Customer Experience Glossary

Welcome to Askdolphin’s customer experience glossary, 120 precise definitions spanning CX, customer service, and AI chat. It covers core concepts and metrics (CSAT, NPS, CES, FCR, AHT), customer journeys and touchpoints, omnichannel support, and conversational AI structured to align product, support, marketing, and ops.

Clear terms, consistent meanings, so you can make decisions faster and keep “buzzword bingo” off the agenda.

Customer Experience Fundamentals

1. Customer Experience (CX)
   Customer experience is the overall perception customers form across all touchpoints, and a strong CX strategy focuses on reducing effort, speeding resolution, and building loyalty through consistent journeys.

2. Customer Journey
   Customer journey is the path from awareness to loyalty, and mapping customer journey stages helps find friction and create smoother, conversion-ready experiences.

3. Touchpoint
   Touchpoint is any moment a customer interacts with your brand, and optimising high-impact touchpoints like checkout, onboarding, and returns reduces churn.

4. Customer-Centricity
   Customer-centricity is aligning strategy and operations around customer needs so decisions improve satisfaction, repeat purchase, and advocacy.

5. Voice of the Customer (VoC)
   Voice of the Customer gathers feedback from surveys, reviews, and conversations so teams can prioritise fixes and close the loop.

6. Omnichannel Experience
   Omnichannel experience delivers a seamless journey across web, app, email, phone, and messaging so customers never repeat themselves.

7. Personalization
   Personalization tailors content, offers, and support using customer context to improve relevance, conversion, and lifetime value.

8. Customer Journey Mapping
   Customer journey mapping visualises steps, emotions, and pain points to align teams on fixes that lift satisfaction.

9. Emotional Connection
   Emotional connection is when customers feel understood and valued, increasing loyalty and referrals.

10. Customer Expectations
    Customer expectations are the speed, clarity, and quality customers anticipate; setting and meeting them prevents disappointment.

Customer Service Metrics & Measurement

11. Customer Satisfaction Score (CSAT)
    CSAT measures satisfaction after interactions; teams often ask how to calculate CSAT and where to set CSAT benchmarks.

12. Net Promoter Score (NPS)
    NPS measures loyalty by asking likelihood to recommend; brands track NPS trends and compare NPS vs CSAT for a fuller view.

13. Customer Effort Score (CES)
    CES measures how easy it was to resolve an issue; lowering effort is a fast path to better retention.

14. Churn Rate
    Churn rate is the share of customers who leave in a period; reducing churn in SaaS often starts with fixing onboarding and value realisation.

15. Customer Lifetime Value (CLV or LTV)
    CLV estimates total revenue from a relationship; improving CLV comes from better onboarding, personalization, and retention.

16. First Contact Resolution (FCR)
    FCR is the percentage of issues solved in the first interaction; higher FCR reduces costs and boosts satisfaction.

17. Average Handle Time (AHT)
    AHT is the average time to resolve an interaction; good teams reduce AHT without hurting empathy or quality.

18. Service Level Agreement (SLA)
    SLA defines service targets like response and resolution times so expectations are clear and measurable.

19. Key Performance Indicator (KPI)
    KPI is a measurable goal that tracks performance; in service, KPIs often include CSAT, FCR, AHT, and resolution time.

20. Response Time
    Response time is how quickly a customer receives a reply after raising a query; faster response time improves trust and conversion.

21. First Response Time (FRT)
    FRT is the time from request to the first human or automated reply; lowering FRT correlates with higher satisfaction.

22. Resolution Time
    Resolution time is total time to fully resolve an issue; shorter resolution time signals effective processes and knowledge.

23. Feedback Loop
    Feedback loop is collecting insights, acting on them, and telling customers what changed to build credibility.

24. Sentiment Analysis
    Sentiment analysis detects customer emotion in messages so teams can route urgency and coach tone.

25. Customer Surveys
    Customer surveys gather structured feedback; ask brief, clear questions to maximise response quality.

26. Customer Retention Rate (CRR)
    CRR is the percentage of customers who remain active over time; improving CRR lowers acquisition pressure.

