Contact Centre Analytics and Customer Experience Intelligence Training Course

Course Introduction

Contact Centre Analytics and Customer Experience Intelligence Training Course is designed to equip professionals with advanced knowledge and practical capabilities for transforming contact centre data into meaningful customer and operational insights. Modern contact centres generate large volumes of interaction data from voice calls, emails, chat, social media, messaging platforms, CRM systems, surveys, and digital channels. The course provides a structured approach to collecting, integrating, analysing, visualising, and interpreting this information to support evidence-based service improvement and customer-centric decision-making.

The course explores how contact centre analytics can move organizations beyond basic performance reporting toward deeper understanding of customer behaviour, service quality, agent performance, operational efficiency, and customer experience outcomes. Participants will examine key contact centre metrics such as average handling time, first contact resolution, service level, abandonment rate, queue performance, customer satisfaction, customer effort, and Net Promoter Score. They will learn how to connect these measures to broader customer journeys and organizational objectives rather than treating operational metrics in isolation.

A major focus of the training is customer experience intelligence and the integration of information from multiple customer touchpoints. Participants will learn how to combine contact centre records with CRM information, customer feedback, digital interactions, transactional data, surveys, and other relevant sources to develop richer customer profiles. The course will introduce customer journey analytics, segmentation, voice-of-customer analysis, sentiment analysis, text analytics, and root-cause analysis as approaches for identifying customer pain points, service gaps, emerging trends, and opportunities for experience improvement.

The training also develops practical skills in analytics-driven reporting and visualization. Participants will explore how to design meaningful dashboards that provide operational teams, supervisors, managers, and executives with relevant and actionable information. Rather than simply presenting large volumes of statistics, the course emphasizes selecting appropriate KPIs, identifying relationships between measures, recognizing trends and anomalies, and communicating insights in ways that support timely decisions. Dashboard design, data storytelling, interactive reporting, automated reporting, and executive intelligence will therefore form important components of the programme.

Advanced analytics and artificial intelligence are also incorporated into the course to reflect the changing contact centre environment. Participants will examine predictive analytics for forecasting customer demand, identifying potential churn, anticipating service issues, and supporting workforce planning. They will also explore conversational AI, intelligent virtual assistants, speech and text analytics, automated quality monitoring, sentiment detection, generative AI, recommendation systems, and AI-assisted agent support. The course addresses the opportunities and limitations of these technologies, including data quality, privacy, transparency, bias, security, and responsible AI considerations.

By the end of the programme, participants will be able to establish stronger analytical approaches for understanding customer interactions, measuring service performance, identifying experience drivers, and supporting continuous improvement. They will be better prepared to translate contact centre data into customer experience intelligence, connect operational performance with business outcomes, and develop practical recommendations based on evidence. The course is particularly valuable for organizations seeking to strengthen customer loyalty, improve service efficiency, enhance employee and agent performance, reduce avoidable customer effort, and build more intelligent and responsive customer service operations.

Duration

10 days

Who Should Attend

• Contact Centre Managers and Operations Managers

• Customer Experience Managers and CX Professionals

• Customer Service Managers and Supervisors

• Contact Centre Workforce Management Professionals

• Quality Assurance and Quality Monitoring Specialists

• Business Intelligence and Data Analytics Professionals

• Customer Insights and Consumer Research Specialists

• CRM Managers and Customer Relationship Professionals

• Digital Transformation and Innovation Managers

• Service Performance and Operational Excellence Professionals

• Customer Success and Customer Retention Teams

• Marketing and Customer Intelligence Professionals

• Data Scientists and Business Analysts

• IT Professionals Supporting Contact Centre Systems

• Team Leaders and Contact Centre Supervisors

• Voice of Customer and Customer Feedback Specialists

• Service Designers and Customer Journey Professionals

• Business Managers Responsible for Customer-Centric Operations

Course Objectives

• Understand the principles of contact centre analytics and how analytical intelligence can improve operational performance and customer experience outcomes.

• Identify, calculate, interpret, and apply critical contact centre performance indicators for monitoring service quality, efficiency, productivity, and customer satisfaction.

• Integrate contact centre data with CRM, customer feedback, digital interaction, transactional, and operational data to create comprehensive customer intelligence.

