CX Key TermsCustomer experience can make or break your company. Whether you’re a rookie or a seasoned pro in CX, check out our definition pages to learn more about CX buzzwords and jargon.

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Action Planning

Action planning is the process of defining and carrying out company objectives through detailed steps

What is Action Planning? Action planning refers to the process of defining and carrying out company

objectives through detailed steps. It’s a way to ensure a company’s vision is concrete. The process of action planning involves several steps such as, what actions or changes will occur, who will carry out these changes, by when will they take place, and for how long, what resources are needed to carry out changes, and who should know what, when? Creating an action plan helps to allocate funds, prioritize tasks and maintain accountability. As more and more companies are beginning to focus on customer experience (CX), using action planning in a CX setting is becoming a viable option in providing organizational change.

Advanced Analytics

"We should be talking about the analytics of things, not the Internet of Things" — Jim Davis, SAS CMO

Advanced analytics focus on the forecasting, simulation and optimization of future events to produce insights that traditional business intelligence approaches, such as query and reporting, are unlikely to discover. Using complex and intricate methodologies – such as text analytics, data mining, machine learning, pattern matching, forecasting, visualization, semantic analysis, network and cluster analysis, multivariate statistics, graph analysis, simulation, complex event processing, and neural networks – advanced analytics seek to provide predictions and recommendations to business questions. They can be applied in a variety of settings, including market research, Voice of the Customer (VoC) programs, Voice of the Employee (VoE) programs (VoE), and any other setting that needs deeper insight into big data.

There are two types of advanced analytics: predictive and prescriptive. Predictive analytics use data collected in the past, such as user preferences, demographics, purchase history and consumer sentiments, to forecast the future. Amazon is a great example of this. By examining what and when consumers buy on their website, their algorithms can suggest items that the customer may be interested in purchasing. In a customer experience (CX) setting, this technology would allow prediction of what customers want, even if they don’t directly state it.

Advanced Market Research (AMR)

AMR helps leaders understand the context of the overall market, so they can predict trends with greater accuracy.

What is Advanced Market Research (AMR)? Advanced Market Research explores hidden relationships within industry data,

collected by a market research firm, in order to predict and forecast future events and behavior within the market. Also known as inferential statistics or advanced analytics, it is a step beyond the basic data collection done in rudimentary market research. AMR pursues insights that cannot be discerned from initially viewing the data, using methods such as correlation analysis, conjoint analysis, maxdiff, factor and principle component analysis, structural equation modeling, cluster analysis, and nonlinear regression. It goes beyond just explaining the conditions of the data set, and seeks to predict and draw conclusions based on the present data. This data is ultimately used to understand consumer purchasing preferences.

Big Data

Big data refers to large amounts of data that can’t be processed by traditional methods Open the door to seamless experiences What Is Big Data? Big data refers to large amounts of data, stored by companies, that are unable to be processed

by traditional data processing. The number of sources of data is ever increasing. This has led to an exponential growth in the amount of structured and unstructured data being created and is fast becoming the norm for companies every day. Big data is relative to the amount of computing power a company has. A small company may consider big data thousands of gigabytes, while a large enterprise may consider big data hundreds of terabytes. In order to gain a competitive edge, organizations, big or small, must learn to utilize their data effectively.

Big data is often spoken of in conjunction with broad terms like predictive analytics and behavioral analytics. Data analytics programs are used with more specific tools like data mining to gain insights from large amounts of data, which will enable businesses to make predictions and conclusions that will aid an organization in making effective business decisions and increase share of wallet.

Case Management

Case management is the process of coordinating a case, or an individual customer-company interaction, to achieve a successful outcome

Provide quality customer care through quick and personal solutions What is Case Management? Case management is the process of coordinating a case, or an individual customer-

company interaction, to achieve a successful outcome. This could include anything from walking a healthcare patient through the recovery process at a hospital to reaching out to a disgruntled customer by offering a free or discounted service.

