Customer Feedback and Sentiment Analysis Training Course

Duration 5 days 10 modules · 33 contact hours
Level Intermediate Certificate on completion
Who attends Customer Experience Managers, Customer Service Managers and others
Fee from USD 1,100 KSh 95,000 for Kenyan organisations
Where 52 cities + online See dates by city
Next start 16 Nov 2026 Course code SD-CS-138

Before you join: Participants should have experience working with customers, service operations, surveys, complaints, market research or customer experience data.

Dates & prices

Two start dates a month in every city, and live online on weekdays or weekends. Fees are per participant; classroom fees include tuition, materials, lunch and refreshments, and the certificate.

Suggest a date or city

Showing the next six months. Later dates, other cities and private deliveries for your team are available on request.

Course overview

Customer feedback programmes often produce large volumes of survey responses, call transcripts, complaint records, reviews and social comments without producing clear service improvements. Teams may report NPS or CSAT scores yet struggle to identify root causes, distinguish urgent issues from noise, or assign accountable owners. Poor sampling, leading questions, inconsistent coding and weak reporting can also create misleading conclusions and costly service decisions.

This course equips participants to design, analyse and act on customer feedback and sentiment data. Participants learn to map feedback sources against the customer journey, build purposeful surveys, select samples, interpret NPS, CSAT and Customer Effort Score results, and apply qualitative coding techniques. The course covers text preparation, sentiment classification, theme analysis, driver analysis, customer segmentation, complaint categorisation and service recovery workflows. Participants also learn to combine quantitative scores with verbatim feedback, operational data and journey-stage evidence.

Teaching combines short instructor briefings with cases drawn from banking, public services, retail, telecommunications and B2B account management. Participants assess example questionnaires, classify customer comments, interpret dashboards, identify root causes and make prioritisation decisions using realistic service data. Each participant leaves with a reusable customer feedback measurement plan, survey design checklist, coding framework, sentiment analysis model and action-tracking structure suitable for adaptation to their own customer environment.

The course is suited to customer experience, service delivery, contact centre, marketing, quality and insight professionals who already work with customer feedback or are responsible for improving how it informs decisions.

What you will be able to do

  • Design a voice-of-customer measurement plan linked to business and service decisions
  • Construct customer surveys using sound question wording, scales and sampling methods
  • Calculate and interpret NPS, CSAT and Customer Effort Score results
  • Code verbatim feedback using a structured thematic and sentiment taxonomy
  • Apply driver analysis to identify factors associated with customer satisfaction and loyalty
  • Segment feedback findings by journey stage, channel, customer group and service issue
  • Develop closed-loop feedback actions with owners, deadlines and escalation criteria
  • Produce an executive feedback dashboard and evidence-based improvement narrative

Benefits of attending

For you

  • Build confidence interpreting NPS, CSAT and effort scores beyond headline reporting
  • Create clearer survey questions that produce decision-ready customer evidence
  • Analyse open-text comments without relying solely on anecdotal reading
  • Present feedback findings with stronger links to operational priorities and customer outcomes
  • Lead structured service improvement conversations with accountable action owners

For your organisation

  • Improves the quality and consistency of customer feedback collected across channels
  • Reduces wasted effort on surveys that do not support decisions or actions
  • Identifies recurring service failures before they become major complaint themes
  • Creates clearer accountability for closing the loop with dissatisfied customers
  • Strengthens investment decisions through evidence on customer priorities and pain points

Course modules

10 modules over 5 days

Participants can define a feedback programme that supports measurable customer and operational decisions.

  • Voice-of-customer programme scope linked to service, retention and revenue decisions
  • Feedback sources mapped across journeys, channels, moments and customer segments
  • Closed-loop and outer-loop feedback processes distinguished for operational accountability
  • Relationship, transactional and event-triggered surveys matched to decision needs
  • Governance roles defined through RACI for collection, analysis and action
  • Privacy, consent and retention requirements assessed before feedback collection

Participants can select appropriate measures, sampling approaches and feedback collection methods.