• Analyse customer journeys and interactions across multiple channels to identify friction points, service gaps, bottlenecks, and opportunities for experience improvement.

• Apply segmentation and behavioural analytics techniques to understand different customer groups, interaction patterns, preferences, needs, and service expectations.

• Use Voice of the Customer methodologies to collect, structure, analyse, and translate customer feedback into measurable service and experience improvements.

• Apply sentiment, speech, text, and conversation analytics techniques to identify customer emotions, recurring issues, service drivers, and emerging customer concerns.

• Design interactive contact centre dashboards and reports that communicate relevant operational and customer experience information to different management levels.

• Apply predictive analytics and forecasting techniques to anticipate contact volumes, customer behaviour, service demand, churn risks, and potential operational challenges.

• Evaluate artificial intelligence and automation applications for contact centre analytics, including conversational AI, intelligent assistants, automated quality monitoring, and generative AI.

• Develop data-driven approaches for improving agent performance, workforce utilization, service quality, first-contact resolution, customer satisfaction, and overall operational effectiveness.

• Establish responsible customer analytics practices covering data quality, privacy, security, governance, ethical AI, transparency, and appropriate use of customer information.

Comprehensive Course Outline

Module 1: Foundations Of Contact Centre Analytics

• Introduction to modern contact centre analytics and its role in data-driven service management

• Evolution from traditional call reporting toward integrated customer and operational intelligence

• Understanding contact centre data ecosystems, analytical processes, and information flows

• Linking contact centre analytics with organizational strategy, service objectives, and customer outcomes

Module 2: Contact Centre Data Sources And Data Architecture

• Identifying voice, chat, email, CRM, social media, survey, transactional, and digital interaction data sources

• Understanding structured, semi-structured, and unstructured contact centre data and their analytical applications

• Integrating data from multiple systems while addressing duplication, inconsistencies, and information silos

• Designing scalable data architectures that support operational reporting, customer intelligence, and advanced analytics

Module 3: Contact Centre Metrics And Performance Intelligence

• Understanding service level, average handling time, abandonment rate, occupancy, utilization, and queue performance

• Measuring first contact resolution, transfer rates, repeat contacts, response times, and escalation patterns

• Connecting operational KPIs with customer satisfaction, customer effort, loyalty, and broader business outcomes

• Developing balanced performance frameworks that avoid focusing on individual metrics without considering customer impact

Module 4: Customer Experience Measurement And Intelligence

• Understanding customer experience intelligence and its relationship with contact centre performance

• Measuring CSAT, NPS, CES, retention, loyalty, complaint rates, and other customer experience indicators

• Identifying experience drivers and determining which service factors influence customer perceptions and outcomes

• Developing analytical frameworks for connecting operational performance with customer experience results

Module 5: Customer Journey And Interaction Analytics

• Mapping end-to-end customer journeys across contact centres, websites, applications, branches, and digital channels

• Analysing customer touchpoints, handovers, delays, drop-offs, friction points, and moments that influence experience

• Using interaction data to identify recurring journey problems and opportunities for service redesign

• Applying journey analytics to improve consistency, convenience, personalization, and customer effort

Module 6: Voice Of The Customer And Feedback Analytics

• Designing Voice of the Customer programmes for collecting structured and unstructured customer feedback

• Analysing surveys, complaints, reviews, contact transcripts, social comments, and other feedback sources

• Combining qualitative customer comments with quantitative performance data to strengthen customer intelligence

• Establishing closed-loop feedback processes that convert customer insights into measurable improvement actions

Module 7: Customer Segmentation And Behavioural Analytics

• Developing meaningful customer segments using demographic, behavioural, transactional, and interaction information

• Analysing contact behaviour, channel preferences, frequency patterns, service needs, and customer value

• Identifying high-value, high-effort, vulnerable, dissatisfied, loyal, and potentially at-risk customer groups

• Applying segmentation insights to improve personalization, service prioritization, retention, and customer engagement

Module 8: Speech, Text And Sentiment Analytics

• Understanding speech analytics, text analytics, natural language processing, and their contact centre applications

• Analysing conversations and written interactions to identify topics, intent, sentiment, emotions, and recurring issues

