Wayne Butterfield, Global Head of Intelligent Automation Solutions at ISG Automation, introduces how task and conversation mining can enhance contact centre performance
The contact centre as we know it has been around since the early 1980s. Banks of people answering questions initially by phone, then email, and now by any number of digital channels, and even via video for those who still wish to enjoy a face-to-face experience from home.
Sure, these channels may have changed, but many of the same age-old challenges persist despite years of process improvement and technology upgrades.
As such, it is time for many to consider; do we really understand why customers make contact? What processes are failing customers? And how can we truly improve the experiences we deliver?
Microscopically reviewing each and every customer conversation is the first step to overcoming these quandaries.
Imagine not only knowing why a customer makes contact but also the steps taken by the agent to respond, and the keystrokes taken to complete any system actions. Sounds transformational and revolutionary.
Yet, there is a catch. For a contact centre of 100 agents, it would take over 400,000 hours to listen to six months of calls while also reviewing their keystrokes.
If a contact centre employs a team of ten people conducting this analysis, it will take them over 15 years to analyse all these interactions. In today’s world, things can change in as little as 15 days, never mind 15 years!
Yet, for too long, transformation programmes have been held back by poor, inaccurate, or just plain missing data points, which could have informed better CX decision-making.
After all, many historical transformations fizzle into a half-baked version of the original intent, and leaders are left wondering why.
With more data, a clearer picture emerges. Without this data and technology assisting our understanding (and supporting transformation teams), we can only play around the edges.
As such, the support of intelligent automation (IA) and AI technologies has become increasingly integral.
The addition of agent assistants to the contact centre has provided a new mechanism to automate the transactional actions that agents complete to resolve customer queries. Such technology evolutions have mechanised regular actions – like completing customer verification or after call work – often saving minutes across every call. But after claiming this low-hanging fruit, where next?
This is where advanced AI steps in. Listening to every contact centre interaction, AI captures each customer and agent intent (and action), including keystrokes. Amplify this across millions of interactions, and suddenly, companies can collect rafts of first-party data.
However, they must mine the right insights amongst all the noise. Compare this to the regular alternative, which is to dig, dig, and dig for data that is often inaccurate or fails to show the complete picture.
Two technologies lay the foundations for this step function shift. On their own, both are incredibly useful, growing in popularity in and outside the contact centre. Together, they are new, futuristic, and potentially game-changing.
First off, Task Mining, which provides insight into agent actions. In most cases, down to a per click, per agent level, so when multiplied across all agents and contacts, over several weeks or months, contact centres start to see repetitive patterns. These are prime candidates for desktop-based task automation or improved workflows.
The second technology is Conversation Mining, which involves listening to the conversations and picking out customer intent and agent responses. In doing so, contact centres can analyse sentiment, effort, and gaps in talk time. These insights help spot and address drivers of high handling times, saving significant time across numerous contact reasons.
Add these technologies together, and a speedy contact centre transformation is possible in months, not years. Most importantly, such transformation is based on unbiased, quantifiable data, which is why this approach trumps the historical practice of assessing agent compiled contact reasons and a small proportion of customer calls to drive transformation.
Eager to learn more cutting-edge insights from Wayne Butterfield? Then, check out our recent roundtable: Driving Contact Center Productivity with Automation