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Customer Experience Glossary: Terms You Should Know

Sơn Vũ vào Jul 26, 2023

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When researching customer experience, you might see all kinds of terms used which may be enough to leave you feeling like you’re being thrown on a loop. Rest assured, though, that’s where we come in and try to help you understand these terms a little bit better.

There are a lot of terms being listed here so don’t forget to press Ctrl + F (or Cmd+F) and find the term that you want to learn more about. With that being said, let’s get started.

Customer Experience Glossary: Terms and Descriptions


Abandonment rate: The percentage of customers who start a process but leave it incomplete. For example, the percentage of customers who add items to their online shopping cart but do not complete the checkout process.
Acquisition: The process of attracting and bringing in new customers to a business or organization. It typically involves marketing and sales efforts aimed at reaching new audiences and converting them into customers.
Average order value (AOV): The average amount of money a customer spends per transaction or order with a business. It is calculated by dividing the total revenue generated by the total number of orders.
Agent: A customer service representative or other employee who interacts with customers on behalf of a business. Agents may assist customers with their inquiries, provide support, or help resolve any issues or concerns.
Artificial intelligence (AI): The use of computer algorithms and machine learning to simulate intelligent human behavior, such as natural language processing and problem-solving. In the context of customer experience, AI can be used to automate tasks, personalize customer interactions, and provide predictive insights.
Asynchronous messaging: A communication method that allows customers to send messages at any time and receive a response at a later time, without requiring a real-time conversation. Asynchronous messaging includes email, social media messaging, and SMS messaging.
Average basket size: The average number of items purchased per order or transaction by customers. It is calculated by dividing the total number of items purchased by the total number of orders.
Average handling time: The average amount of time it takes for a customer service representative to handle a customer inquiry or issue. It includes the time spent interacting with the customer and any necessary follow-up activities.
Average resolution time (ART): The average amount of time it takes to resolve a customer issue or inquiry. It includes the time spent interacting with the customer, researching the issue, and implementing a solution.
Average speed of answer: The average amount of time it takes for a customer service representative to answer a customer's call or respond to a customer inquiry.


Brand advocate: A customer who actively promotes a brand or business to others. Brand advocates are typically loyal customers who have had positive experiences with a brand and are willing to share their experiences with others.
Business intelligence: The use of data and analytics to gain insights into business performance and customer behavior. It involves collecting and analyzing data from various sources, such as customer interactions and sales data, to inform business decisions.
Business process outsourcing (BPO): The practice of contracting out specific business processes to a third-party provider. BPO can include customer service, data entry, and other back-office functions.


Case management: The process of tracking and managing customer issues or inquiries from start to resolution. It typically involves assigning cases to specific agents, tracking progress, and following up with customers as needed.
Close the loop: The process of following up with customers after a service interaction or purchase to ensure their satisfaction and resolve any outstanding issues or concerns.
Customer-centric: A business or organizational approach that focuses on meeting the needs and preferences of the customer. Customer-centric businesses prioritize the customer experience in all aspects of their operations.
Customer expectations: The expectations that customers have for a business or organization, based on their previous experiences, interactions with the brand, and other factors. Meeting or exceeding customer expectations is a key component of delivering a positive customer experience.
Customer experience (CX): The overall impression or perception a customer has of a brand or business, based on their interactions with the brand across all touchpoints and channels. A positive customer experience can lead to increased customer loyalty, repeat business, and positive word-of-mouth referrals.
Customer experience management framework: A structured approach or methodology for designing, delivering, and managing the customer experience. It typically includes customer journey mapping, touchpoint analysis, and other tools to help businesses understand and improve the customer experience.
Customer experience maturity level: A measurement of a business's ability to deliver a consistent and positive customer experience across all touchpoints and channels. Businesses with a higher customer experience maturity level typically have well-defined processes, tools, and metrics in place to manage the customer experience.
Customer effort score (CES): a metric used by businesses to measure how easy or difficult it is for their customers to interact with their products, services or support. It is based on a survey question asking customers to rate on a scale from 1 to 5 how much effort they had to put in to resolve their issue or complete a task. The purpose of CES is to identify areas of the customer experience that can be improved to reduce friction and make it easier for customers to achieve their goals.
Customer feedback: The opinions and comments customers provide about their experiences with a brand or business. Customer feedback can be gathered through surveys, reviews, social media, and other channels.
Customer journey mapping: The process of visualizing and analyzing the customer's journey across all touchpoints and channels. It can help businesses identify pain points, opportunities for improvement, and areas where they can deliver a more seamless and positive customer experience.
Customer loyalty: The degree of commitment or loyalty that a customer has to a brand or business. Loyal customers are more likely to repeat business and refer others to the brand, which can lead to increased revenue and growth.
Customer relationship management (CRM): The process of managing and nurturing customer relationships over time. It typically involves using software and other tools to track customer interactions, analyze customer data, and provide personalized experiences.
Customer satisfaction (CSAT): A measurement of how satisfied customers are with a brand or business. CSAT surveys typically ask customers to rate their experience on a scale of 1 to 5 or 1 to 10.
Customer service: The process of providing support and assistance to customers who have questions or issues related to a product or service. Good customer service is essential for delivering a positive customer experience.
Customer survey: A tool used to gather feedback and opinions from customers. Surveys can be conducted through various channels, such as email, social media, and in-person interactions.
CX transformation: The process of transforming the customer experience across all touchpoints and channels. It typically involves a comprehensive approach to the design, delivery, and management of the customer experience.