Case management falls under the umbrella of customer experience management (CXM), but differs in that it focuses on individual interactions rather than on the overall customer experience. Service recovery, the effort that companies put forth to satisfy customers by compensating for poor experiences they’ve had with the company, is a facet of case management, but does not cover the entire process of case management, from the beginning to the end of a customer’s interation with the company.

Customer Experience (CX)

Making customers the center of your business universe.

What is Customer Experience (CX)? Customer Experience (CX) describes how customers feel about their

collective experiences and interactions with a company—including their overall relationship with a specific brand. “CX,” together with terms like “Customer Experience Management (CXM or CEM),” are also often used to describe an organization’s ongoing efforts to measure, manage, and improve their customers’ perceptions and experiences.

Customer Experience Research (CXR)

Customer experience research is the process of collecting data regarding the experience customers have with a company.

"You've got to start with the customer experience and work back toward the technology - not the other way around." - Steve Jobs

What is Customer Experience Research (CXR)? Customer experience research (CXR) is the process of collecting data regarding the 

experience customers have with a company (CX). It is a crucial part of a good CX program and can help companies better understand their customers’ needs and desires, so that they can build a customer-centric business model. It gives companies the tools they need to satisfy customers, build customer loyalty, and increase wallet share and promotion, which will in turn create substantial return on investment. Customer experience research is a subset of marketing research, or research done for a specific company and with data collected from its own customer base.

Customer Journey Mapping

Journey Mapping is a flexible consulting engagement for organizations seeking insights into what their customers feel and experience.

Gain deep, accurate insights into your customers’ collective experiences with your business. What is Customer Journey Mapping? A customer journey map is a visual representation of the journey a customer has with a company’s

brand, products, services and people. The process of creating one is called customer journey mapping. A customer journey map visualizes all touch points between the customer and the organization, from customer research on the product, to first contact with the company, to building customer loyalty. By constructing theoretical customer decision-making scenarios, companies can more easily understand factors and product features that influence customers’ purchase decisions.

Journey Mapping is an outside-in exercise, reviewing and documenting the stages of customers’ lifecycle from their points of view looking in. Customer journey maps may also be called customer interaction maps, customer corridors, or service blueprints. Customer Process Mapping (CPM), often an artifact of Six Sigma or Lean work efforts document, is similar but different from customer journey mapping in that it is about internal processes and the channels businesses undertake when serving a customer.

Customer Prospects

Customer prospects, while undesirable, can provide unique insight. “There is a big difference between a satisfied customer and a loyal customer.” –

Shep Hyken What is a Customer Prospect? Companies have the burden of maintaining customers. Millions of dollars per year

are invested in programs that are designed to ensure that clients stay. Yet, even in the midst of the bustling humdrum of customer retention, people can still get left out. Not because of lack of engagement, but because of complacency and neglect in the company-customer relationship. If left unchecked, this relationship can devolve into what is called, “customer prospects”.  This means that even though customers are staying, they are evaluating competition. These prospects are officially “in-the-market.” Customer prospects are hard to detect because more often than not, their existence isn’t known until it’s too late. Below are some helpful characteristics and strategies for interacting with customer prospects.

Customer Satisfaction (CSat)

“A satisfied customer is the best business strategy of all.” – Michael LeBoeuf What is CSat/Customer Satisfaction? Customer satisfaction (CSat) is a key performance indicator that measures how happy

customers are with different aspects of a company’s products, services, or customer interactions. It is an outcome metric that shows how well a company’s performance matches up to customer expectations.

Customer satisfaction survey questions focus on analyzing customer happiness with individual interactions or products of a company, and do not measure customers’ overall relationship with the brand. They are widely used in almost all customer surveys.

Companies may also measure customers’ happiness with their services using other metrics, but these are separate measures and do not fall under the umbrella of CSat.

