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Table of Contents:

: Customer Experience

Overview

Customer experience is rapidly evolving. There was time when market research was the only way to gather the voice of the customer (VOC). In today’s environment, many forms of listening posts have been created to gather the VOC from different perspectives. In addition, customers are not waiting to tell organizations what they think. They are becoming increasingly comfortable with self-service using automation to obtain goods and services rather than relying on others. Self-service provides more user control of the experience. Not all customers want this ability, but many do. Automation can also provide a very deep customer experience because it uses previous purchase decisions to build predictive models to mimic the customer’s purchasing behavior. The result is that they are presented with information, products, and services that coincide with historical preferences. This promotes customer satisfaction.

We as customers have a perception of great customer service or product design as well as the interfaces that customers access for transactions. Customer satisfaction is now highly dependent on these interfaces because expectations have been previously set based on prior personalized experiences. The expectation also carries over to personal interactions. When customers receive good service from automated bots, they then expect no less from personal interactions where more types of information are available for transmission between customers and sellers. In both situations, a balance must be set between efficiency and personalization.

Other expectations now routine for customer experience are transparency for information collected and products and services provided. It is unlikely today to fail to meet customer expectations without reports showing up on social networks calling out an organization for poor services or products. Transactions are increasingly transparent. In this context, it is also important that personal privacy be respected when personal information is exchanged. Data that are requested should be needed only for the transaction and encrypted for security. The General Data Protection Regulation (GDPR) requirements discussed in Chapter 10 and Table 10.7 are applicable. Customer satisfaction will not be high for organizations that mishandle personal information or have had data breaches.

Employee training is always relevant regardless of the level of automation applied by an organization. Customers will always interact with employees to some degree. These encounters influence their perceptions of an organization based on previous experiences with other organizations. Employee skills should always be updated and expanded. Soft skills related to listening, negotiation, subject matter expertise, and an ability to resolve issues quickly and effectively will always enhance the customer experience. Relationship building, to the extent possible given the nature of the interaction and transaction, is also important.

Leading-edge organizations do not just listen to customers but ask them about needs requiring solutions. Sometimes customers do not know what is needed until suppliers go on-site and see their products and services being used by the customer’s employees. Customers are also evolving their own products, services, and supporting operations. Suppliers need to understand industry trends to continue providing value to their customers. They need to enhance the customer experience by proactively managing the back-end of their customer-facing process. To do this customer transactions are analyzed for ways to enhance customer satisfaction while maintaining operational efficiencies. As an example, customers increasingly do not like waiting. The tolerance for waiting varies from person to person and by use case. Models are being built to ensure minimum waiting time and high customer satisfaction while lowering operational cost. Data management enables the application of analytics and modeling to develop predictions of customer behavior based on correlated factors to enhance the customer experience.

As a result, analysts must continually learn new analytical skills. This information is incorporated into success measures and dashboards for reporting, operational management, and continuous improvement. Two useful metrics are customer satisfaction (CSAT) and the net promoter score (NPS), in addition to industry-specific metrics such as active users of a service or customers who opt into software applications after free trials. In this chapter, we will discuss ways to gather and analyze the VOC. Then in Chapter 4 we will discuss translating the VOC into the design of products and services.

Gathering “voice of” information is a general phrase for all methods used to collect information from suppliers, employees, partners, and customers. It involves both active and passive collection. Active methods include visiting customers, partners, and other groups to conduct focused interviews that involve customers in meetings to understand moments of truth. These are points in the supplier-customer interactions where expectations are met or are not met. In contrast, passive methods rely on collecting information from analyses of complaints, warranty reports, and similar sources, often without contacting those providing the information. Once “voice of” information is gathered, it is conditioned, categorized, and analyzed by modeling relationships between inputs (e.g., demographic or stratification variables) and outputs of interest (e.g., measures of satisfaction, loyalty, or performance).

Creating a consensus with stakeholders and other respondent groups requires that survey questions be unambiguously framed to ensure consistent interpretation and delivered using a standardized process across interviewers. In this context, well-documented procedures, a standardized process, and reliable survey tools and methods are needed to define, gather, and summarize the “voice of” information. Otherwise, there will be misunderstandings. People have different perspectives, and they take actions reflecting their unique understanding of the relevant information. As an example, a classic “voice of” exercise is to ask participants what information will be important for controlling operations. The situation could be a movie theater, restaurant, or anything else. The list of recommendations might include operational productivity drivers such as employee attendance, sales, inventory levels, complaints, and similar items. The customer-centric metrics will be missing. In contrast, when the participants are asked to assume the role of customer, a different list of recommendations is made. This list is likely focused on ease of use, such as parking, access to products or services, safety, price, and similar needs. Combining the two lists provides a holistic basis for a comprehensive array of “voice of” information. Process improvement planning will be more balanced using this approach.

Understanding customer needs and sentiment are the basis for product design and service improvement. Listening to customers provides unique opportunities for improving products and services or to design entirely new ones that excite customers. Process improvement programs rely on planning and on gathering and analyzing the VOC to identify gaps and project opportunities. The “voice of” focus has been expanded to include other stakeholder groups, such as employees, suppliers, and others, to improve products and services. In this context, an interesting application is “voice of” the field, which includes sales staff and service people. Their recommendations help augment information to better describe the customer experience.

The “voice of” information is gathered from diverse sources, using efficient methods. These sources are called listening posts. A survey may rely on one or more listening posts having differing costs, time commitments, and information content. Examples include social media (e.g., Twitter, Facebook, or Linkedln), complaint logs from customer calls, voice transcripts, information contained in published articles or similar published sources. The data from these sources are unstructured, meaning the data are not simply numbers in tables. These data are used to augment traditional data sources such as customer concessions for poor service, warranty expenses, and similar types of information that are available in a structured format (e.g., numbers representing expenses, times, and the number and types of complaints). Figure 3.1 describes listening posts (or modes) and data collection strategies. There are basic considerations when planning to gather “voice of” information. The first considerations are the purpose for the data gathering and the needed information. It is important to consider how the information will be used, i.e., for process improvement to increase customer service satisfaction and or to reduce the time between product order and delivery to improve the customer’s purchasing experience. Initial planning considers data type, the target audience (including segments and respondents), the type of survey (e.g., transactional, relationship, in-person, etc.), the timing, and resource availability.

FIGURE 3.1

Ways to obtain “voice of” information.

 
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