A contact centre must collect data in order to categorise the contact, as well as analyse it, rather than simply collect data on what happens: what the customer called about, what the fix was, what we did, what they did. Few companies collect the data for why customers had to call, which is powerful data to indicate improvement within the contact centre and company as a whole.
It is important to identify why customers had to contact in the customers’ words. A utility might use “I don’t understand my bill” or “My bill is wrong” or “My billing estimate is wrong” which is so much more insightful than classifying these as “billing” or “refunds”.
This type of analysis follows the customer journey as it starts with the customer, goes to the contact point and then into the organisation. Journey maps are very different from process maps and allow for both physical and emotional mapping of why things happen and therefore how it can be avoided. Front-line staff can start asking questions. If they ask why something happened, then analysis projects become unnecessary as there exists a real-time root cause analysis, free feedback and engaged front-line staff. Voice of the Contact Centre.
You can’t analyse data that isn’t there, so speech analytics will not tell you the answers unless the customer spoke them. To do that the agents have to ask the relevant questions. And finally, and importantly, senior and middle management will finally talk the same language as the agent and the customer. It’s harder to ignore the frustration of the customers’ requests for help, and a cultural shift occurs manifesting in business improvement and ultimately ROI.