10 steps to create a voice of the customer program
One of the best initiatives a customer experience team can undertake is a voice of the customer program. Here are some guidelines for building one from scratch.
At the heart of any CX strategy is customer feedback. Creating and implementing a voice of the customer program are often the most effective ways to do so.
VoC can be thought of as a listening program applied to customer relationships, a systematic approach to collecting and analyzing customer feedback and operationalizing the customer insights. The idea is to go beyond the usual touchpoints -- survey results, customer service ratings, etc. -- and assemble an omnichannel profile of the customer, integrating all the data from every possible source.
Why a VoC program is important
Customer data is always valuable, but the structured, all-inclusive approach of a VoC program boosts that value considerably. It fills in gaps in the customer journey and lifecycle and increases customer success, which, in turn, improves customer satisfaction, customer retention and, ultimately, customer lifetime value. VoC's expanded channels go beyond direct feedback, mining social media and other sources where the customer is communicating with other customers, rather than the organization itself.
Structured feedback is important, but unstructured, unsolicited feedback can be of even greater value; the latter is often more honest and reliable. A VoC program helps develop the capacity to gather and process that feedback, which greatly enhances the view of the customer.
The benefits of a successful VoC program are substantial: increased Brand loyalty from the customer, increased advocacy and referral, and partnership with the customer not only in working through issues, but also developing future products and services.
Steps to build a successful voice of the customer program
There are several basic steps to building a VoC program, and all of them vary greatly, depending on the target market. These steps are basic, but how CX teams implement them may end up being highly customized.
Customer data is always valuable, but the structured, all-inclusive approach of a VoC program boosts that value considerably.
Determine the target audience. CX teams should figure out who they are trying to understand and communicate with. No product or service can reach everyone, and no company can serve the entire world.
Identify core values. Connection is about needs, and the meeting of needs includes shared values. CX teams should determine what those are and how to identify them in customers. For example, if the typical customer in the target audience treasures transparency, the brand should make that a priority.
Configure the CX team around VoC. VoC isn't just an agenda; it's a way of thinking. When a company commits to it, it is setting a new direction for CX, and the CX team must be behind it all the way. Businesses should select and train CX team participants with a focus on enthusiasm for that mission.
Align CRM with the relationship between the customer and the VoC program. It's critical to have machine learning and analytics engines tie back to the assembly of a customer profile. It's also important that that profile works well in the context of CRM.
Carefully select the right VoC tools. VoC software parses customer data and supports multichannel feedback. When selecting VoC software, organizations should assess how well it integrates with existing CRM and the quality of the analytics it offers. Vendors include Verint, Qualtrics, Mindshare, Questback and others.
Prioritize customer satisfaction as a key metric. Machine learning systems grow and improve based on outcomes and selective feedback. The feedback metric that matters is simple: Is the customer satisfied? Brands should make this the centerpiece of their analytics and never lose sight of it.
Grab customer signals wherever possible, no matter how obscure. There's a rule in big data: More is better. Companies should brainstorm every possible source of customer data: email, text messages, survey feedback, chatbot dialogs, product ratings, social media, interactive voice response -- anything they can think of. It doesn't matter if it's structured or not; it's all useful. However, it's also helpful to rank those sources by value. Some channels will give companies gold; some won't. CX teams should prioritize those that deliver the best feedback.
Build predictive models, and let them drive response. The unified customer profile feeds a predictive machine learning model; the output must be tied to specific behavioral outcomes, such as likely to buy or likely to recommend. Brands should make these connections and continually refine them.
Automate. The VoC system's outputs will, most of the time, be useful insights that feed into process refinement and performance optimization for customer engagement. CX teams should make these insights action-oriented and automate their delivery -- for example, spread them throughout the organization to support center agents, web teams and everyone who has a customer contact role. VoC improves CX from one end to the other, and that includes the human contacts.
Align VoC response to customer expectations. Today's customer expects responsiveness, transparency, empathy and a proactive attitude. Companies should build the system to deliver on these expectations.
Brands can ask customers questions through interviews, focus groups and surveys.
VoC methodologies
The list of methods that companies can employ in a voice of the customer program is long. Brands should adopt as many channels as possible for the most complete customer profile, but some methods will be of greater use than others, depending on the market.
CX teams should perpetually gather metrics on those methodologies that make it into the program to continually measure their performance and improve them over time.
Website and app surveys. Online surveys are ubiquitous at this point, and customers are used to experiencing them constantly, usually in the form of a quick pop-up at the end of some event, like a product purchase. Surveys are easy to implement, and the data is useful.
Online behavior. Studying the patterns of a customer's behavior on the company website can really pay off by generating heat maps that reveal needs and interests that might not be detectable on other channels.
Interviews. Speaking to a customer to gather information is both expensive and time-consuming. But it's one of the most trustworthy forms of data collection, and it can often build customer trust.
Social media. What does the customer say to others about a brand? Social media is the best place to find out. This, too, is an especially honest channel.
Live chat. Live chat is great for real-time feedback, and its presence is increasingly comforting to customers. It not only offers great VoC data capture, but it's a natural spot to drop in a survey.
Recorded phone calls. It may not be an intuitive channel and it certainly isn't easy to work with, but phone call recordings offer a great deal of insight -- not just into what the customer does and doesn't like, but how they feel. Chatbots can't do nearly as much to reveal customer emotion.
Focus groups. Interviews are a great source of customer insights, and a focus group is an interview on steroids, getting to the core of customer needs and issues in a way an interviewer often can't. When customers are gathered together offering their input, they feed off one another, stimulating an endless parade of thoughts and experiences.
Online reviews of products and services. Customers tend to let it all hang out when they write a review online. Why? Because they wouldn't bother taking the time to write one if they didn't feel strongly -- for better or worse.
Email and text data. Email is an old standard for customer feedback but as useful as always. Text -- its younger cousin -- tends to pull in less data, but on the other hand, it's now the most preferred point of contact from the customer side.
Net Promoter Score (NPS). NPS is still the simplest and best measure of the customer's brand loyalty. Companies must simply ask, "On a scale of 1 to 10, how likely is it that you would recommend our products/services/company to a friend or colleague?"
