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        Top Trends in VoC Analytics

        A formal Voice of the Customer (VoC) program is a necessity for any organization that wants to grow its customer base and differentiate from its competitors. Unfortunately, many organizations have not updated their notion of “formal” in quite a few years.

        VoC has a contact center component and an enterprise component. They are related, hopefully connected, but not the same. Contact centers are where the bulk of VoC data is collected, but not where it gets analyzed. The enterprise makes use of some of the contact center’s data contribution but not generally enough of it (or the relevant parts).

        The trouble is that the traditional method of VoC in contact centers is a simple survey, usually several questions offered up at the end of a voice or digital interaction, often with a scaled response mimicking the NPS scale. This feedback is helpful but extremely limited in three ways. It captures a response to the latest interaction only, without discerning long-standing issues that might be lingering, and is divorced from any context outside the interaction. Second, it incorporates a self-selection bias on the part of the customer, who is likely to answer a survey only when things go exceptionally well or badly. And third, it is most often used inside contact centers to assess agent performance rather than to identify overall defects in products or processes.

        With that kind of baggage, it is not surprising that a deeper kind of VoC approach is needed. Modern best practices in VoC are moving beyond surveys, and beyond the contact center, to incorporate free-form text, voice recordings, marketing data and contextual customer information.

        The most important emerging trend in VoC is the use of artificial intelligence (AI) to overcome some of the limitations just described. As AI becomes a more valuable tool across the enterprise, many are using it to identify trends in customer sentiment, intention and buying behavior. This takes the data outside the contact center, usually to marketers, who have more experience using AI. AI and other forms of rich analytics are now able to ingest and parse enormous stores of unstructured voice recordings, a largely untapped source of customer intelligence. Success with this has been hampered by the enormous volume of recordings; without direct feedback, it is hard to know what to look for, to understand how to find a signal in the enormous pile of noise. That makes AI a good candidate for cross-departmental deployments that foster the integration of contact centers into wider customer experience (CX) and VoC programs.

        The movement toward AI mirrors a second trend, the transition from using mainly direct customer feedback to the passive collection of data. The voice recordings are part of this, as they can be run through a natural language processing (NLP) system and converted to text for analysis. Other passive elements include historical transaction data and customer data with life events and demographics. By analyzing these types of data, you can use VoC for brand management, spotting subtle trends that may have little to do with any one person’s interaction but a lot to do with how groups of customers view an organization more broadly. Ventana Research asserts that by 2025, one-half of organizations will rely more on analysis of passively collected data than direct survey feedback for insight into VoC.

        VR_2022_Voice_of_the_Customer_Assertion_3_Square-1We are also seeing a deeper linkage between VoC programs and loyalty management more generally, especially among marketers and customer success teams. These teams occupy a space somewhere between brand managers (who take a very broad view) and contact centers (with a very narrow one). They focus on the needs and progress of a specific set of customers, usually of high value. But they must have insight that is more qualitative than quantitative, more related to uncovering future potential than in correcting problems that have already occurred. These users are likely to find their VoC tools as part of existing systems, like CDPs, CRMs and personalization platforms, and augment them with analysis tools that might or might not be formally created for VoC.

        Another trend is the adoption of “microfeedback” — instant reactions to some event, like an interaction or a communication. Airport bathrooms, for example, are often now equipped with three buttons (sometimes colored red, yellow and green) for people to rate cleanliness on their way out the door. It takes two seconds, is completely anonymous and provides an instant snapshot of success or failure. It does nothing to seek out deeper issues, but it can provide a quick alert to send someone to replace the paper towels. When this kind of system is used in a mobile app or on a website, it does become more trackable and provides a guidepost for deeper investigation. By forcing someone to make a snap choice between very simple up or down ratings, you eliminate any confusion about wording or bias related to an agent or a conversation. In other words, useful in some contexts but limited overall.

        Finally, VoC has a role to play in workforce relations. The pandemic has upended how contact center agents are hired, located, trained and managed. Since it has become more difficult to find and retain qualified staff, many organizations are beefing up their workforce engagement practices. Some are looking to versions of VoC tools to apply them to the voice of the agent as well. The agent has always been one side of the conversation captured on voice recordings and is often the subject of the feedback delivered on customer surveys. So, the idea of capturing and analyzing that part of the interaction is not new. What is new is using more targeted tools to provide agents with a forum for expression in a nonthreatening way. These practices are merging with existing performance management and training/coaching methods that capture assessments of activity. Now the idea that you can assess agent satisfaction and engagement in much the same way is taking hold.

        Overall, what we are seeing is a recognition that traditional survey-based feedback is good at helping contact centers see the short-term issues, mostly within the agent pool, but that it is insufficient for a wider CX strategy seeking to build loyalty and extend customer value. For that, other departments and new technologies must move to the forefront.

        For more insight into how voice of the customer technology is being developed and used, visit the VoC Focus Area at Ventana Research’s Customer Experience expertise section.


        Keith Dawson



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