Net Promoter score Behavioral metrics Text analytics (customer complaints)

Customer Service

Customer service involves any interaction between staff and customers Customer service is genuinely caring for people Customer service refers to the interactions between customers and

company staff. This could include a specific department that deals with customer complaints and returns or the company philosophy for employees dealing with customers. Regardless of the definition chosen, every company aims for great customer service. Each year, $41 billion is lost by U.S. companies due to bad customer service.  In today’s highly competitive market, customers are unwilling to deal with companies that don’t address their concerns quickly, effectively, or as they would like them dealt with. To prevent such a loss, it is imperative customers leave having had a great customer experience (CX).

Customer Loyalty

Loyalty means sticking around when it isn’t easy, rejecting competition and believing in a transcendental customer-company relationship

Loyalty is built on trust Customer loyalty is believing that an organization’s product is the best option. It’s more than a casual friendship. Loyalty

means sticking around when it isn’t easy, rejecting competition and believing that the customer-company relationship transcends products and services.

Most people aren’t 100% loyal to one brand. One may shop from three grocery stores, loyal to them all, and none others, but not loyal to one completely. This has been termed polygamous loyalty. Due to split loyalties, it is in the best interest of companies to invest in customer loyalty and be the one that holds the most wallet share. Loyal customers can keep sales coming, even in economic downturns, they can purchase supplementary products/services, bring in new customers and reduce costs for consumer marketing.

Loyalty can also come in two different types, behavioral and attitudinal. Behavior loyalty refers to those who buy the company’s products and tell their friends about them. Whereas attitudinal loyalty refers to the positive emotions that people have towards a company or its products.

Customer loyalty can be confused with similar terms such as brand advocacy, loyalty programs, and customer satisfaction. Brand advocates believe in what the company stands for, regardless of products/services. Not all brand advocates are loyal customers. The inverse is also true. Not all loyal customers are brand advocates. Loyalty programs don’t often affect loyalty. Usually they are executed improperly and result in the equivalent of discounted rates rather than customer that stay. Customer satisfaction is also a small indicator of loyalty. While it plays a part in it, loyalty is more than just a good experience.

Data Cleansing

Data cleansing is the process of fixing any and all data quality issues arising in a dataset. "Without a systematic way to start and keep data clean, bad data will happen." - Donato Diorio What is Data Cleansing? Data cleansing is the process of fixing any and all data quality issues arising in a dataset. It is 

alternately known as data cleaning, data washing, or data scrubbing. Data cleansing, performed by specialized software programs, scans datasets looking for errors in data quality.

Data quality dimensions are defined in many ways by different organizations, but generally include most of the following factors:

Accuracy – Is the information correct? Is the customer’s name spelled correctly, or are there typos? Completeness – Is any part of a value missing? Does the telephone number have the right number of digits? Uniqueness – Is any customer’s information entered in the database more than once? Consistency – Does the data translate correctly between its collection and storage? Timeliness – Is the data sufficiently current to provide value to the company? Integrity – Is the data correctly linked, or will further analysis create uniqueness issues? Conformity – Is each data value recorded in the same format?

Data Mining

“It is a capital mistake to theorize before one has data.” – Arthur Conan Doyle

What is Data Mining? Data mining software unearths correlations in large datasets. It quickly

and systematically combs through big data, using artificial intelligence, pattern recognition, traditional statistics, and graphics to present hidden relationships, patterns, and correlations between measurable variables in a data pool. These patterns are then converted into a format that can be understood by data specialists. Companies can use these insights to improve their customer experience (CX)

Employee Engagement

Employee satisfaction surveys help companies assess When your employees are happy, so are your customers. What is Employee Engagement? Employee engagement is the measure of an employee’s commitment to

the success of an organization. Engaged employees enthusiastically perform their duties with a resolve to accomplish the goals of the company. Their motivation to work does not stem simply from a paycheck, or upward mobility, but from devotion to the work they are performing.

Engaged employees voluntarily seek to better understand their work. When the task is clear, they make an effort to exceed expectations and improve the company. They often recommend the company to others as a good place to work, and have strong relationships with colleagues.

