I’ve noticed something interesting about voice of the customer (VoC) programs lately. The line between VoC, customer experience (CX) and customer insights or analytics seems to be blurring. Take the Gartner definitions for these terms:
Voice of the customer solutions combine multiple, traditionally siloed technologies associated with the capture, storage and analysis of direct, indirect and inferred customer feedback. Technologies such as social media monitoring, enterprise feedback management, speech analytics, text mining and web analytics are integrated to provide a holistic view of the customer’s voice. The resultant customer insights are acted on by disseminating relevant information to the right person at the right time on the right channel.
Customer experience management is the practice of designing and reacting to customer interactions to meet or exceed customer expectations and, thus, increase customer satisfaction, loyalty and advocacy. It is a strategy that requires process change and many technologies to accomplish.
Customer analytics is the use of data to understand the composition, needs and satisfaction of the customer. Also, it’s the enabling technology used to segment buyers into groupings based on behavior, to determine general trends, or to develop targeted marketing and sales activities.
When you look at them comparatively, these definitions seem to be almost circular in nature. It can be particularly hard for executives new to CX or VoC to discern the nuanced differences that exist between the three.
The Common Denominator? All Roads Lead to the Customer
VoC and CX seem to overlap because disseminating relevant information to the right person at the right time on the right channel (VoC) is a significant part of how companies design or react to customer interactions to increase customer satisfaction, loyalty and advocacy (CX).
VoC and customer analytics are even more difficult to clearly separate because the VoC definition of integrating data into a holistic view of the customer voice resulting in customer insights is nearly the same as using data to understand the composition, needs and satisfaction of the customer (customer analytics definition).
The hard to see nuance here, and what makes VoC and CX different but associated disciplines, lays in what constitutes customer voice and what is done with the insights generated. CX professionals who look closely at the technologies named to generate customer voice — social media monitoring, enterprise feedback management, speech analytics, text mining and web analytics — will realize that these do not include applications that provide insights into purchase and product usage patterns, demographic and profile information, etc. Thus, customer voice is not the all-encompassing 360 view of the customer (although there are VoC proponents who claim it is), but rather a more narrowly focused component of it — the component that identifies how the customer feels about specific interactions, particularly when problems arise.
Also, the application of analytics and insights for VoC programs refers not to the very broad activity set encompassed by CX (marketing, promotions and offers, sales, service, product design, pricing and credit decisions, etc.) but to a specific subset of these: touchpoints where customers can experience issues and the activities needed to identify, respond and prevent.
Less experienced individuals might easily miss this nuance.
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Blurred Lines Permeate the Industry
When talking to industry peers or keeping up with blogs and articles, much of what I find highlights these blurred lines and ambiguous definitions.
I recently read a very informative article (well worth the reading time) on making VoC programs actionable, written by another CMSWire author Duff Anderson. While emphasizing the importance of C-suite involvement in VoC programs, Anderson references a quote from Tiffani Bova, Salesforce’s global customer growth and innovation evangelist. The quote and associated interview are not about VoC specifically, but instead, transition the conversation to CX. Bova says, “executing a customer experience (CX) program has to start at the top. The company at the executive level has to make CX a part of the company’s DNA.”
The advice is spot-on, for both CX and VoC, but it is easy to see why a novice might mistakenly believe the two are the same.
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One of my favorite CX research and consulting companies, Temkin Group, provides another great example, this time highlighting the VoC and analytics overlaps. In its last State of VoC Programs research report, it repurposed a set of trends I first encountered in 2014. The 2014 version was labeled “5 trends for CX insights” and focused on analytics, while the latest version transitioned to “6 trends reshaping future VoC programs.” While the trends remain mostly the same, the positioning and advice differ to reflect VoC programs today. As with the article above, this piece is well worth the read and provides a solid basis for understanding and actioning VoC. The naming and positioning changes also serve to highlight the fluidity with which the industry in general moves back and forth between these terms.
Related Article: Customer Experience Measurement: Back to Basics
Don’t Lose Sight of the Value of VoC — and Where It Fits
The upshot for me (and I realize people may take issue with this point-of-view) is we need to make clear delineations between CX, VoC and customer analytics. Combining them into a single all-encompassing bucket, or failing to distinguish between the disciplines, particularly to C-suite executives, comes with significant risk, the biggest of which is that the non-overlapping components may be left out of the equation.
Customer analytics and CX extend well beyond VoC to encompass every customer-facing and customer-impacting decision made across the organization. VoC is essentially a listen, understand and respond program, designed specifically to capture customer feedback and attitudes about performance, highlight and fix trouble spots, respond to individual customer issues and reinforce strengths.
Making sure that all three disciplines work together requires a solid understanding of listen, understand and respond aspects of VoC.
Listen: The old-fashioned market research techniques commonly associated with early VoC programs can be modernized to extend past focus groups and web surveys and include much more detailed tracking mechanisms (e.g., mobile applications utilizing location and search data, open-ended feedback questions, and participation incentives). Customer-controlled communications — complaints, customer service calls, emails and web chats, as well as indirect communications such as social media mentions and blog posts, are equally important and should not be overlooked.
Understand: Analytics can add significant value by helping to refine conclusions and highlight what action should be taken. The analytics programs should be able to identify trends and themes, categorize responses, determine root causes for behaviors, and highlight sentiment in speech and text communications.
Respond: The feedback or response mechanism established to handle the VOC insights and analysis recommendations is critical. Companies must define and implement specific response monitoring processes and action teams. Social listening activities must be augmented with individuals accountable for and empowered to respond to customers and take action as problems are detected. Declining KPIs must initiate action teams entrusted with investigating root causes and recommending solutions.
That is not to say that customer analytics don’t play a big part in VoC — they do. Nor are VoC and CX are mutually exclusive — they aren't. Rather, customer analytics enhance VoC programs, and VoC efforts play a vital role in comprehensive CX initiatives. Clearly delineating between the three disciplines will ensure that each program performs to its fullest.
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