Conversational Marketing Training Course

Participants can prioritise conversation opportunities using customer evidence and business value.

• Jobs-to-be-Done interviews distinguish functional, emotional and social conversation drivers
• Persona evidence drawn from CRM records, web analytics and call transcripts
• Intent taxonomy separates informational, transactional, support and escalation requests
• Conversation entry points mapped against funnel stages and customer moments
• Priority use cases scored by volume, value, feasibility and risk
• Success hypotheses linked to measurable customer and commercial outcomes

Participants can write clear, on-brand conversational content for customer journeys.

• Brand voice principles translated into concise conversational writing rules
• Plain-language microcopy reduces ambiguity in questions, confirmations and error messages
• Progressive disclosure sequences information according to stated intent and readiness
• Choice architecture limits options while preserving customer control and clarity
• Accessibility requirements cover readable language, keyboard access and screen-reader labels
• Localization decisions address dialect, date formats, currency and cultural conventions

Participants can create usable language models for customer-facing conversational assistants.

• User utterances collected from search queries, chat logs and sales calls
• Intent definitions specify customer goals, inclusion rules and exclusions
• Entity models capture products, locations, dates, amounts and identifiers
• Training phrases represent natural language variation without duplicating identical examples
• Fallback design distinguishes unknown intent, low confidence and out-of-scope requests
• Disambiguation questions resolve competing intents with minimal customer effort

Participants can design end-to-end conversation flows for qualification, service and conversion.

• Happy-path flows guide qualification, recommendation, booking and purchase conversations
• Decision trees model branches, conditions, exceptions and recovery paths
• Slot-filling sequences collect required data with validation and confirmation
• State diagrams document context, transitions, memory and conversation termination
• Escalation rules route customers to agents with transcript and intent context
• Wireframes specify messages, buttons, rich media and input controls

Participants can select appropriate chatbot technology and specify a testable prototype.

• Platform selection compares NLP capability, channels, integrations, governance and pricing
• Dialogflow CX agents structured through flows, pages, intents and parameters
• Microsoft Copilot Studio topics configured with triggers, variables and escalation
• WhatsApp Business Platform templates planned for approved outbound message categories
• Webhook patterns connect conversation events to CRM and marketing systems
• Prototype acceptance criteria define intended behavior, content and handoff conditions

Participants can test conversational journeys systematically before launch and after release.

• Test scripts cover happy paths, edge cases, failures and escalation scenarios
• Scenario matrices combine customer intent, channel, device, language and customer status
• Acceptance testing validates responses, data capture, routing and completion outcomes
• Error-message reviews assess recovery guidance, tone and available customer options
• Accessibility testing checks keyboard interaction, readable labels and screen-reader support
• Transcript sampling identifies misunderstood questions, repeated failures and abandoned flows

Participants can design effective transitions between automated conversations and human support.

• Escalation thresholds balance automation efficiency, customer risk and service quality
• Agent desktop requirements include transcript history, customer context and recommended actions
• Warm handoff messages explain transfer reasons, expected waits and next steps
• Service recovery scripts address failed automation, complaints and unresolved customer needs
• Agent feedback loops convert recurring issues into chatbot content improvements
• Capacity planning estimates handoff volumes by channel, intent and service period

Participants can apply privacy, consent and safety requirements to conversational experiences.

• Consent records capture channel, purpose, timestamp, source and withdrawal method
• GDPR lawful-basis decisions distinguish consent, contract, legitimate interests and necessity
• Data-minimisation rules restrict conversational collection to stated business purposes
• Retention schedules define deletion, anonymisation and transcript access controls
• Bias testing identifies unequal outcomes across language, demographics and accessibility needs
• Safety guardrails route medical, financial, legal and crisis-sensitive requests appropriately

Participants can connect conversation data to lead management and sales follow-up processes.

• CRM field mapping aligns conversational data with contact and opportunity records
• Lead-scoring models combine declared intent, fit, engagement and recency signals
• Qualification frameworks apply BANT, MEDDICC or custom discovery criteria appropriately
• Routing logic assigns leads by territory, product, language and account value
• Sales alerts include transcript summaries, requested actions and consent status
• Service-level agreements define ownership, response times and follow-up responsibilities

Participants can design controlled generative AI responses grounded in approved information.

• Retrieval-augmented generation grounds answers in approved knowledge-base content
• System instructions define role, scope, tone, refusals and escalation behavior
• Prompt patterns constrain output formats for qualification, summaries and recommendations
• Knowledge sources assessed for freshness, ownership, authority and retrieval suitability
• Hallucination controls require citations, confidence thresholds and human review
• Red-team scenarios test prompt injection, unsafe requests and data exposure

Participants can design consented conversational campaigns for activation, retention and renewal.

