Voice lessons

Editor’s note: Randy Brandt is vice president of customer experience and loyalty research, Maritz Research, St. Louis.

To gain maximum insight and decision support from marketing research, CRM, and other sources of customer and market data, an organization must develop an integrated voice-of-the-customer (VOC) architecture. Properly designed and implemented, an integrated VOC architecture enables an organization to: deploy “listening posts” for all key touch points, elements and episodes of the total customer experience; integrate and analyze the data from these listening posts in order to develop a comprehensive understanding of the total customer experience; and link critical aspects of the total customer experience to: a) financial and other “downstream” business results; and b) internal processes, human resource, and other “upstream” enablers.

Building an integrated VOC architecture means more than just gathering data about customer experiences and relationships. It also requires:

  • organizing these data in a manner which maximizes their comparability and complementarity;
  • defining how customer experiences and relationships are linked to key financial and other business results; and
  • establishing how the management of operations and employees is connected to and has a direct impact on key elements of customer experiences and relationships.

Organizing voice-of-the-customer data

Initially and periodically throughout the research process, many organizations conduct exploratory focus groups to ensure that all critical elements of the total customer experience have been identified. The inventory of customer experience elements produced by this exploratory process typically is used as a starting point for designing or updating survey attribute rating questions. However, there is no reason to stop there. The same inventory may be used to capture and organize other VOC data such as customer verbatims from inbound channels of communication (e.g., comment cards, e-mails, telephone calls, etc.), survey ratings, open-ended feedback from customer contact employees, and observations made by mystery shoppers. After all, if the discovery process has fulfilled its objective, there should be few, if any, VOC data points that cannot be aligned with one of the categories in the master inventory of customer experience elements. (This is most likely to be true in the case of verbatims or open-ended statements referring to relatively specific or granular aspects of the customer experience. Classifying more general or vague statements may be more difficult, but these types of statements usually do not furnish much insight anyway, unless it is possible to drill down into them in order to clarify what the customer means.)

Once all VOC data are organized within these common categories or attributes, such data are rendered comparable, and it is possible to determine if conclusions drawn from one data source are supported by findings drawn from the other sources.

To illustrate, suppose that a hotel chain has assembled the following types of data:

  • unfavorable comments and complaints from in-room comment cards;
  • attribute ratings from guest satisfaction surveys;
  • open-ended statements from front-desk and other guest-contact employees.

When a common set of categories or attributes has been used to organize the data from these three sources, it is possible to integrate these data using a technique called convergence mapping.

The convergence map illustrated in Figure 1 shows how comparable data from comment cards and guest surveys may be integrated. An attempt has been made to position each attribute of the guest experience using the relative frequency of complaints from comment cards as coordinates for the vertical axis, and the percentage of dissatisfied ratings from guest surveys as coordinates for the horizontal axis.

Figure 1 draws attention to the attributes in the upper right-hand quadrant (highlighted orange). Results suggest that these attributes should be targeted for improvement because:

  • a relatively high proportion of all complaints from comment cards pertain to these attributes; and
  • the percentage of dissatisfied ratings from guest surveys is also relatively high for each of these attributes.

In other words, more than one data source leads to the same conclusion regarding which attributes are key sources of customer dissatisfaction.

Similar convergence maps would be constructed in order to integrate feedback from guest contact employees with both comment card and guest survey data. To the extent that comparisons among these three data sources consistently point to the same subset of attributes, managers may be increasingly confident that these attributes should be the targets of improvement and innovation initiatives. If attribute importance information is available, it may be juxtaposed on the convergence map to facilitate further prioritization of issues for improvement. In the end, highest priority would be given to those attributes that are most important or have the greatest impact on overall customer satisfaction and loyalty and appear to be in need of improvement based on problem or dissatisfaction data obtained from multiple VOC sources.

The key benefit of integrating comparable VOC data is increased managerial confidence in the accuracy and validity of marketing insights. That is, rather than having to rely on results from a single data source (none of which is without its limitations or potential biases), decision makers are able to corroborate findings and conclusions using multiple sources – sort of like getting a second or third “opinion” before investing organizational resources to improve customer experiences and relationships.

Integrating the voice of the customer with other business process and performance metrics

There is a general belief among many marketers that individual experiences or “moments of truth” contribute to the cumulative perceptions a customer formulates about a brand or firm. These perceptions, in turn, are thought to determine the customer’s overall brand preference or loyalty. To the extent that a customer is loyal to a brand, he or she is more likely to repurchase or buy different products or services offered by the brand, and to recommend the brand to others. Ultimately, such repurchase and referral behavior directly impacts financial and other “downstream” business results.