Data mining: The process of analyzing and extracting insights from large sets of data. Data mining can be used to identify patterns, trends, and other insights that can inform business decisions.


Leading question: A question that is designed to elicit a specific response from the person being questioned. Leading questions can bias the results of surveys and other research studies.


Key driver analysis: A statistical technique used to identify the factors that have the biggest impact on a particular outcome or behavior. In the context of customer experience, key driver analysis can be used to identify the factors that most strongly influence customer satisfaction or loyalty.


Machine learning: An application of artificial intelligence that involves training computer algorithms to recognize patterns and make predictions based on data. In the context of customer experience, machine learning can be used to personalize interactions, detect trends, and provide predictive insights.


Inspection software: Software that is used to conduct inspections and audits of products, facilities, or other assets. Inspection software can help businesses ensure compliance with regulations, identify areas for improvement, and ensure product quality.


Net promoter score (NPS): A metric used to measure customer loyalty and satisfaction. NPS surveys typically ask customers how likely they are to recommend a brand or business to others on a scale of 1 to 10.


Omnichannel: A customer experience approach that aims to provide a seamless and consistent experience across all channels and touchpoints. Omnichannel strategies often


Persona: A fictional character that represents a typical customer or user of a product or service. Personas are used in customer experience design to help businesses understand the needs, preferences, and behaviors of their target audience.
Personalization: is the process of tailoring a product, service, or experience to the specific needs, preferences, and characteristics of an individual customer by using their data. Personalization can help businesses improve customer satisfaction, loyalty, and engagement by providing a more relevant and tailored experience. Examples: 
  • An online clothing store recommending outfits based on a customer's browsing and purchase history
  • A fitness app creating personalized workout plans based on a user's fitness level and goals
  • A hotel greeting a returning guest by name and providing a room with their preferred amenities


Fragmented data: Data that is spread out across multiple systems or platforms, making it difficult to access and analyze. Fragmented data can be a barrier to delivering a seamless and personalized customer experience.


Operational audit: A review of business operations and processes to identify areas for improvement and optimize efficiency. In the context of customer experience, an operational audit can help businesses identify bottlenecks, inefficiencies, and other issues that impact the customer experience.


Predictive analytics: The use of statistical models and algorithms to make predictions about future outcomes based on historical data. In the context of customer experience, predictive analytics can be used to anticipate customer needs and preferences, as well as to identify opportunities for improvement.


Referral: A referral is a recommendation or suggestion made by someone to another person or group. In business, referrals often refer to recommendations made by existing customers to potential new customers.
Response Rate: Response rate refers to the percentage of people who respond to a particular survey or marketing campaign. It is typically calculated by dividing the number of people who responded by the number of people who were contacted.
Retention: Retention refers to the ability of a business or organization to keep its customers or employees over a period of time. In the context of customers, retention refers to the percentage of customers who continue to do business with a company over time. In the context of employees, retention refers to the ability of a company to retain its staff over a period of time.


Sentiment analysis: The process of analyzing customer feedback and other textual data to determine the emotional tone and sentiment. Sentiment analysis can help businesses understand how customers feel about their products or services and can inform decisions related to customer experience design and management.
Social media scraping: The process of collecting data from social media platforms, typically through automated tools or algorithms. Social media scraping can provide valuable insights into customer opinions, preferences, and behaviors, and can inform decisions related to customer experience design and management.
Structured data: Data that is organized and formatted in a way that is easily searchable and analyzable. Structured data can include customer information, purchase history, and other data points that are relevant to customer experience design and management.


Text analytics: The process of analyzing unstructured text data, such as customer feedback or social media posts, to identify patterns, trends, and insights. Text analytics can help businesses understand customer opinions, preferences, and behaviors, and can inform decisions related to customer experience design and management.
Touchpoint: Any interaction between a customer and a brand or business, whether online or offline. Touchpoints can include website visits, phone calls, email interactions, social media posts, and more, and are critical for delivering a seamless and positive customer experience.


Unstructured data: Data that is not organized or formatted in a way that is easily searchable or analyzable. Unstructured data can include customer feedback, social media posts, and other textual data.

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