Modern customer customer service teams support more customers, more products and more devices, across more service channels than ever before. All of this means more data, and ultimately more difficulty when it comes to keeping track of customer behavior, preference and intent.
To better understand their customers and all of this new data, customer service and support leaders are prioritizing data and analytics in a big way. A recent Gartner survey showed that 84% of service and support leaders view customer data and analytics as either extremely, or very important, to achieving their organizations goals in 2023.
Let’s be honest though, service and support teams have not traditionally been experts when it comes to managing complex data. In fact, in many cases customer service has often been resigned to an afterthought when it comes to enterprise customer data strategy.
So how can customer service and support teams rise to the challenge and keep track of their customers across all these new touch points? And what does a modern Voice of Customer (VoC) program look like for a data focused service and support organization?
Embracing New Listening Methods
For many years it was the simple customer survey that persisted as the primary mechanism through which service and support teams would keep track of the customer experience. However the limitations of surveys as a listening method have been known for a long time. Low response rates, inconsistent survey methods, and a notoriously slow time from data to action, are only some of the problems customer surveys present. When you take into consideration the evolving and complex ways that customers access service and support today, the traditional survey appears to be a wholly ineffective method for understanding your customers – particularly when deployed in isolation.
Today the most progressive customer service teams have started to move beyond surveys towards new advanced VoC listening methods that provide faster insight into customer preference and behavior across a multitude of different channels and experiences. Rather than simply waiting for customer feedback via surveys, new VoC methods such as speech, digital and social media analytics offer organizations a more immediate means of understanding their customers’ experience in a multi-channel world.
Many of the best teams are also looking for ways to analyze and join multiple forms of VoC data in combination to further deepen their understanding of their customer. For example, how does a customer’s experience on a self-service portal impact their sentiment when they speak to an agent on the phone, and how does this interaction on the phone impact what they say about the brand later on social media? By combining VoC insights across multiple listening methods, organizations are able to develop advanced, and in many cases predictive insights, that can help to shape customer journeys and improve the customer experience overall.
Becoming a ‘Data First’ Customer Service Organization
If all of this sounds difficult, then you are not alone. For service and support teams who have traditionally lacked experience with data and analytics, making the most of their available customer data can represent a significant challenge. Organizational silos, legacy capabilities and technology, and an overall lack of experience for dealing with large and complex VoC data sets, are only some of the challenges that service teams face.
To overcome these hurdles, service and support leaders require an end-to-end process for handling customer data, where a range VoC data sets (not always exclusively controlled by the customer service team) can be centralized, analyzed and transformed to improve service and support insight into the customer experience. Leaders can start to address this process by auditing their current capabilities, and making a plan for investment.
In terms of technology, leaders should consider what VoC methods are currently deployed and what analytics tools they have at their disposal. They should start considering investment into technologies that will enable them to capture a broader spectrum of insights. Depending on their delivery strategy they may consider specialist vendors in the speech or digital analytics space, or could instead consider vendors who offer more general coverage across a broad spectrum of VoC analytics.
In terms of people, leaders should consider the available analytics talent within the service and support team. As teams continue to modify their approach to data and analytics, it is likely new analytics roles will be needed that are aligned to service and support objectives. Organizations may consider starting by hiring data analysts roles who could support a broad spectrum of service analytics requirements.
Finally, leaders should consider their existing process for sharing and collaborating on VoC throughout the enterprise. Leaders should partner with other parts of the enterprise to understand what data is being captured elsewhere and to start developing a formal process for managing and sharing insights. This is most commonly achieved via some form of VoC or data governance group, with ongoing representation from different areas of the business responsible for aspects of the customer experience.
While it may be hard to imagine a future where the traditional customer survey disappears completely, service leaders must address the reality of modern customer interactions. By emphasizing data and analytics as a core pillar of their strategy, service leaders can start to evolve their organizations out of the past, and into a future where new and advanced VoC methods.
