Imagine a small-business customer making the simple, everyday transaction of depositing a check at a branch. The customer leaves the branch thinking the deposit was accepted. However, something about the check requires special processing, and the teller was never trained on the specific nuances of this particular transaction. As a result, the funds fail to be deposited, causing the customer liquidity issues and fees.
The customer then calls the bank to complain. The teller or branch involved in this transaction may never be made aware there was a problem because the customer service representative takes the call, focuses on making the customer whole, records the resolution and moves on to the next incoming call.
Repeating situations like the one above can be avoided by using voice of customer (VOC) information gleaned from the customer’s phone call, combining that information with data from other interactions to identify an opportunity, and then working with the appropriate operational teams to adjust processes, procedures and training. Data from future transactions can even be monitored to deploy proactive real-time notifications or guidance to front-line employees when the risk of such events is detected.
Many companies find it challenging to synthesize and operationalize VOC data (e.g., data from phone calls, emails, chat, survey verbatims, etc.), meaning they underutilize a valuable asset. Large volumes of customer feedback, often about low-risk or unpopular business practices (e.g., fees), make it difficult for banks to find useful insights and applications of VOC data.
Historically, use of this type of data has been driven by static systems (e.g., traditional complaints capture, reporting and analysis). These traditional approaches are typically laboriously created based on past experience, require a great deal of manual — and error-prone — data collection, and do not dynamically evolve with customers’ present-day concerns.
When the collection of VOC data is limited to these traditional approaches, finding useful insights can be like searching for the proverbial needle in the haystack without being able to find the haystack. The right approach for using your VOC data is one that helps you find and navigate through the haystack and actually use the needle for something.
Admittedly, when it comes to using VOC data there are real challenges. But they can be overcome by marrying analytical and other capabilities that likely already exist to some degree in your organization.
A robust VOC analytical program that incorporates transactional data and sound governance can ultimately help improve your company’s operations in myriad ways. Some examples include: identifying process breakdowns that may otherwise go undetected; monitoring for areas of policy/regulatory noncompliance; supporting timely coaching activities with front-line employees; proactively detecting inconsistencies in customers’ accounts that require correction (and avoiding related problems); supporting automation for low-value-added activities such as data capture; prioritizing and routing information that needs to be vetted in your operational routines; and even proving real-time activity monitoring for next-best-decision guidance to your employees during customer interactions. All of this leads to a better customer experience and more efficient operations.
In developing a VOC analytical program, advanced analytical techniques need to be complemented with manual analysis of operations and customer journeys — manual involvement may vary depending on your maturity, data environment and complexity. If your organization has less sophisticated analytical capabilities, you can still make a great deal of headway by starting simple (e.g., through manually reviewing samples based on keywords, topic clustering and/or relative metric analysis). As you continue to mature you can develop more sophisticated tools like artificial intelligence and machine learning to help quickly detect new or emerging trends for routing, research or use in operations.
Manual analysis is a fundamental element to understanding your VOC, isolating problems’ true root causes, making your insights actionable and driving them into your operations. This analysis requires personnel familiar with bank operations that know how to ask the right questions (and get answers). A helpful technique to managing this process can be to establish triage processes that are complemented with analytics, allowing quick prioritization of areas requiring additional research and review by more experienced subject matter experts and stakeholders.
Creating a VOC analytical program is only worth the investment if your company leverages it for change. Change can be facilitated through strong reporting accompanied by governance routines that provide transparency to business leaders, helping them understand the opportunities in terms that bring solutions to light. VOC can be challenging to synthesize, but the data can be a treasure trove of information that supports adaptation of operations. As banks continue to become exposed to increasingly sophisticated competitors, the right program can be worth the effort.
