Analytics will always have a key role to play in effective workplace optimisation in the call centre, and the most widely used type of interaction analytics functionality is historical post-call speech analytics.
When speech analytics solutions first began to be implemented, the focus was generally on the analysis of large numbers of recorded calls, with this often occurring a significant period of time after the actual event.
Back then, speech analytics solutions tended to be purchased with a view to using them to help ensure compliance, as part of a broader quality assurance (QA) system.
That benefit still holds true today, with call centres able to go a long way to optimising their QA processes when they have access to high-quality information that enables them to assess the performance of agents fairly and accurately.
Post-call speech analytics remains a highly relevant source of insight
While recent times have seen real-time analytics much talked about, this should not overshadow the crucial role that post-call speech analytics continues to play for contact centres. After all, it provides invaluable business intelligence, helps ensure compliance, and is key to the optimisation of agent performance.
It helps, of course, that the typical call centre tends to already have call recording in place, which allows for easy access to the necessary raw material.
If anything, businesses are frequently overwhelmed by the sheer volume of recorded voice data that they are able to call upon, which underlines the relevance and usefulness of post-call speech analytics for analysing 100% of recorded calls.
Exactly what do contact centres use post-call analytics for?
Recent research has shed considerable light on the wide-ranging reasons for which call centres turn to post-call analytics. It was especially striking that all respondents agreed on the use of analytics for the purposes of compliance as being either very or somewhat useful.
It was also evident from the findings how crucial analytics was for the automation and acceleration of the quality monitoring process, with some 96% of the research participants that used analytics for this purpose agreeing that it was either very or somewhat useful for that purpose.
Significant, too, was the acknowledgement by so many analytics users that it is very useful for the identification of improvements to business processes. It is expected that in the longer term, analytics will see even more extensive use for the optimisation of processes and the gaining of actionable insight that is applicable to the customer journey.
The research findings indicated that there isn’t presently much enthusiasm for using analytics to provide information about competitors. We do consider this to be a highly underused area of analytical usage at the moment, but we expect that situation to change markedly, with major growth anticipated in the coming years.
Similarly, it didn’t seem from the research that significant numbers of respondents believed analytics to be particularly helpful for influencing scheduling or routing strategies. But with the use of more tightly integrated workforce optimisation (WFO) suites, it does appear that some of the research participants are starting to see meaningful advantages from this.
It is important to note that the above does not represent an exhaustive rundown of every possible purpose of interaction analytics. With post-call analytics enabling the storage of an extremely in-depth mass of interactions, there will be various ways to extract even greater insight from all of this information, in light of the given business’s specific requirements.
Would you like to learn more about the part analytics can play in the optimisation of call centre operations, including the performance of agents? If so, please download our free research report “The Inner Circle Guide to Omnichannel Workforce Optimisation”.