Customer Insights and CRM Training Course

Duration 5 days 10 modules · 33 contact hours
Level Intermediate Certificate on completion
Who attends CRM Managers, Marketing 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-M-041

Before you join: Participants should understand basic marketing, sales or customer service processes and have experience working with customer records, campaign reports, sales data or service metrics.

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 data is often distributed across CRM records, sales pipelines, service cases, campaign platforms, transaction systems and feedback channels. Teams may hold large volumes of information but still struggle to identify profitable segments, detect churn risk, target communications appropriately or connect customer experience issues to commercial outcomes. This course addresses the practical work required to turn customer data into decisions, treatments and measurable CRM activity.

Participants learn how to assess customer-data quality, define usable customer records, build actionable segments and interpret behavioural, transactional and journey data. The course covers RFM analysis, cohort analysis, customer lifetime value, churn indicators, voice-of-customer coding, journey mapping, campaign measurement and CRM dashboard design. Participants also examine lead management, account planning, service recovery, consent management, GDPR requirements and data ethics.

Teaching combines short instructor briefings with sector-based cases from banking, retail, telecommunications, B2B sales and public services. Participants work with realistic customer-data scenarios, interpret reports, design CRM rules and prepare decisions for management review. They leave with a reusable customer insight and CRM action pack containing analysis templates, segment profiles, measurement plans and a 90-day implementation plan.

The course suits marketing, sales, customer experience, service and analytics professionals who already work with customer information and need a more disciplined method for converting it into revenue, retention and service improvements.

What you will be able to do

  • Assess customer-data quality using documented profiling and validation rules
  • Build actionable customer segments using RFM, behavioural and needs-based methods
  • Interpret cohort, funnel and cross-tabulation analyses for commercial decisions
  • Calculate customer lifetime value and prioritise retention interventions
  • Map customer journeys and identify high-impact moments of truth
  • Design consent-aware CRM campaigns using triggers, contact policies and test controls
  • Specify CRM dashboards, data definitions and performance measures
  • Prepare a 90-day customer insight and CRM implementation plan

Benefits of attending

For you

  • Produce defensible customer insight briefs for marketing and sales decisions
  • Prioritise customer segments using value, behaviour and retention risk
  • Translate CRM reports into specific campaign, service and sales actions
  • Design customer journey improvements supported by evidence and measures
  • Contribute credibly to CRM data, consent and governance discussions

For your organisation

  • Improves targeting accuracy through defined segments and usable customer records
  • Reduces avoidable churn through earlier identification of retention risks
  • Strengthens campaign accountability using test controls and incremental measures
  • Connects customer feedback with operational root causes and ownership
  • Creates common CRM definitions across marketing, sales and service teams

Course modules

10 modules over 5 days

Participants can assess whether customer data is fit for analysis, targeting and CRM activity.

  • Customer data sources, identifiers and grain assessed before analytical use
  • First-party, second-party and third-party data distinguished by consent and control
  • Customer master records matched using deterministic and probabilistic identity resolution
  • Data dictionaries document fields, definitions, owners, refresh cycles and permitted uses
  • Completeness, validity, uniqueness, timeliness and accuracy tested through data-quality rules
  • Duplicate records, missing values and outliers treated with documented decision rules

Participants can define CRM processes, ownership and data requirements around customer lifecycle goals.

  • CRM operating model links strategy, processes, data, technology and governance
  • Lifecycle stages defined from prospect acquisition through retention, recovery and advocacy
  • Service-level agreements align marketing, sales and service handoffs
  • Lead, contact, account and opportunity objects configured around business processes
  • Required fields and validation rules improve record completeness at capture
  • Data stewardship roles assign accountability for customer-data decisions and remediation

Participants can create actionable segments and profile the customers within them.

  • Segmentation objectives tied to growth, retention, cross-sell and service priorities
  • RFM scoring ranks recency, frequency and monetary value using observed transactions
  • Behavioural segments combine product usage, channel preference and engagement signals
  • Needs-based segmentation separates customer motivations from demographic descriptors
  • Cluster-analysis outputs tested for stability, interpretability, size and actionability
  • Segment profiles specify value, needs, barriers, triggers and preferred treatment

Participants can interpret core customer analyses and frame evidence-based recommendations.

  • Descriptive, diagnostic, predictive and prescriptive analytics matched to business questions
  • Cross-tabulations expose differences by segment, channel, product and tenure
  • Cohort analysis tracks acquisition groups through activation, repeat purchase and churn
  • Funnel analysis quantifies conversion losses between defined customer journey stages
  • Correlation, confounding and causation distinguished before recommending commercial action
  • Insight statements separate evidence, interpretation, implication and recommended decision

Participants can prioritise retention and growth actions using customer value and risk indicators.

  • Customer lifetime value estimated from margin, retention, frequency and acquisition cost
  • Retention cohorts reveal survival patterns, renewal risk and intervention windows
  • Churn definitions distinguish voluntary, involuntary, partial and predicted attrition
  • Propensity scores prioritise customers for retention, upgrade or cross-sell treatment
  • Uplift thinking separates customers persuaded by offers from inevitable responders
  • Next-best-action rules balance expected value, customer need and contact pressure

Participants can identify priority journey improvements from customer feedback and operational evidence.

