One of the biggest reason for potential customer angst for a contact center is if the caller has to navigate through a complex IVR and still doesnt get any resolution for the reason he/she decided to call and ultimately they have to speak to an agent.
Today, the speech recognition and natural language processing capabilities of have matured by leaps and bounds. We have this capability on our phones (siri and similar).
Still, we are not using this to solve the biggest reason for customer angst.
Can we not replace the IVR with a NLP algorithm that understands the reason from the caller (who just speaks out why he has called) and analyses that and searches a database to check if there is a pre-canned response for this type of query and responds accordingly.
If for any reason it is not able to directly respond, it picks an agent who has shown good FCR (first call resolution) rates for similar issues and directs the call to that specific agent.
This might have been impossible to think of a few years as the technology was not there yet. But today, we have in-memory systems which will be able to handle the analysis of voice and subsequent database search in realtime without any challenge (once the algorithm is in place).
This can actually do away a big cause for customer angst.
If the organization then wants, they can scale this same system to do realtime analysis of the calls to find if there are any patterns in the call and if there is a trigger to the same. This provides them the opportunity to not only identify potential issues really early (almost in realtime) and solve them before they can spiral out-of-control. This will then result in a reduction of overall cost of operations and increase in customer satisfaction.
