Customer Engagement Strategy Training Course

Participants can identify priority customer groups and define their needs using validated evidence.

• Segmentation combines behavioural, needs-based, value and lifecycle variables
• Jobs to Be Done captures customer progress, motivations and barriers
• Persona evidence separates validated insight from assumptions and stereotypes
• Priority segments assessed using attractiveness, accessibility, fit and serviceability criteria
• Moments that matter identified by emotional stakes and commercial consequences
• Segment needs converted into differentiated engagement objectives and propositions

Participants can map customer journeys and locate high-value improvement opportunities.

• Current-state journey maps capture stages, actions, emotions, channels and ownership
• Swimlane mapping exposes handoffs between marketing, sales, service and operations
• Journey evidence combines CRM records, call reasons, web analytics and observation
• Pain points prioritised through frequency, severity, effort and revenue impact
• Service blueprints connect frontstage interactions with backstage processes and systems
• Future-state journeys specify target experiences, controls, owners and measures

Participants can create relevant propositions and communications for each engagement stage.

• Value propositions match segment jobs, pains, gains and proof points
• Message hierarchies organise primary promise, supporting evidence and calls-to-action
• Content mapping assigns formats and messages to journey-stage information needs
• Behavioural science applies reciprocity, social proof, loss aversion and defaults
• Plain-language writing reduces cognitive load and service misunderstanding
• Accessibility checks address readable content, inclusive language and usable formats
• Consent-based personalisation balances relevance, data permissions and customer expectations

Participants can define channel roles and design consistent interactions across touchpoints.

• Channel roles defined by customer intent, complexity, urgency and preference
• Omnichannel orchestration maintains context across digital, telephone and face-to-face contacts
• Conversation design uses opening, discovery, resolution, confirmation and next-step techniques
• Service standards specify response times, tone, escalation and ownership
• Proactive communications prevent avoidable contacts through timely status and guidance
• Channel migration identifies suitable self-service journeys without forcing vulnerable customers
• Quality monitoring samples contacts against defined interaction criteria and coaching

Participants can design fair service recovery processes and reduce recurring service failures.

• Complaint journeys distinguish dissatisfaction, failure, vulnerability and formal complaint stages
• HEARD method structures hear, empathise, apologise, resolve, diagnose responses
• Recovery decisions align remedy authority, fairness, precedent and customer value
• Root-cause analysis uses five whys, Pareto charts and failure categories
• Closed-loop complaint handling confirms resolution, learning and follow-up ownership
• Vulnerable customer indicators trigger appropriate adjustments, support and escalation
• Recovery metrics track repeat contacts, resolution time, satisfaction and preventable failures

Participants can establish a measurement system that converts customer feedback into action.

• Voice of the Customer programmes combine solicited, behavioural and unsolicited feedback
• Survey design controls sampling, question wording, scale choice and timing
• NPS, CSAT and Customer Effort Score serve distinct decisions
• Text coding converts comments into themes, sentiment, causes and owners
• Closed-loop feedback processes assign response thresholds, actions and accountability
• Driver analysis separates correlation, causation, sample bias and confounding factors
• Executive dashboards connect experience indicators to retention, revenue and cost

Participants can specify the data, consent and automation controls needed for customer engagement.

• CRM data models unify customer profiles, interactions, permissions and cases
• Data-quality rules address duplicates, missing fields, outdated records and validation
• Consent management applies purpose limitation, preference capture and suppression rules
• Event-triggered journeys respond to onboarding, abandonment, renewal and service milestones
• Decision rules select next-best actions using eligibility, propensity and risk
• Automation boundaries retain human review for sensitive or complex cases
• Measurement tags link campaign exposures, responses, conversions and downstream outcomes

Participants can assign ownership, governance and adoption actions for an engagement programme.

• Operating models allocate journey ownership, channel accountability and decision rights
• RACI matrices clarify responsibilities for design, delivery, approval and escalation
• Service-level agreements define handoffs, response commitments, exceptions and reporting
• Frontline feedback routines turn recurring issues into improvement priorities
• Governance cadences review customer outcomes, risks, experiments and investment decisions
• Change plans address sponsor roles, capability gaps, communications and adoption measures
• Ethical review tests fairness, transparency, privacy and unintended customer harm

Participants can create a prioritised implementation plan for sustained customer engagement improvement.

• Opportunity backlogs rank improvements by impact, effort, confidence and dependencies
• SMART objectives translate engagement priorities into measurable quarterly outcomes
• Test-and-learn plans define hypotheses, segments, controls, metrics and decision rules
• Experiment design distinguishes A/B tests, pilots, phased releases and holdouts
• Implementation roadmaps sequence quick wins, foundational work, owners and milestones
• Risk registers document operational, conduct, data and reputational exposures
• Personal application plans commit first actions, stakeholders, measures and review dates