Enterprise Feedback Management (EFM) EFM software makes survey data readily accessible and actionable to a

company’s employees–from the front line to the C-suite What Is Enterprise Feedback Management (EFM)? Enterprise feedback management is the process of collecting, analysing,

and taking action on customer feedback for an enterprise-class large company. It is principally involved with the distribution and analysis of surveys.

Enterprise Feedback Management is similar to customer experience management (CXM), but whereas EFM focuses just on dealing with customer feedback, CXM uses all aspects of a customer’s experience, from feedback to transactional data to retention rates. Both can be used at the enterprise level to enact productive change.

Mystery Shopping

Mystery shopping is the process of recruiting and paying individuals to provide feedback on company protocols, services and products

Mystery Shopping is fast becoming a more viable option for evaluating services What is Mystery Shopping? Mystery shopping is the process of recruiting and paying individuals to provide

feedback on company protocols, services and products. Pre-qualified customers go to a store location, purchase products, services or interact with employees. After the transaction is complete, mystery shoppers log the feedback into the company system by reporting on the quality of the service, products, or compliance with regulation. They also perform certain tasks such as purchasing products, asking questions, registering complaints, or behaving in a certain way.  This allows a company to identify how well it is delivering on brand promises by using the customer experience. In addition, mystery shopping allows deficiencies to be identified and resolved.

Net Promoter Score (NPS)

Loyal customers are your most effective advertising. What is NPS? NPS®, or Net Promoter Score®, is a popular Customer Experience (CX)

metric designed to measure the willingness of a company’s customers to recommend the company’s products or services to others. NPS® is a straightforward indicator of overall CX performance, and organizations can use their scores to quantify customer experience and predict future business results.

The Net Promoter Score framework was developed by Fred Reichheld of Bain and Company several years ago. His books, the Ultimate Question and theUltimate Question 2.0, have helped establish a strong business case for NPS among executives.

Predictive Analytics

Predictive analytics is the branch of data mining concerned with the prediction of future probabilities and trends.

Boost your CX program’s ROI by predicting the future. What is predictive analytics? Predictive analytics is the branch of data mining concerned with the prediction of

future probabilities and trends. The central element of predictive analytics is the predictor, a variable that can be measured for an individual or other entity to predict future behavior.

With the usage of predictive analytics, organizations with declining survey response rates, can predict and address individual customers in need ofremediation. This can, in turn, significantly boost CX program ROI. According to the White House Office of Consumer Affairs, for every customer who bothers to complain, 25 other customers remain silent. Predictive analytics in CX help companies give a voice to the silent majority and helps them recover silent detractors.

Purpose of Surveys

Surveys align the needs of customers with the goods and services that companies provide.

We are passionate about listening to and responding to customers as unique individuals

Why use Surveys? Surveys align the needs of customers with the goods and services that companies

provide. They serve different purposes for the company and the customer, so each has incentive to create or participate in the survey experience.

Surveys are beneficial for customers in that they give them an outlet to praise good service or air grievances. Customers can have an impact on company procedure – or at least, they can feel like they’re making a difference. In this way, companies can form an emotional connection with their customers, build customer loyalty, and gain insights that will help them to better provide what customers want.

Qualities of a Great Survey

Action taken on survey data is one of many ways to improve the customer experience. Purposes of a Customer Survey: An average business will not hear from 96% of its dissatisfied customers. When considering that

91% of those dissatisfied customers who go unheard will leave and not return, that statistic becomes an important bottom-line influencer. A dissatisfied customer, however, will often be willing to voice an opinion when prompted by the offending company. One of many ways to solicit this information is through a customer survey.  The ultimate goals of this survey are to:

Identify and fix any meaningful problems that have occurred for customers with the company’s products or service.

Assess and improve the performance of its customer-facing units (retail locations, call centers, digital care team, etc.) and staff (salespeople, call center reps, etc.).

