If you’re like many other businesses out there, one or all of the below Quality Assurance (QA) Contact Centre practices will be very familiar to you –

  • 3 QA’s per agent per month. The same agent takes a minimum 400 calls a month, so less than 1% of calls are sampled
  • Different Quality Management (QM) scorers mark differently – calibration sessions used to occur, but… .well … now we are just too busy
  • QA is not across all customer interaction channels and if it is, it is inconsistent

While technology innovation in the Contact Centre has made great headway over the past decade, technology supporting QA operations has not always  kept up.

On the one hand we have Speech and Text analytics that can pinpoint specific points in an interaction where an agent missed a critical compliance step, failed to correctly close an interaction or did not use the right soft skills (such as empathy, open question, probe for customer needs).

On the other hand, it feels most Contact Centres, even when they have a Speech and Text analytics technology capability, are not harnessing this powerful rich insight capability to full advantage for QA purposes.

Staying with the theme of Speech and Text Analytics, this capability allows you to shift from a traditional approach of a very small subset of calls/digital interactions being checked for often “tick a box” type checks (e.g. did the agent use the right welcome message, did they offer a survey at the end of the call, etc..) to one where all interactions are analysed automatically with QM teams focussing on the issues identified by the system.

This approach then allows the QM team to spend 80% of their time on the value creation of how to drive real improvements in agent performance. e.g. speech analytics flags calls to ascertain where specific compliance steps were missed, and the QM team can focus on how best to close the gap for specific agents.

Sharing a real business case, one of our recent engagements was for a Financial  Services company, and in particular within their phone based sales team.

Due to their obligations under ASIC as an Australian Financial Services licensee especially with respect to giving information versus advice, as well as the extra scrutiny driven by Royal Commission into Misconduct in the Banking Suppuration and Financials Services Industry, every call had to be vetted for compliance for areas such as recital of product disclosures, exclusions being declared, pricing and customer consent to buy.  A sales call was on average 30 minutes.

The organisation had a system in place whereby one Quality Management person was required per 4 sales people to ensure this compliance was being met with every single call being QA’d.  This was not sustainable and more importantly was not scalable when the company had significant growth targets to increase the sales team and sales target by an order of magnitude. You can imagine the overhead.

To address this customers problem, Ensighted configured, tuned and deployed a speech analytics system that did 100% Quality Management of all sales calls which focused on ensuring mandatory call script items were achieved.  By automating much of this process, we were able to bring positive change to the role of the QA process.

In the past a QA member spent around 80% of their time listening to calls end to end to ensure mandatory items were completed so they could check off compliancy items.  Now, they can focus on checking only calls flagged by the speech and text analytics system for non-compliance, and by being directed to the specific point in the conversation where there may be a compliance issue, significant efficiency  gains area achieved  compared with listening to an entire 30 minute call. This benefits the Business with the QM team now spending less time on standard compliance checks and more time on identifying coaching opportunities for improved customer service and sales conversion.

Critically this enabled the business to easily scale up to meet sales demand without needing an unsustainable increase in the quality management team.

Key takeaways:

  • You can automate many of the standard Quality Management functions which can translate to a benefit of up to 80% of a person’s time
  • Use Analytics to determine 100% compliance of standard and patterns
  • The Quality Management team can move from being largely focussed on quality control to deeply embedded in supporting development of people’s skills
  • The analytics technology is the easier part – you need the right blend of business, process and analytical capabilities to deliver results