AI is Transforming Contact Centre Agent Performance

It’s no secret – artificial intelligence is transforming contact centre agent performance says Ricardo Solano, Solution Lead at Genesys

“The biggest room in the world is the room for improvement,” the late German statesman Helmut Schmidt is reported to have said.

Never has this been more true for contact centres. As self-service options, chat bots and virtual assistants increasingly take care of routine queries, contact centre agents are left to handle more complex and relationship-dependent issues. Often by the time a live agent gets involved, customers have already tried (unsuccessfully) to solve the issue themselves leaving them frustrated and irritated. That means the employee’s job is even harder.

There’s also the issue of increased inquiry volumes due to the rise in digital channels. Oh, and the fact that a high percentage of customers want to connect directly with a live agent because they believe that’s how they get the best service. With increasing demands on their time, its more critical than ever for call centre agents to be as productive, efficient and effective as possible, particularly as staffing accounts for around 75 per cent of contact centre costs.

To improve performance, contact centres have traditionally focused on a variety of quality assurance metrics, such as first contact resolution, average handle time and Net Promoter Scores (“NPS”). Then, as it became possible to record thousands of calls digitally, the focus shifted to monitoring what agents were actually saying to callers so that entire teams could learn from the successes and mistakes.

Artificial intelligence: The path to higher quality

The reality, however, is that until the advent of artificial intelligence (AI), managers only had enough time for random sampling. Research conducted in 2017 by industry analysts ContactBabel found that 80 per cent of contact centre managers said the greatest challenge to managing performance and quality was insufficient time to analyse and use data.

AI has changed all that. Without this technology supervisors have a limited view into how their teams or individual agents are performing. With speech analytics thousands of calls are converted into text data. Then, by using machine learning algorithms, that data is analysed to uncover meaningful insights about the actions that produce a successful outcome from a call (and those that do not) and then measures performance against those benchmarks.

The fact that AI makes it far more efficient to analyse every call means supervisors gain a comprehensive view of team and individual agent performance. Speech analytics not only detects the phrases that have the biggest impact, but also key emotions and whether the agent builds rapport, is courteous or has a sense of urgency. AI can match such behaviour against desired outcomes, indicating where, for example, a sense of urgency in the agent’s voice more frequently leads to upsells with certain types of customers.  Since all conversations have two sides, the technology also monitors the speech of callers, potentially uncovering phrases or tonal indicators that the agent may have missed. This can also uncover important insights such as why customers are contacting the company, why multiple contacts are needed to resolve specific issues, what processes cause frustration and whether contact centre agents are providing an appropriate level of service.

A picture is worth a thousand words

Visualisation – the presentation of data in readily-understood charts and graphs – means that supervisors can easily grasp the important trends and details uncovered by AI. They can see how individuals or teams are faring and spot the signs of above-average or below-par performance across all channels. With dashboards updated as frequently as every 15 minutes, supervisors have a near real-time view, enabling them to send notifications to agents’ screens, with prompts about the right tactic or set of words to use to achieve a sale, an upsell or find the right information.

Supervisors can also send an agent the recording of a particular call so they can learn what worked well and where improvements can be made. Without the need for the intervention of a quality analyst, these can be used to form best-practice guidelines and libraries for sharing across the organisation.

As AI solutions evolve we can expect agents to benefit from more real-time guidance, including flagging relevate customer and product information as well as recommendations, as they handle inquiries..  The key point here is that the insights derived from AI are actionable – not obscure points that can only be fully understood by data analysts. This is practical guidance that delivers direct improvements in performance.

It is this combination of AI and the human skills of supervisors and agents that will continue to transform contact centre performance, replacing the traditional methods that are no longer adequate for optimisation in a more complex world.

Additional Information

Ricardo Solano is Solution Lead at Genesys

Genesys® powers more than 25 billion of the world’s best customer experiences each year. Our success comes from connecting employee and customer conversations on any channel. Every day, 11,000 companies in more than 100 countries trust our #1 customer experience platform to drive great business outcomes and create lasting relationships. Combining the best of technology and human ingenuity, we build solutions that mirror natural communication and work the way you think. Our industry-leading solutions foster true omnichannel engagement because they perform equally well across channels, on-premises and in the cloud. Experience communication as it should be: fluid, instinctive and profoundly empowering.

For additional information on Genesys visit their Website or view their Company Profile

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