Data and Analytics for Customer Service & Experience Training Course

Customer experience decisions are too often made on anecdote: the latest escalated complaint, a manager's impression or a single month's dip in satisfaction. Meanwhile the evidence needed to make better decisions sits unused in contact centre platforms, CRM systems, survey tools and social media channels, rarely joined together or analysed beyond simple averages.

The Data and Analytics for Customer Service & Experience Training Course gives service professionals practical analytical skills applied to their own field. It starts with the service data landscape, data quality and the correct definition of core metrics. Participants then build a clean, linked dataset and explore it with pivot tables and visualisation before moving to statistical methods: sampling and margins of error for survey scores, key driver modelling, and simple A/B comparisons for service changes. Further labs cover unstructured feedback, using sentiment scoring and topic coding, and predictive questions such as which customers are likely to leave and how many contacts to expect next week. Data protection and ethical use of customer data are addressed throughout.

Every session is a lab using anonymised service datasets in Excel and Power BI, with optional Python and pandas examples for those who code. Participants finish with a working dashboard and an insight briefing.

On completing the course, participants will be able to:

• Identify, extract and combine service data from CRM, ticketing, telephony and survey systems.
• Clean and structure customer data in Excel and Power Query for reliable analysis.
• Calculate NPS, CSAT, customer effort score, first contact resolution and handle time consistently.
• Test whether changes in service scores are statistically meaningful.
• Use correlation and regression to identify the drivers of satisfaction and loyalty.
• Analyse complaint text and verbatim comments with sentiment scoring and topic coding.
• Forecast contact volumes and identify customers at risk of churn.
• Design Power BI dashboards and insight briefings that prompt action.

The course suits professionals who produce, interpret or act on service data, including:

• Customer experience and customer insight analysts
• Contact centre managers and workforce planners
• Quality assurance and complaints analysis leads
• CRM administrators and business intelligence officers
• Customer service managers who want to read data critically
• Marketing and retention analysts working with customer data
• Service performance officers in utilities, health and government agencies
• Digital channel managers tracking chat, app and self-service usage

Each participant leaves with:

• A cleaned, linked service dataset and a documented data preparation routine in Power Query.
• A metric definitions sheet that ends disputes over how scores are calculated.
• A key driver analysis showing which service attributes most affect satisfaction.
• A coding frame for classifying complaints and verbatim feedback.
• A contact volume forecast with staffing estimates from an Erlang C calculator.
• A churn-risk view built from customer behaviour data.
• A working Power BI service dashboard and a one-page insight briefing.

Learning is hands-on from the first morning, with each concept practised on data. The course uses:

• Computer labs in Excel, Power Query and Power BI using anonymised service datasets
• Guided walkthroughs followed by independent analysis tasks
• Optional Python and pandas notebooks for participants with coding experience
• Group interpretation sessions where teams explain findings to a mock management panel
• Clinics on participants' own metrics and reporting problems

Participants who attend every lab and complete the analysis exercises receive a CPD-accredited Certificate of Completion issued by Vision Reach Global Consultancy.

The dashboard, driver analysis and insight briefing produced in class can be kept as a portfolio of applied analytics work, useful when discussing new responsibilities or projects with managers.