  • Journey maps connect customer goals, touchpoints, emotions, friction and backstage processes
  • Moments of truth prioritised using customer effort, value and failure impact
  • Voice-of-customer data coded from surveys, complaints, calls and digital feedback
  • Closed-loop feedback processes route issues, owners, deadlines and customer responses
  • Root-cause analysis uses five whys and fishbone diagrams for recurring failures
  • Journey metrics link NPS, CSAT, CES and operational performance measures

Participants can design targeted, permission-based CRM communications and measure their results.

  • Campaign objectives translated into audiences, propositions, channels, timings and metrics
  • Consent status and preference-centre choices govern addressable contact populations
  • Trigger-based journeys respond to events, thresholds, behaviours and lifecycle changes
  • Personalisation rules use declared, observed and inferred data within permissions
  • Contact policies manage frequency caps, suppression rules and channel conflicts
  • Test-and-control designs measure incremental response, conversion and commercial value

Participants can apply CRM data to lead conversion, account management and service recovery.

  • Lead-scoring criteria combine fit, intent, engagement and sales-readiness signals
  • Pipeline stages, exit criteria and ageing rules support forecast discipline
  • Account plans identify stakeholders, whitespace, risks, opportunities and next actions
  • Case categorisation reveals recurring issues, priority levels and resolution performance
  • Service recovery workflows specify escalation paths, ownership and communication standards
  • CRM dashboards show activity, conversion, retention and customer-health measures

Participants can apply practical privacy, access and ethical controls to CRM activity.

  • Lawful basis, purpose limitation and data minimisation guide customer-data collection
  • GDPR rights handling covers access, rectification, erasure, portability and objection
  • Consent records capture purpose, channel, timestamp, source and withdrawal status
  • Retention schedules distinguish active records, archives and defensible deletion
  • Role-based access controls restrict sensitive customer data by job requirement
  • Data ethics reviews assess fairness, intrusiveness, explainability and foreseeable harm

Participants can prioritise CRM improvements and prepare an accountable 90-day action plan.

  • Insight backlogs prioritise initiatives by value, effort, risk and data readiness
  • Measurement plans define baselines, targets, owners, cadence and decision thresholds
  • Pilot charters state hypothesis, audience, treatment, controls and success criteria
  • Dashboard specifications connect metrics, data sources, calculations and intended decisions
  • CRM adoption plans address process change, training, reinforcement and accountability
  • 90-day action plans sequence quick wins, dependencies, milestones and reviews

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

What you take back to work

  1. Customer-data quality assessment checklist
  2. RFM segmentation and customer-profile template
  3. Customer lifetime value and retention-priority model
  4. Customer journey and voice-of-customer analysis template
  5. CRM campaign measurement plan
  6. 90-day customer insight implementation plan

Who should attend

  • CRM Managers — responsible for converting customer records into targeted treatments and measurable activity
  • Marketing Managers — need evidence-based segments, campaign audiences and response measures
  • Customer Experience Managers — need to connect journey evidence with operational improvements
  • Sales Managers — need stronger lead prioritisation, pipeline discipline and account insight
  • Customer Insights Analysts — need structured methods for producing commercially useful analysis
  • Customer Service Managers — need case data and feedback analysis to improve retention

Skills and tools covered

Customer segmentationCRM data governanceCustomer lifetime valueJourney mappingCampaign measurementCRM performance reporting

Tools and standards

RFM analysis, Customer lifetime value, Customer journey mapping, GDPR

How the course runs

Training methodology

The course uses short instructor briefings followed by guided analysis of realistic customer-data cases. Participants interpret transaction, campaign, pipeline, service and feedback data; build segment logic; assess journey evidence; and make decisions from dashboards. Small-group work examines CRM scenarios such as declining retention, poor lead conversion and recurring service failures. Facilitated discussions compare alternative treatments, contact rules and performance measures. Each participant develops an application plan using their own customer, CRM or campaign context where suitable.

Requirements and prerequisites

Participants should understand basic marketing, sales or customer service processes and have experience working with customer records, campaign reports, sales data or service metrics. Familiarity with spreadsheet functions such as filtering, sorting and simple calculations is useful. Participants should be able to discuss their organisation's customer lifecycle, main channels and available data sources. Prior statistical training, coding, database administration or CRM system configuration experience is not required. The course explains analytical concepts without assuming advanced mathematics or specialist data-science knowledge.

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

You should be familiar with basic marketing, sales, service or customer experience processes and have worked with customer information or reports. Advanced analytics, coding and CRM administration experience are not required.

Bring a laptop if possible, along with examples of customer reports, segment definitions, campaign measures or CRM challenges from your role. Do not bring identifiable customer data, confidential exports or restricted records.

The course is designed for CRM, marketing, sales, customer experience, service and customer insight professionals. It is particularly useful for people expected to turn customer data into actions, priorities and performance measures.

This course focuses on customer insight methods, decision rules, data governance and commercial applications rather than button-by-button training in one software product. The methods can be applied in Salesforce, Microsoft Dynamics, HubSpot, Oracle CX and other CRM environments.

You can use the templates to assess data quality, build segments, investigate churn, improve customer journeys and specify campaign measures. The 90-day action plan helps convert findings into owned initiatives with targets and review points.

The five 08:30-16:30 training days provide about 32.5 contact hours. Ten teaching modules occupy roughly 30 hours, with remaining time used for case discussion, group analysis, reflection and application planning.

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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