Introduction
The programme “Marketing and Sales Using Predictive Analytics” develops professional practice in Marketing and Sales. It connects the subject with workplace challenges by examining existing evidence and practices and choosing methods appropriate to the organization and its available resources.
The learning progresses from reliability, predictive maintenance, and failure analysis to data analysis and decision support, with practical work on sales management, negotiation, and relationship development, market analysis and marketing strategy development, customer experience development and complaint handling. Participants prepare outputs to support workplace application and review the quality and results of implementation.
Learning objectives
- Analyze asset failure and condition data to define a justified warning and maintenance intervention in an application related to “Marketing and Sales Using Predictive Analytics”.
- Build a sales process connecting opportunity qualification with customer needs and disciplined follow-up.
- Design a marketing direction based on a defined segment and measurable value.
- Design a service journey and complaint response based on customer needs and follow-up evidence.
- Turn available data into documented analysis that supports a specific professional decision.
Learning areas
1. Reliability, Predictive Maintenance, and Failure Analysis
- Define the asset's function, functional failure, and usage context, and assess the effects of failure modes before selecting a maintenance task type.
- Organize fault, downtime, repair, and condition reading histories, checking the quality of timestamps, classifications, and record completeness.
- Analyze trends, vibration, temperature, or other appropriate condition indicators, linking alerts to documented thresholds and specialist technical review.
- Distinguish correlation and prediction from proof of a failure's cause, and assess false and missed alarms and warning lead time before intervention.
- Design a condition monitoring pilot for a training asset, with escalation criteria and documentation of the maintenance decision, and verify the intervention's effect on reliability. The application examines a case related to “Marketing and Sales Using Predictive Analytics”.
2. Sales Management, Negotiation, and Relationship Development
- Identify the right customer and qualify the opportunity in terms of need, decision-making, budget, and timing, documenting missing information.
- Conduct a discovery interview focused on the customer's problem and intended result, distinguishing the stated request from the actual need.
- Write a proposal connecting the solution to value, evidence, scope, and terms, and address objections through questions and checks on understanding.
- Prepare a negotiation identifying interests, alternatives, and authority limits, and document both parties' commitments and the closing and handover steps.
- Manage follow-up in an opportunity register with evidence-based forecasts, and measure conversion, sales cycle length, and relationship quality after delivery.
3. Market Analysis and Marketing Strategy Development
- Analyze the market, competitors, and customers using appropriate data, and identify sample limitations and assumptions requiring testing.
- Segment the market, select the priority segment, and describe customer needs, behavior, and decision-making criteria.
- Build a clear value proposition and positioning, connecting them to service features and evidence supporting the marketing promise.
- Select the channel mix, content, and budget according to the customer journey, and define messages suited to each stage without overstating claims.
- Prepare a campaign pilot with reach, engagement, conversion, and cost indicators, and analyze results to adjust targeting, messages, and resource allocation.
4. Customer Experience Development and Complaint Handling
- Define customer groups, expectations, and touchpoints, and map an actual journey including waiting, effort, and information exchange.
- Analyze the voice of the customer, complaints, and feedback, classifying recurring causes and linking them to the process, product, or communication channel.
- Set response, resolution, and escalation standards that consider the problem's impact, staff authority, and message clarity for the customer.
- Simulate a difficult service situation, applying listening, empathy, and fact verification, and offer a feasible solution or alternative.
- Build indicators for resolution time, complaint recurrence, and experience quality, and use results to address root causes and monitor impact.
5. Data Analysis and Decision Support
- Frame an analytical question linked to a specific decision, and define the unit of measurement, time period, and data needed to answer it.
- Check data quality for completeness, accuracy, consistency, and duplication, and document cleaning steps and limitations on reliance.
- Select appropriate comparisons, indicators, and charts, and distinguish statistical correlation from causal explanations of results.
- Interpret results in the work context, test assumptions and unusual values, and present alternatives and their associated uncertainty.
- Prepare an analytical report containing the finding, recommendation, data source and date, review owner, and next follow-up step.
Practical outputs
- A failure mode analysis, condition monitoring plan, and alert and review rules.
- A customer account plan, opportunity pipeline, and proposal and follow-up template.
- A marketing plan covering segments, value proposition, channels, and outcome measures.
- A customer journey map, complaint response guide, and service quality cards.
- A dashboard and decision memo explaining the data, assumptions, and alternatives.
Who should attend
- Practitioners, specialists and supervisors whose work relates to the programme subject.
- Managers and teams working in marketing and sales, according to their practical responsibilities.
- Professionals responsible for applying the outputs of “Marketing and Sales Using Predictive Analytics” within their organizations.
Prerequisites
- Working familiarity with the programme field and the ability to discuss a professional case or challenge.
- Confirm the suitability of your experience and any specialist prerequisites with the Union before participation.
Conclusion
The programme “Marketing and Sales Using Predictive Analytics” brings together concepts, case review and a practical application. Participants prepare steps that can be adapted to their responsibilities and organizational resources, with an indicator to follow application and review results after returning to work.
Participation arrangements and any special requests are specified in the confirmation issued by the Union.