Improve its processes and standards for delivery. Understand customers’ needs as they use the company’s products or services so the company can

provide them a better overall experience.Source

Service Recovery

When your customer is unhappy, what will you do? What is Service Recovery? Service recovery is the effort that companies put forth to satisfy customers by

compensating for poor experiences they’ve had with the company, its employees, or its products or services. Customers who have experienced service or product failure, and have not been compensated or helped by the company, can become disgruntled or angry toward the company. These unhappy customers often stop buying from the company or even create negative publicityfor the company.

If companies collect customer feedback and act to make up for negative experiences, they can often retain these customers. They may compensate customers monetarily, with replacements and returns, or simply by apologizing for negative service interactions.

Social Listening

Capturing, understanding, and responding to every comment from any source

See beyond traditional metrics.

Why is social media feedback management important? Customers around the world are constantly telling each other what they

love about your brand, what they hate about it, when they enjoyed their service experience, and when they didn’t. Social media feedback management allows you to tap into this enormous pool of authentic comments, reviews, and complaints to discover candid, unfiltered insights about your customers and your company.

Survey Program Solutions

Creating productive conversations with your customers. Get closer than ever to your customers. What makes a strong, successful survey program? Some claim that surveys are becoming less important and relevant, but most industry experts agree that

there is still simply no better way to understand what customers are thinking and feeling. Today, surveys are also about more than simply collecting and measuring customers’ preferences and opinions. With the right solution and approach, surveys can open productive new lines of communication with your customers, show them that you understand and care about their opinions and preferences, and help you gain deep insights to improve your business.

The most successful programs combine many different types of surveys—transactional, relationship, self-serve, and ad-hoc surveys to name just a few—with the ability to quickly deploy them across a wide variety of traditional, email, online, and social media channels. Your survey program solution should also give you the flexibility to leverage and combine different types of survey questions and approaches, including open- and close-ended, multiple choice, scale, or simple yes/no questions.

Finally, your survey program should include the ability to combine and quickly analyze survey data from many different sources, so you can convert the flood of raw survey data you’re receiving into useful and relevant business insights.

Text Analytics

Capture, analyze, and respond to unstructured feedback from your customers. What is Text Analytics? Text analytics is all about turning customer comments into quantifiable data.

Computers like numbers and patterns, which customer comments and complaints, submitted via surveys or website comments, unfortunately do not provide. Text analytics programs, also known as text mining programs, create accessible quantitative data from natural-language input.

Most surveys ask general satisfaction questions and assign numerical values to the answers. Many will follow those questions with open-ended questions that ask why respondents chose the score they gave. Text analytics allow companies to understand the ‘why’ behind the score by making text responses into quantitative data.

Voice of Customer (VoC)

Voice of Customer (VoC)Capturing and understanding everything your customers say about your company.Your most unhappy customers are your greatest source of learning.What is the Voice of the Customer (VoC)? Voice of the Customer refers to a process or programme designed to capture customers’ preferences and opinions, analyse them to gain new business insights, and then share them to create meaningful change.

Most VoC programmes work to collect and unify customer feedback across many different sources, channels, and touch points. This starts with formal structured sources like email and website surveys, customer interviews, focus groups, and other initiatives where companies actively seek feedback from their customers. But the most successful VoC programmes also incorporate a wide variety of unstructured, customer-initiated feedback, including product reviews on third-party websites, unsolicited comments on social media sites, and customer support inquiries.

Voice of the Employee

Employee Engagement Helps Drive Productivity and Growth

Treat your employees exactly as you want them to treat your best customers.

What is the Voice of the Employee (VoE)? Today, more than ever, companies must attract and retain top talent to stay competitive. Voice of

the Employee (or Voice of Employee) programs play a key role in those efforts—by making it possible to systematically collect, manage, and act on feedback and input from employees on a variety of subjects. For example, most successful VoE programs collect job engagement and satisfaction data, ideas for improving internal programs and processes, suggestions for improving products and services, and more.

VoE programs typically use a variety of methods to collect and analyze data from employees, including surveys, group studies, management reviews, and focus groups. Then, they have tools in place to analyze input from employees and convert it into relevant, actionable insights that management can use to boost employee engagement, increase productivity, and improve profits.