27. Renewal Rate
    Renewal rate is the share of contracts or subscriptions renewed; increasing renewal rate ties to value communicated and realised.

28. Upsell and Cross-sell Rate
    Upsell and cross-sell rate tracks expansion within accounts; helpful recommendations raise revenue without spiking effort.

29. Customer Effort
    Customer effort is the work customers must do to achieve a goal; lower effort drives loyalty.

30. Abandonment Rate
    Abandonment rate is the percentage who leave before completing a task like checkout; reducing abandonment lifts conversion.

Customer Support Channels & Skills

31. Live Chat
    Live chat is real-time text support on web or app; fast replies and proactive prompts improve conversion and satisfaction.

32. Help Desk (HD) / Ticketing System
    Help desk software tracks requests as tickets to prioritise, assign, and resolve efficiently.

33. Self-Service Portal / Knowledge Base (KB)
    Knowledge base is a searchable library of guides and FAQs that reduces time to resolution.

34. Email Support
    Email support handles asynchronous issues; clear templates and SLAs keep tone and speed consistent.

35. Phone Support / Call Centre
    Phone support addresses complex or urgent cases; good routing and coaching keep AHT and escalations in check.

36. Social Media Support
    Social support resolves issues on public platforms to protect reputation and speed assistance.

37. Messaging Apps (WhatsApp, Messenger, WeChat)
    Messaging support offers always-on, conversational help where customers already are.

38. Chatbot (Rule-Based)
    Rule-based chatbots use scripted flows for FAQs; great for predictable requests and deflection.

39. Conversational AI
    Conversational AI understands intent and context to handle varied queries more naturally.

40. Virtual Assistant (VA)
    A virtual assistant is a digital agent that helps customers complete tasks like order status or returns.

41. Voice Bot / Voice AI
    Voice bots automate spoken requests and route calls based on intent.

42. Interactive Voice Response (IVR)
    IVR is an automated phone menu that gathers inputs and directs callers without agent involvement.

43. Agent Assist Tools (AA)
    Agent assist surfaces suggestions, summaries, and knowledge in real time to speed accurate replies.

44. Escalation Process
    Escalation defines when and how complex issues move to specialists for resolution.

45. Omnichannel Support
    Omnichannel support lets customers move between channels without losing context.

46. Multilingual Support (MLS)
    Multilingual support serves customers in multiple languages, often with translation and language routing.

47. 24/7 Support
    24/7 support provides around-the-clock coverage through regions, shifts, or automation.

48. Personalization in Support
    Personalised support uses profile and history to tailor solutions and reduce back-and-forth.

49. Empathy
    Empathy recognises feelings and responds with validation and clarity to de-escalate issues.

50. Active Listening (AL)
    Active listening focuses fully, reflects understanding, and confirms next steps to avoid miscommunication.

51. De-escalation Techniques (DET)
    De-escalation uses calm language, validation, and options to move from conflict to solution.

52. Tone and Voice (T&V)
    Tone and voice define style and personality; consistent T&V strengthens brand trust.

AI Chat & Conversational AI

53. Natural Language Processing (NLP)
    NLP enables machines to understand and generate language so chatbots can interpret intent and reply clearly.

54. Machine Learning (ML)
    ML lets systems learn from data to improve predictions, routing, and suggested answers.

55. Generative AI (GenAI)
    Generative AI produces human-like responses and content to scale accurate, on-brand service.

56. Conversational AI Platform (CAIP)
    A CAIP provides tools to design, deploy, and manage bots, agents, and workflows.

57. Intent Recognition (IR)
    Intent recognition identifies what the customer wants so routing and responses are relevant.

58. Entity Extraction (EE)
    Entity extraction pulls details like names, dates, and order IDs to speed resolution.

59. Context Management (CM)
    Context management keeps memory across turns so customers don’t repeat themselves.

60. Dialogue Flow (DF)
    Dialogue flow structures the conversation to prevent dead ends and guide next steps.

61. Prompt Engineering (PE)
    Prompt engineering crafts inputs so GenAI responds accurately and in brand voice.

62. Training Data (TD)
    Training data is the corpus that teaches models; quality data reduces error and bias.

63. Knowledge Base Integration (KBI)
    KBI connects bots to up-to-date articles and policies to ground answers in facts.