  • NPS, CSAT and Customer Effort Score matched to measurement objectives
  • Leading and lagging customer indicators separated within measurement frameworks
  • Population, sampling frame and respondent eligibility defined before fieldwork
  • Probability and non-probability sampling methods compared for service feedback
  • Response rate, completion rate and representativeness monitored through fieldwork
  • Nonresponse bias identified through customer profile and channel comparisons

Participants can create clear, unbiased questionnaires that generate usable service evidence.

  • Questionnaire objectives translated into measurable customer experience research questions
  • Double-barrelled, leading and ambiguous questions identified and rewritten
  • Likert, numeric rating and semantic differential scales selected appropriately
  • Question order designed to reduce priming, fatigue and abandonment
  • Open-ended prompts written to capture reasons behind customer scores
  • Cognitive testing and pilot studies used before survey launch

Participants can interpret survey results and identify meaningful patterns in customer scores.

  • NPS calculation separates promoters, passives and detractors using standard rules
  • CSAT results analysed by frequency, percentage, mean and distribution
  • Confidence intervals used to judge meaningful differences between customer groups
  • Cross-tabulation compares feedback across channels, regions, products and segments
  • Trend charts distinguish normal variation from material service performance changes
  • Sample size limitations stated clearly when reporting customer findings

Participants can prepare customer feedback data for reliable analysis and reporting.

  • Duplicate responses, incomplete records and invalid entries identified systematically
  • Data dictionaries document variables, value labels, source systems and definitions
  • Missing data patterns assessed before calculating summary customer metrics
  • Customer identifiers matched across surveys, complaints and operational records
  • Personal data removed or masked before feedback analysis and sharing
  • Quality checks reconcile dashboard figures with underlying survey extracts

Participants can classify customer comments into consistent sentiment, theme and issue categories.

  • Sentiment categories defined as positive, negative, neutral and mixed
  • Codebooks specify theme definitions, inclusion rules and exclusion rules
  • Inductive and deductive coding approaches compared for customer comments
  • Inter-coder agreement checked using sample reviews and coding reconciliation
  • Text cleaning removes duplicates, boilerplate, spelling noise and irrelevant content
  • Keyword frequency interpreted alongside context, negation and customer intent

Participants can identify the service factors most associated with feedback outcomes.

  • Pareto analysis ranks complaint themes by frequency and customer impact
  • Five Whys examines underlying causes behind recurring negative feedback
  • Fishbone diagrams organise people, process, policy, technology and environment causes
  • Driver analysis links satisfaction scores with specific service experience attributes
  • Journey-stage analysis identifies where customer effort and dissatisfaction arise
  • Severity and frequency matrices prioritise issues requiring immediate intervention

Participants can design response processes for dissatisfied customers and recurring service failures.

  • Detractor alerts routed using severity, vulnerability and escalation criteria
  • Service recovery standards define acknowledgement, investigation, remedy and follow-up
  • Complaint handling aligned with ISO 10002 principles and internal policies
  • Case ownership assigned with response deadlines and manager escalation points
  • Root-cause actions separated from individual customer recovery actions
  • Closed-loop records capture contact outcome, remedy and unresolved risk

Participants can communicate feedback insights clearly to operational and executive audiences.

  • Executive dashboards combine headline scores, drivers, themes and action status
  • Data visualisation selects charts suited to comparisons, trends and distributions
  • Verbatim comments curated to illustrate themes without anecdotal distortion
  • Insight narratives distinguish observation, interpretation, recommendation and decision required
  • Performance thresholds flag deteriorating experience measures and priority service issues
  • Reporting cadence matched to operational reviews, governance meetings and planning cycles

Participants can prepare a practical plan for improving their own feedback and sentiment process.

  • Current-state assessment identifies gaps in collection, analysis, action and governance
  • Improvement backlog prioritised using impact, effort, risk and customer urgency
  • Ninety-day action plans assign milestones, owners, measures and review dates
  • Pilot designs test revised surveys, taxonomies and recovery workflows
  • Success measures link feedback improvements to operational and customer outcomes
  • Stakeholder communication plans secure support for changed feedback processes

Exercises and examples are adapted to each cohort's sectors and roles.