• Lifecycle messaging maps onboarding, activation, replenishment, renewal and win-back triggers
• Triggered campaigns use behavioral events, consent status and frequency caps
• Segmentation combines profile attributes, conversation intent and engagement history
• Message sequencing balances promotional offers, service notices and educational content
• Frequency policies prevent fatigue across email, messaging and paid retargeting
• Suppression rules protect opted-out, converted and vulnerable customer groups

Participants can plan acquisition campaigns that move audiences into relevant customer conversations.

• Conversation starters tested through paid social, search and email placements
• Landing-page chat prompts matched to campaign promise, audience and source
• UTM conventions connect campaign traffic to conversation and downstream outcomes
• Attribution models distinguish first-touch, last-touch and assisted conversation value
• Referral mechanics encourage sharing without misleading incentives or undisclosed conditions
• Abandoned-conversation follow-up uses consented reminders and relevant completion prompts

Participants can design conversation flows that support product selection and transaction completion.

• Product discovery questions narrow choices using needs, preferences and eligibility
• Recommendation rules combine customer inputs, product attributes and inventory availability
• Cart recovery conversations address objections, delivery questions and payment concerns
• Payment handoffs protect card data through approved secure transaction pages
• Order-status journeys provide tracking, exceptions, returns and exchange options
• Cross-sell prompts follow completed customer goals without disrupting primary tasks

Participants can measure customer, operational and commercial results from conversational activity.

• Measurement plans connect business objectives, conversation metrics and decision owners
• Funnel dashboards track starts, engagement, completion, qualification and conversion
• Containment rate interpreted alongside resolution quality and customer effort
• Conversation analytics identifies recurring intents, drop-offs, failures and agent transfers
• GA4 events capture chat launches, key actions, conversions and campaign sources
• Cohort analysis compares retention and revenue after conversational interactions

Participants can prioritise and evaluate conversational improvements using valid experiment methods.

• A/B test hypotheses isolate message, flow, timing or channel changes
• Sample-size assumptions account for baseline conversion, detectable effect and traffic
• Control groups separate campaign impact from seasonality and concurrent activity
• Qualitative transcript coding explains quantitative patterns and unexpected customer behavior
• Prioritisation matrices rank improvements by impact, confidence, effort and risk
• Experiment readouts document decisions, limitations, next tests and accountable owners

Participants can establish operating controls for conversational marketing services and platforms.

• Operating models define product ownership, content approvals, agent coverage and escalation
• RACI matrices assign accountability for marketing, sales, service, legal and technology
• Conversation QA checklists assess accuracy, tone, compliance, accessibility and completion
• Incident playbooks cover outages, harmful outputs, privacy breaches and reputational risks
• Change-control procedures govern releases, rollback criteria and version histories
• Vendor scorecards assess security, data residency, support and total cost

Participants can adapt conversational marketing designs to sector-specific customer needs and controls.

• Retail conversations support product discovery, order updates, returns and loyalty enrolment
• Banking flows handle product enquiries, appointment booking and secure service escalation
• Public-service assistants guide eligibility checks, application status and appointment requests
• B2B conversations qualify buying committees, discovery needs and demonstration requests
• NGO messaging supports donor engagement, programme information and volunteer registration
• Regulated scenarios identify approval requirements, mandatory disclosures and prohibited claims

Participants can prepare a controlled launch plan for conversational marketing initiatives.

• Launch checklists cover content approval, platform testing, tracking and agent readiness
• Phased rollout plans define pilot audiences, release gates and rollback decisions
• Stakeholder communications explain customer value, operational changes and accountability
• Training plans prepare agents, marketers and administrators for new conversation processes
• Post-launch monitoring schedules review performance, customer feedback and incident signals
• Ninety-day roadmaps sequence improvements, owners, dependencies and investment decisions

Participants can build, review and present a complete conversational marketing solution with governance and measurement controls.

• Capstone brief defines audience, objective, constraints, channels and success measures
• Journey map connects campaign entry, conversation flow, handoff and follow-up
• Working prototype demonstrates intents, branches, content, integrations and escalation rules
• Measurement plan specifies events, dashboard metrics, targets and review cadence
• Risk register addresses consent, privacy, brand safety and operational failure
• Peer review tests scenario coverage, clarity, feasibility and commercial logic
• Presentation communicates design decisions, expected value, governance and launch actions