64. Bot Handover to Human Agent (H2H)
    H2H transfers with context to an agent when automation isn’t enough.

65. Multimodal Chatbots (MMB)
    Multimodal chatbots handle text, voice, and images to improve clarity and access.

66. Sentiment Detection / Emotion AI (SD/EAI)
    Emotion AI senses mood/urgency so teams can prioritise and coach tone.

67. Speech-to-Text (STT) / Text-to-Speech (TTS)
    STT transcribes speech and TTS reads replies aloud to support voice channels.

68. Multilingual NLP (MNLP)
    MNLP enables bots to understand and reply in multiple languages.

69. AI Summarisation (AIS)
    AI summarisation condenses long chats for quick handovers and follow-ups.

70. Smart Routing (SR)
    Smart routing sends tickets to the right queue or agent based on intent and context.

71. Predictive Analytics (PA)
    Predictive analytics forecasts churn, satisfaction dips, or purchase intent so teams can act early.

72. ChatOps (CO)
    ChatOps puts tools and automations inside chat so agents trigger workflows without switching tabs.

73. Agent Assist AI (AAA)
    Agent assist AI suggests next best actions, retrieves knowledge, and drafts replies.

74. Bot Analytics (BA)
    Bot analytics tracks containment, drop-offs, and satisfaction to guide optimisation.

75. Conversational UX (cUX)
    Conversational UX designs flows, tone, and recovery so chats feel natural and effective.

76. Natural Language Generation (NLG)
    NLG creates coherent responses from structured or unstructured inputs.

77. Large Language Model (LLM)
    An LLM is a pre-trained model used for understanding and generation in modern AI chat.

78. Fine-Tuning AI Models (FT)
    Fine-tuning adapts a model to brand data and policies for higher accuracy.

79. Hallucination (AIH)
    Hallucination is when a model produces incorrect information; retrieval and policy checks reduce it.

80. AI Ethics and Bias (AIEB)
    AI ethics and bias focus on fairness, transparency, and accountability in automation.

81. Data Privacy and GDPR Compliance (GDPR)
    GDPR compliance ensures lawful, secure handling of EU personal data in support and automation.

Tools & Buying Terms (High Purchase Intent)

82. AI Chatbot Software (AICS)
    AI chatbot software provides the platform to build, deploy, and measure chatbots for web, app, and messaging.

83. Conversational AI Tools (CAIT)
    Conversational AI tools power advanced agents with NLP, ML, and orchestration.

84. Customer Support Platform (CSP)
    A CSP unifies ticketing, chat, and knowledge base with shared context and analytics.

85. Customer Relationship Management (CRM)
    CRM manages customer data and interactions so service, sales, and marketing can align.

86. AI Helpdesk Software (AIHD)
    AI helpdesk software automates triage, routing, and suggested replies to increase deflection.

87. Chatbot Builder / No-Code Bot Builder (CBB)
    CBB lets teams create bots without code using templates and drag-and-drop flows.

88. AI-Powered Live Chat (AILC)
    AILC augments agents with suggestions and automation to improve speed and quality.

89. Virtual Agent as a Service (VAaaS)
    VAaaS delivers hosted chatbots managed by a provider for faster time-to-value.

90. Generative AI SaaS Platforms (GenAI SaaS)
    GenAI SaaS offers subscription AI for dynamic, brand-safe conversations.

91. Chatbot Templates (CBT)
    Chatbot templates are pre-built flows for FAQs, returns, and order status.

92. Chatbot Integrations (CBI)
    CBI connects bots to CRM, ecommerce, payment, and messaging systems.

93. Pricing Model (PM)
    Pricing model defines billing—per agent, per conversation, or flat subscription.

94. Uptime / SLA Guarantees (SLA)
    Uptime/SLA promises availability and performance, often with credits for breaches.

95. Vendor Support & Professional Services (VSPS)
    VSPS covers implementation, training, and customisation for a successful rollout.

