The world has moved out the office and into the home. Remote working and a growing customer trust in virtual and online engagements have transformed how companies connect with their customers and manage their interactions.
As McKinsey points out, remote channels have become critical in managing customer relationships and generating revenue.
This changing landscape has put the call centre front and centre, making it one of the most relevant and trusted tools for customer and company alike.
However, contact centres have their own challenges to manage within this space, particularly when it comes to quality assurance (QA) and customer engagement. Language differences, language barriers and limited visibility have traditionally impacted on customer experiences and satisfaction – until now.
Artificial intelligence (AI)-powered speech analytics tools are busy transforming QA, engagement and contact centre potential.
To become compelling components of any customer engagement strategy, the contact centre needs to harness the potential of artificial intelligence (AI)-driven solutions to meet changing consumer demands, and to allow for deeper connections with customers that deftly remove language barriers.
“We didn’t have this many interactions with our customers in the past which can be considered challenging, but what I consider to be an opportunity,” says Nosihle Mbatha, artificial intelligence manager at Rewardsco.
“Everybody is interacting in different ways across multiple channels and we have to engage with more people and fully realise the potential of the omnichannel contact centre platforms. We need to ask how we can adapt, how we can get more customers, and how we can deliver both quality and compliance.”
On one hand, the size of the organisation will influence the tools that it puts at its customer’s disposal. For Rewardsco, the contact centre is predominantly outbound with around 1 300 agents across sales, inbound and other customer interactions; and with nearly 40 QA assessors monitoring the agents to ensure quality. This is a situation that’s replicated across multiple companies, globally, as they juggle the need for quality and compliance against the limitations of time and the sheer volume of calls.
“Traditional monitoring with tick sheets and spreadsheets used to be the only way of managing both quality and compliance, but today this approach is far too time consuming and costly to be of value when measured against the sheer volume of customer engagements,” says Rod Jones, industry analyst and Callbi Brand Ambassador.
“These old methodologies are one-dimensional and often don’t fully capture the real situation, or the reason why a call doesn’t resonate with a customer, or why the customer’s matter ended up on Hello Peter or in the social media and putting the company’s reputation at risk. And often these problems are triggered by poor understanding caused by languages or accents.”
The problem is that the reaction is usually to point fingers at the contact centre and to blame the agents or the managers for failed customer interactions.
Alternatively, a typical reaction is for organisations to spend more money on improving agents’ performance before even determining what the real problem is. There are questions that have to be answered that the traditional contact centre systems are not geared to unpack. Questions that ask if the agents are knowledgeable enough, if they are actually empowered to resolve the issue, or if there is a process inhibiting problem resolution.
“The default mindset when there is a quality problem is, it must be an agent problem,” says Jones. “What should be happening is that the metrics we use and the ways in which we interpret these metrics have to change.
“They have to be aligned to what the customer wants and to true issue resolution and root cause analytics, and the traditional manual methods can’t keep up with the sheer scale of this analysis or deliver the rich insights that are needed to drive operational improvements.”
In the context of call quality there are two things that the contact centre wants to achieve – customer satisfaction, and measuring customer feedback and information.
Which is where AI-driven speech analytics steps in. Implemented intelligently, speech analytics rapidly sifts through vast numbers of recorded calls extracting incredibly valuable information and provides deep actionable insights.
Speech analytics takes away the need for contact centre quality assessors to randomly select the calls or agents that they plan to assess. Instead, the speech analytics solution can be configured to assesses every single call.
The reports that the system produces can be interpreted to give the operations team insights that drive relevant change.
“Speech analytics is a tool that can be used to check 100% of your sales, calls and processes, and that turns quality assurance teams into data analysts who deliver meaningful reports, insights and recommendations to the business,” says Jones. “These are true actionable insights that enable real performance transformation.”
In some cases, there may be some resistance within the call centre as agents worry that they are being watched or that the quality assurance team are in danger of losing their jobs. These may be reasonable concerns, but ones that can be assuaged by the business.
Mbatha adds: “Yes, there are concerns from agents, but what if these insights help them too? What if the speech analytics tool can show them that they’re talking too fast and that’s why their customers don’t understand what they’re saying? What if it gives the business the opportunity to adapt its training so agents are better prepared? This is the value of speech analytics in the contact centre, especially when it comes to quality and assurance.”
Speech analytics can provide agent, call centre and business with immense value. It can subtract the finger pointed at the agent when things go wrong, add the insights needed to transform engagement, and deliver the kind of results that businesses really need in a frenetic, digital market.