Measures such as Net Promoter Score (NPS) are becoming ever more important to companies, as the success (or not) of customer service operations increasingly has an impact on the bottom line. It’s all very well measuring customer sentiment at the end of the process, but this won’t give you any insight into why you might have achieved a negative or positive score, which makes it difficult to correct or replicate in the future.
The field of customer service is constantly changing – systems and processes are updated, outages or billing errors can have almost instant impacts on in-bound contacts, as well as company reputation. It’s important to keep an eye on the data so you can spot potential issues before they start to impact on business performance. And in order to do this, you need to be able to benchmark your data. Is your business keeping a constant eye on important measures like call volumes, first time issue resolutions, and frequency of customer contacts? Tracking these high-level measures over time allows you to identify spikes that might point to a process or business issue. But don’t stop there – these alone won’t help you to find the problem, without the ability to interrogate a deeper layer within your measurement data.
Whilst working with a communications client, we spotted an increase in the number of engineer visits that resulted in ‘No Fault Found’ outcomes after a customer logged a fault call. Sending an engineer out to visit a customer has an obvious cost impact on the business, and failed visits are effectively wasted cost.
By going back and examining the data from the original customer call we discovered the fault type that was leading to the highest proportion of ‘No Fault Found’ visits. After examining these types of calls we were able to put in place additional questioning and technical support around this particular error.
These calls were also automatically escalated to a 2nd line support technician by default, meaning that we were able to resolve more of them without the need for an engineer visit, which led to an immediate and significant drop in NFF call outs by 50%, with a 56% cost saving for the customer, and an overarching NPS score increase of 6% over 3 months.
It’s clear that by being able to dig down into the granularity of data, support partners can help solve issues that directly impact on business success. This data, once evaluated, can help develop coaching conversations with agents, and manage issues that could have cost or service implications further down the line.
Businesses keen to drive an increase in customer satisfaction over time need to work with a partner that takes a proactive approach to fault identification and process improvement. A trusted customer or technical support provider should be constantly reviewing management information to understand where support processes can be improved to drive both customer satisfaction improvements and cost savings for the business. It’s important too that they can drill down beyond top level reporting to truly understand which behaviours and processes are impacting customer outcomes.
If you’d like to learn more about how Arise works with clients to improve customer satisfaction, reputation and efficiency, visit our website here or get in touch directly.