What you take back to work

  1. Voice-of-customer measurement plan template
  2. Customer survey design checklist
  3. Verbatim feedback coding framework
  4. Sentiment and theme taxonomy
  5. Closed-loop service recovery workflow
  6. Customer feedback dashboard specification

Who should attend

  • Customer Experience Managers — need reliable evidence to prioritise journey and service improvements
  • Customer Service Managers — need to convert complaints and survey findings into operational actions
  • Market Research and Insight Analysts — need stronger methods for analysing structured and unstructured feedback
  • Contact Centre Managers — need to identify recurring call drivers and recovery opportunities
  • Marketing Managers — need customer evidence to improve communications, offers and retention activity
  • Quality Assurance Managers — need consistent feedback taxonomies and reporting for service performance

Skills and tools covered

Voice-of-customer designSurvey methodologySentiment codingDriver analysisService recoveryFeedback reporting

Tools and standards

Net Promoter Score, Customer Satisfaction Score, Customer Effort Score, ISO 10002

How the course runs

Training methodology

The course uses short briefings to introduce feedback measurement, survey design, sentiment analysis and reporting methods. Participants work with realistic survey datasets, customer comments, complaint records and service scenarios. Group exercises focus on questionnaire critique, coding consistency, root-cause identification, prioritisation and action ownership. Simulations examine how teams respond to detractor feedback and escalating complaints. Facilitated discussion connects each method to participants' own channels, customer journeys and reporting requirements. The final sessions support practical application planning.

Requirements and prerequisites

Participants should have experience working with customers, service operations, surveys, complaints, market research or customer experience data. Familiarity with basic spreadsheet functions, percentages, averages and charts is useful because the course includes interpretation of survey scores and feedback reports. Participants should understand their organisation's main customer channels and service processes. Prior statistical training, programming, specialist text analytics software or research qualifications are not required. The course explains core analytical concepts before applying them to feedback and sentiment cases.

A typical training day

08:30 – 10:30First session
10:30 – 10:45Refreshment break
10:45 – 12:30Second session
12:30 – 13:30Lunch and networking
13:30 – 15:00Third session
15:00 – 15:15Refreshment break
15:15 – 16:30Workshop and daily review

Live online deliveries follow the same structure in East Africa Time, with shorter screen blocks and longer breaks.

What the fee includes

  • Instruction by a practitioner facilitator
  • Full course workbook and materials
  • Exercise files, templates and case studies
  • Refreshments and lunch on classroom deliveries
  • Certificate of completion
  • Post-course application plan

Frequently asked questions

Participants should understand basic customer service, marketing, research or operational processes and be comfortable reading simple charts and percentages. Specialist statistics, programming and text analytics software experience are not required.

Participants may bring examples of existing surveys, feedback reports, complaint categories or customer journey maps, subject to their organisation's confidentiality rules. A laptop is useful for reviewing course materials and working with data examples.

The course is designed for professionals responsible for customer feedback, customer experience, service quality, contact centres, insight, marketing or complaint handling. It is particularly useful for teams seeking more discipline in turning feedback into operational action.

General customer service courses focus on frontline interactions, communication and service standards. This course focuses on measuring customer views, analysing feedback data, identifying causes and managing improvement actions.

Participants can review their current survey design, refine feedback categories, improve dashboard reporting and create clearer recovery workflows. The templates and planning tools can be adapted to existing customer channels and governance meetings.

The five days cover programme design, survey methodology, quantitative analysis, sentiment coding, root-cause analysis, recovery processes, reporting and improvement planning. Each training day runs from 08:30 to 16:30 and provides about 6.5 contact hours.

Questions about this course?

Ask about dates, fees, group bookings or running it for your team. Our training team replies by email.

Ask on WhatsApp info@skillsetdevelopment.com

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