% of your calls

Voice AI can analyse and evaluate all the calls that go through your call centre. Instead of limiting the review process to the sample size of calls, you can get a more holistic view of where your entire operation stands. This means identifying patterns that may have been missed—say, habitual errors that happen during peak or slack seasons—can be picked up and acted upon.

By fully utilising the available data, Voice AI can provide human QA officers with the kind of granular information that traditional QA processes cannot.

Accurate evaluations, and better training

Because you get access to more data, Voice AI can give a more complete and robust picture of each agent’s performance over time. You can even tweak and calibrate scorecards to reflect performance KPIs that are more relevant to each team, instead of having a static scorecard that’s used across the board.

Detailed performance insights can also help trainers develop more useful programs to address pain points surfaced by AI analytics. Where development plans used to be generic, Voice AI can pave the way for more personalised learning paths for each agent, complete with detailed feedback and metrics.

Deeper insights to drive decision-making

One key advantage of using Voice AI is the ability to perform in-depth speech analysis. Voice AI doesn’t only assess calls based on adherence to scripts, but also tone and language. AI-powered insights can be used to update your agent scripts, potentially bringing about better outcomes due to clearer guidelines.

Digging deeper, Voice AI can also identify behavioural patterns that need to be corrected. Does your agents fail to bring up relevant offers or identify upsell opportunities? Are their mental well-being protected and looked after in the event when customer service employees receive a heighten number of angry or abusive customers?  Tone and language analysis can help smoothen out the rough edges and provide prompts to manage difficult conversations. This can help your agents deliver the quality service your customers deserve, even boosting conversion simply by using the right words.

Deliver consistent, high-quality service

Customer experiences may vary based on the agent that takes the call. That scenario will become less and less common thanks to Voice AI. AI-powered voice assistants can act as first responders, picking up calls and answering concerns according to the most appropriate scripts.

With this layer of pre-screening, customers can expect the same quality of call handling regardless of circumstances. Once AI voice assistants have done the preliminary processing, calls can then be handed off to the most appropriate agent available—someone who is especially knowledgeable in that particular area of concern. The customer then gets the best possible service delivered by the best possible person without having to be put on hold for extended period of time.

Ensure the best voice interactions with customers

Ensuring that each customer interaction brings positive outcomes is nearly impossible if you solely rely on human effort. On the other hand, Voice AI sits at the intersection of speech analytics and quality management, using cutting edge speech technology and natural language processing to transcribe and analyse customer calls at a massive scale.

Whether you’re a large call centre or a modest-sized outfit, delivering quality customer interactions is an important factor to success. Voice AI opens the door to more accurate, automated, and efficient ways to gather insights on quality assurance.

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