• Detecting emerging complaints, service failures, compliance risks, and customer concerns through interaction analytics

• Using conversation intelligence to support coaching, quality monitoring, knowledge improvement, and service optimization

Module 9: Contact Centre Dashboards And Data Visualization

• Designing operational dashboards for real-time monitoring of service performance and customer experience indicators

• Developing management dashboards that combine contact centre, customer, agent, and business performance information

• Applying data visualization principles to communicate trends, anomalies, relationships, and actionable insights clearly

• Using tools such as Power BI and other business intelligence platforms for interactive contact centre reporting

Module 10: Workforce And Operational Analytics

• Analysing contact volumes, arrival patterns, staffing requirements, occupancy, schedules, and workforce utilization

• Using historical data to support demand forecasting, capacity planning, scheduling, and resource allocation

• Identifying relationships between staffing levels, waiting times, service quality, and customer satisfaction

• Applying workforce intelligence to improve operational resilience while maintaining appropriate service standards

Module 11: Predictive Analytics And Customer Risk Intelligence

• Introducing predictive analytics techniques for forecasting customer and contact centre behaviour

• Developing models for customer churn, repeat contact, escalation risk, satisfaction, and service demand

• Identifying early warning indicators that can support proactive intervention before customer problems escalate

• Evaluating predictive model outputs and translating forecasts into practical operational and customer experience actions

Module 12: Artificial Intelligence And Intelligent Contact Centres

• Exploring AI applications including conversational AI, virtual agents, intelligent routing, and agent-assistance technologies

• Understanding generative AI applications for knowledge retrieval, interaction summaries, response assistance, and service workflows

• Applying machine learning to customer segmentation, forecasting, personalization, recommendation, and service optimization

• Evaluating AI opportunities alongside accuracy, transparency, human oversight, security, privacy, and responsible-use considerations

Module 13: Quality Assurance And Agent Performance Analytics

• Using analytics to evaluate agent performance, interaction quality, adherence, productivity, and customer outcomes

• Applying automated quality monitoring and interaction analytics to expand coverage beyond manual call evaluations

• Identifying coaching opportunities through patterns in customer interactions, escalations, transfers, and resolution outcomes

• Balancing productivity measurements with service quality, customer satisfaction, employee experience, and sustainable performance

Module 14: Omnichannel And Digital Customer Experience Analytics

• Analysing customer interactions across voice, email, live chat, messaging, social media, mobile applications, and web channels

• Measuring channel performance, channel switching, digital adoption, self-service success, and assisted-service demand

• Identifying customer journeys that move between automated and human-assisted service environments

• Using omnichannel intelligence to improve consistency, accessibility, personalization, and seamless customer experiences

Module 15: Analytics Governance, Privacy And Responsible Intelligence

• Establishing data governance frameworks for accurate, reliable, secure, and accountable contact centre analytics

• Addressing customer privacy, consent, access controls, retention, security, and responsible handling of interaction data

• Identifying ethical risks associated with automated decision-making, profiling, sentiment analysis, and artificial intelligence

• Developing governance practices that support trustworthy analytics while enabling useful customer and operational insights

Module 16: Emerging Trends And Future Of Customer Experience Intelligence

• Exploring real-time experience intelligence, predictive service management, and increasingly automated customer operations

• Examining generative AI, agentic AI, intelligent copilots, autonomous workflows, and next-generation conversational experiences

• Understanding the growth of customer data platforms, unified customer profiles, journey orchestration, and real-time personalization

• Developing future-ready strategies for integrating analytics, AI, automation, human expertise, and continuous customer experience improvement

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: training@upskilldevelopment.com Tel: +254 721 331 808

Training Venue 

The training will be held at our Upskill Training Centre. We also offer training for a group (at a discount of 10% to 50%) at requested location all over the world. The Onsite course fee covers the course tuition, training materials, two break refreshments, buffet lunch, airport transfers, Upskill gift package, and guided tour.

Visa application, travel expenses, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Upskill certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: training@upskilldevelopment.com, +254 721 331 808

Terms of Payment:

Unless otherwise agreed between the two parties’ payment of the course fee should be done 3 working days before commencement of the training so as to enable us to prepare better.