Most managers have a mental picture of the road to business results that is consistent with the above description. However it is not often documented or shared organization-wide. To ensure that such organizational knowledge is captured and leveraged, another key step in implementing an integrated VOC architecture is creation of a business blueprint that links the customer experience to other business process and performance metrics. Generally speaking, the blueprinting process should be guided by the following basic questions:

  • What customer purchase and related behaviors generate top-line revenue and other financial or business outcomes?
  • How does the customer experience relate to and impact customer purchase and related behaviors? What are the experiential and attitudinal drivers of such customer behaviors?
  • What are the employee and/or partner enablers or means of addressing the drivers of customer behaviors?
  • What are the operational and business process enablers or means of addressing the drivers of customer behaviors?

In essence, focusing the blueprinting process on the preceding questions yields a customer-centric value chain analysis. The blueprint furnishes a detailed illustration of the hypothesized relationships among key operational, product, employee and customer elements which, if they are managed effectively, lead to desired financial and other business outcomes.

Typically, managers from marketing, finance, operations and human resources each have detailed knowledge about a specific part of the business. For this reason, blueprinting usually is best performed by a cross-functional team of managers and data stewards who can pool and document their individual perspectives in order to produce the most comprehensive and panoramic view of the business enterprise.

A hypothetical blueprint for retail banking is illustrated in Figure 2. For this particular bank, it would provide the basis for identifying the operational, employee, customer and financial variables for which data should be captured. In addition, the blueprint suggests how these variables are related, which furnishes a basis and direction for how the data should be integrated and analyzed.

The benefit of blueprint development extends beyond providing guidance in integrating customer experience with other business process and performance metrics. As importantly, the blueprint facilitates managerial consensus regarding how to align people and processes in order to achieve desired business results by “doing the right things well” in the eyes of customers. This will prove to be particularly valuable when the time comes to take actions to address the customer-driven issues that have been targeted for improvement.

A recommended approach

In most cases, an integrated VOC architecture will be comprised of multiple sources of customer experience data. In addition, these customer experience data will have connections to financial and related downstream business performance metrics, as well as process, operational, human resource and related upstream data.

A recommended approach to implementing an integrated VOC architecture, illustrated in Figure 3, incorporates and basically flows from completion of the activities described earlier.

The initial step in the process requires completion of an exploratory research phase in which review of secondary data is supplemented with qualitative research to identify the product, service, cost, relationship and brand image elements that comprise the total customer experience. The exploratory research phase also provides an opportunity to explore the objectives and envisioned applications of the integrated VOC architecture with key stakeholders (i.e., individuals who will sponsor, own, and/or use the VOC process and results).

The exploratory research process should be conducted in a manner that provides inputs required to complete the next two parallel steps. The elements of the total customer experience identified via secondary and exploratory qualitative research are used to create a master category system. This master category system will provide the framework for capturing and organizing all customer experience data. Discussions with key stakeholders should include a blueprinting exercise that documents systematic relationships among operational, human resource, customer and financial elements of the business enterprise. This blueprint will furnish a basis for assembling and organizing an appropriate mix of VOC and other data that will be the focus of linkage analyses.

Once appropriate data have been captured and organized, the next step is the integration and analysis of these data. Data integration and analysis should center on two related objectives:

  • developing convergent intelligence that supports identification and prioritization of customer-driven issues for managerial action; and
  • linking VOC data to both upstream and downstream elements of the business enterprise blueprint in order to furnish insights that facilitate alignment of people and processes to achieve desired business results.

Designing and implementing an integrated VOC architecture using the preceding approach yields a variety of benefits, enabling an organization to:

  • make maximum use of available customer experience data - multiple data sources work in a complementary, rather than separate fashion;
  • increase managerial confidence in the accuracy of conclusions drawn from these data;
  • demonstrate the business consequences of effective (or ineffective) management of customer experiences and relationships;
  • identify and improve effectiveness in managing the operational and employee enablers of positive customer experiences and relationships.

Increase effectiveness

An organization cannot be truly customer-driven in the absence of an integrated VOC architecture. Gathering and analyzing data on customer experiences and relationships is a necessary, but not sufficient condition to ensure implementation of such an architecture. In addition, an organization must integrate all VOC data using a common set of categories representing all key aspects of the total customer experience and establish the relevance of VOC data to other key business process and performance metrics.

By implementing an integrated VOC architecture, an organization can increase its effectiveness in defining customer-driven priorities for managerial action and aligning people and processes with these customer-driven priorities to achieve desired business results.