Inputting wrap-up codes is a standard piece of ACW work a contact centre agents typically completes. It allows a call to be classified so insight can be extracted on popular topics, locations, type of caller and so on. Some contact centres also use the accuracy of codes as a KPI for individual agents.
However, too many lengthy dropdown lists are proving too laborious for many contact centre operatives – we call this ‘Aberdeen Syndrome’.
Aberdeen Syndrome occurs when the agents classifying calls select wrap-up codes from picklists in a lazy fashion, i.e. if the list is alphabetical, then they will more likely select “Aberdeen” than “Wells”, hence Aberdeen Syndrome.
Providing ‘Other’ as a code is also common practice. The result however is this option being selected unnecessarily too many times as it’s much quicker to locate this category than root through all of the other options. It’s a quick ‘go to’ for agents when they want to move through the wrap up process quickly or don’t have sufficient time during a call to make the selections accurately.
On other questions there is sometimes only a single wrap-up code.
In all of these cases vital information is being missed that would benefit the customer, agent and business.
So how can you get from Aberdeen to Wells avoiding ‘other’?
The answer is in auto-tagging or auto-classification, made possible by the latest in AI and machine learning. Specific information can be requested and automatically identified from a call, email or other piece of customer feedback such as online chat. The wrap up codes are populated automatically, significantly reducing call wrap up time.
Sentiment and customer intent can also be automatically identified providing additional key customer feedback, all in near real time.
There are no issues with multiple sentiments or answers either as responses are classified by the whole concept, and not just keywords.
It’s all part of a new breed of automated analytics for contact centres that is proving to improve CSAT by up to 20% and FCR by 50% plus reduce AHT by 35% and customer churn by 18%
Warwick Analytics recently worked with a global retailer that was experiencing Aberdeen Syndrome, too many ‘others’ being selected and a lack of code choice for some key areas.
Information was being incorrectly coded when there were too many drop down options. When looking into this further the majority of selections were in the top quartile of the drop down and very inaccurate.
When only a single code was offered, multiple issues were being hidden on the same interaction.
Most worryingly however, “Other” was hiding some serious issues as well as some really useful insight.
With the auto-tagging in place the retailer is no longer reliant on the operator selecting the right codes and is able pick up all feedback with explicit accuracy.
So if your contact centre has a disproportionate number of customers calling from Aberdeen or ‘Other’ is becoming the default option for too many agents, then it might be time to start looking at some technology to make wrap up codes and wrap up time not just more accurate but less of a burden for all.
Dan Somers is CEO of Warwick Analytics
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