Advanced AI is enabling contact centre leaders to extract valuable management information (MI) from voice conversations, highlighting inefficiencies and creating new automation opportunities.
Calls are at the heart of the contact centre. But, for the longest time, they have also been a blindspot for businesses.
When something goes wrong, most customers would rather pick up the phone than send an email or lodge a support request. That’s why calls are by far the most common form of communication in the contact centre. They are also the most expensive communication type to service, given their time and resourcing cost as well as the admin created around them. It’s estimated that the fully loaded cost per call is in the range of $6-$8, or even higher.
Calls could be a major source of insight and opportunities for the enterprise. The problem is that it’s been extremely difficult to understand or analyse them in any significant way. A typical call centre will receive at least 4,000 calls a month, and the task of monitoring them is usually left to a small quality assurance (QA) team of no more than 20 people. A small team like this has little choice but to select partial, random samples of calls to investigate.
Realistically, a QA agent can maybe process 25 calls a month split across a handful of agents. Under this operating model - which has become standard practice for contact centres globally - complete coverage and visibility into calls is a pipe dream.
Calls remain a major blindspot for businesses. In terms of risk and compliance, but also for revenue and upselling opportunities. Fortunately, recent innovations in AI and natural language processing (NLP) are changing this.
Communications Mining for calls
NLP - a branch of AI focussed on helping machines understand human language - has greatly advanced in performance, accuracy and reliability in recent years. Through Communications Mining software, NLP is enabling contact centre leaders to gain unprecedented insight into every call they service.
Calls have traditionally been difficult to analyse because they produce no structured data. Any insight has to be extracted manually, usually through post-call analysis or logging by the same employees who service the call. The benefit of using advanced NLP is that it can process and understand all this information rapidly, and with limited manual input.
Recorded calls can be easily transcribed into text which is then analysed en masse, at speed and scale, by Communications Mining. After a brief training period, the underlying AI models are able to extract the most important information as structured data from masses of calls instantaneously. In only a matter of weeks post-deployment, the business has complete insight and visibility into every call that passes through the contact centre.
This real-time extraction of data from calls is enabling a number of powerful analytics and automation use cases in the contact centre:
Transforming service quality
Communications Mining removes the effort of analysing and monitoring the calls processed by the contact centre. It achieves what used to be impossible with humans alone - complete visibility over all customer conversations. Furthermore, it automatically extracts invaluable insights from calls - including customer intent, contact drivers and sentiment.
Contact centre leaders can use this insight to identify previously unknown issues, target the real causes of customer churn, and identify valuable opportunities for automation and self-service. Most importantly, Communications Mining allows them to do this - and track the results - in real time.
Communications Mining offers custom in-platform reporting and dashboards for actively monitoring quality of service trends at all service levels. Customisable alerts can be configured that are triggered by specific events or trends, such as deviations from acceptable quality of service levels. It’s a new capability to help you monitor and improve service and the customer experience.
Enhancing automation for the contact centre
Communications Mining is also helping to enhance agent productivity through automation. Calls usually demand a significant amount of extra admin from agents. This most often comes in the form of logging call reasons and outcomes from all the conversations they service. This post-call activity is important work, but it’s taking agents away from what they do best - servicing customers and processing requests.
Unproductive wrap-time wastes agents’ specialist skills and limits the capacity of a contact centre. What’s more, the output isn’t always reliable. Agents know their wrap time isn’t seen as productive by the business, so there’s a tendency to rush the busy work so they can get to the next call in their queue. Human error is all too common, leading to ineffective MI and potential issues down the line.
Fortunately, Communications Mining can drastically reduce the lag time between calls. NLP solutions have gotten so sophisticated that they can accurately analyse and extract caller intent, sentiment, call reason and outcome data from conversations. Communications Mining automates the process of information capture from calls, classifies cases, and extracts the most important insights from a conversation. When integrated with automation and workflow tools, it can even auto-route and auto-triage transactional requests.
In this way, contact centre leaders are eliminating call logging and cutting unproductive wrap time. Capacity is liberated and agents can focus on actually performing the work and processing the requests.
Improving agent coaching
Quality coaching is difficult in the contact centre environment. Agents are typically only given feedback when they’ve done something wrong - and they usually have to wait until they've been selected for review.
Businesses dedicate limited resources to their QA teams, and they can’t dedicate enough time and effort to monitor and coach every individual agent. As a result, QA can only focus on addressing the ‘problem agents’ who increase their operational risk. The top performers rarely receive any meaningful feedback or development.
It’s a system that underserves both high-achievers and developing agents. Top performers feel unsupported and unchallenged in their work; developing agents feel singled out while also not being given detailed and actionable feedback for improvement. Attrition on both ends has long been a problem.
Yet Communications Mining is helping to address this. Through the AI-enabled monitoring of every call, the contact centre achieves full and detailed oversight over all agents. With real-time alerts, issues can be flagged as they happen meaning agents don’t have to wait weeks or months for quality feedback that is immediately actionable. The depth and coverage of insight provided by Communications Mining also means that the managers aren’t just restricted to reprimanding mistakes. They can recognise and encourage good behaviours as well.
Quality coaching - augmented by AI - doesn’t just help agents to be better, it improves service, enhances the customer experience and pays dividends for the business.