96. Security & Data Protection (SDP)
    SDP includes encryption, access controls, auditing, and compliance.

97. Customisation & Branding (C&B)
    C&B tailors bot persona, tone, and UI to match brand and audience.

98. Scalability (SCB)
    Scalability is the ability to handle growth in users and conversations without degradation.

99. Multichannel Deployment (MCD)
    MCD runs bots across web, apps, messaging, and social simultaneously.

100. Analytics & Reporting Features (ARF)
     ARF surfaces KPIs such as containment, CSAT, and drop-offs to prove ROI.

101. Free Trial / Demo (FTD)
     FTD lets buyers validate fit and performance before committing.

102. Return on Investment (ROI)
     ROI measures value versus cost for automation and support improvements.

Advanced / Emerging Concepts

103. Hyperautomation
     Hyperautomation combines AI, automation, and orchestration to streamline end-to-end workflows.

104. Proactive Support / Proactive CX
     Proactive support anticipates needs and reaches out before customers ask, reducing effort and churn.

105. Predictive Support
     Predictive support uses models to forecast issues so teams can intervene early.

106. AI-Driven Insights
     AI-driven insights find patterns in conversations and behaviour to inform product and policy.

107. Behavioural Analytics
     Behavioural analytics studies how users navigate and act to reveal friction and opportunities.

108. Real-Time Sentiment Monitoring
     Real-time monitoring flags frustration or urgency during live interactions for quick coaching or routing.

109. Micro-Moments
     Micro-moments are intent-rich instants when customers want immediate answers on the device at hand.

110. Hyper-Personalization
     Hyper-personalization uses real-time data and AI to tailor one-to-one experiences.

111. AI / Human Hybrid Model
     AI/human hybrid blends automation for routine tasks with human empathy for complex problems.

112. Explainability in AI (XAI)
     XAI makes model decisions understandable for users, auditors, and regulators.

113. Zero-Touch Support
     Zero-touch support aims for fully automated resolution without agent involvement.

114. Agentless Support
     Agentless support relies on bots and self-service at scale, with human backup for edge cases.

115. AI Governance & Oversight
     AI governance sets policies, controls, and review processes for safe, compliant AI.

116. Multimodal Experiences
     Multimodal experiences blend text, voice, and visuals to improve clarity and accessibility.

117. Data Annotation & Labelling
     Annotation and labelling prepare high-quality training data for supervised learning.

118. Transfer Learning
     Transfer learning adapts knowledge from one domain to another to reduce training time.

119. Continuous Learning
     Continuous learning updates models with new data and feedback for sustained accuracy.

120. Voice Biometrics / Authentication
     Voice biometrics verifies identity from speech patterns to reduce friction and fraud.

CX HAPPENS

If you’ve ever nodded through a meeting while quietly Googling “CES vs CSAT,” you’re in excellent company.

Flow Forward

That’s the glossary, read, link, repeat…and may your buzzword bingo cards stay gloriously blank.

FAQ

1. What is a customer experience glossary and why use one?
   A single source of truth for CX, service, and AI chat terminology so teams align on journeys, touchpoints, and metrics.

2. Which CX metrics should we start with?
   CSAT, NPS, CES—plus operational metrics like response time, FRT, resolution time, and FCR. See

3. What’s the difference between metrics and KPIs?
   Metrics describe performance; KPIs are the small set you actively manage.

4. Where do AI chatbots add value first?
   FAQ deflection, sentiment-based triage, and agent assist for speed/consistency.

5. What is a good first response time benchmark?
   Provide near-instant acknowledgement and fast first response; set SLAs by channel and review quarterly.

6. How can CX reduce churn?
   Fix onboarding friction, lower effort, communicate value before renewal, and close the feedback loop.

7. How do we choose AI chatbot software?
   Prioritise governance, analytics, integrations, uptime/SLA, and security; run a task-based pilot before purchase.