How AI is Transforming Agent Performance
Guest Blog by Ricardo Solano, Manager, Product Marketing, Genesys
Artificial intelligence (AI) has been heralded as the most important technological development of recent years and is set to radically change the way that people live – and work.
The call centre industry is just one sector that is feeling the effects of AI
The growing use of chatbots and virtual assistants, and their ability to take care of routine queries means that 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.
And with increasing demands on their time, its more critical than ever for call centre agents to be as productive, 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 and average handle time.
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.
The reality, however, is that until the advent of AI , managers only had enough time for random sampling. By using machine learning algorithms, data can be 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 relevant 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.