As businesses accelerate their digital transformation post-COVID, conversational analytics is playing a key role Not only do insights help companies better manage conversations across multiple channels but it also gives them the ability to dive into the meaning behind those all-important interactions with customers. But conversational analytics goes far further than that, as Sebastian Glock, Head of Product Marketing at Cognigy tells us.
‘Conversational analytics describe a set of tools designed to understand and make sense of data that is happening in artificial or human-to-human communications,’ Glock begins, with a simple, easy to digest definition.
‘It helps craft better bots and allows business users to fine tune those experiences for end users,’ he adds.
Analytics has become somewhat of a buzzword as the world begins to emerge out of the coronavirus pandemic. This is because throughout the past 18 months, for businesses to not only stay afloat but thrive in the COVID-19 climate, organisations have had to level up their artificial intelligence initiatives to allow for insights into that rich customer data. But why the surge in conversational analytics now and not before the pandemic hit? As Glock says, this is all to do with companies pushing for faster digital transition.
‘We see that many of the conversational analytics initiatives are now maturing on a level where it is increasingly important to measure the results and see the outcome, whether that’s measuring ROIs or taking the ability of bots up a gear. Each business has a different agenda for using conversational analytics, but the speed of the transition is key for all.’
The benefits of conversational analytics are tenfold in providing a far deeper level of customer engagement, Glock explains, highlighting areas of risk in interactions that can be prevented using the tool.
'Businesses design a process and essentially let it out into the wild in the hope it performs well. This could be a product or a service. But it’s very hard to understand what is actually happening in the background during those conversations with customers. An example could be those friction points in the conversation where customers may really struggle. Or the part of the customer journey where there’s a risk that agents disappoint customers, perhaps where they want to talk to a human because they get the feeling that the bot can't help, but the bot doesn't understand their request.
‘The only way to identify areas of concern in interactions with customers, when they’re not feeling empowered by the bot they’re speaking to is through conversational analytics. It allows companies to make sense of that data and those protocols to really understand what’s going on. And making data actionable can only be achieved through the power of automation.’
Insights provided from conversational analytics, whether it be natural language processing, sentiment analysis or path analysis, to name a few, help business leaders future-proof their companies with top-notch performance across the enterprise and prove results from their investment. With bots sifting through customer data from interactions it provides organisations with the tools to make better informed business decisions by tying the interactions back to the orchestrator to allow for tweaks – major or minor.
Glock explains: ‘Conversational analytics allows for direct correlation between what end users are really experiencing when, for example, they’re talking to a bot. That information is then passed back to those who built that bot so they can make changes based on that data.’
Cognigy Insights has really raised the bar when it comes to the ability of conversational analytics. It enables enterprises to access and analyse conversational data easily and leverage them for optimising processes. The suite allows users to track and measure each step of conversation and pinpoint exact pain points by using its unique Step Explorer feature, which helps users to better understand their CX offering beyond the limited capabilities of intent-driven analytics.
