Course Introduction
Marketing has become increasingly data-driven, requiring organizations to understand market trends, customer preferences, campaign effectiveness, and the financial contribution of marketing activities. Businesses invest significant resources in advertising, digital promotions, customer engagement, brand development, and sales activation, yet many struggle to determine which activities generate measurable results. Marketing business intelligence provides the analytical foundation for transforming marketing data into actionable insights that improve planning, resource allocation, and strategic decision-making. This course equips participants with the knowledge and practical skills required to develop marketing intelligence frameworks, measure campaign performance, and use analytical insights to improve marketing effectiveness and organizational growth.
The programme explores the principles of marketing business intelligence and the role of data analytics in developing effective marketing strategies. Participants examine how customer information, market research, sales transactions, digital engagement, advertising performance, and competitor intelligence can be consolidated to provide a comprehensive view of marketing performance. Emphasis is placed on understanding marketing objectives, defining measurable performance indicators, evaluating customer acquisition strategies, analyzing market opportunities, and aligning marketing activities with organizational priorities. Participants also learn how to distinguish between activity-based marketing measurements and meaningful performance indicators that demonstrate commercial value.
A central component of the training focuses on campaign performance analytics and the methods used to assess marketing effectiveness across traditional and digital channels. Participants explore campaign reach, impressions, engagement, click-through rates, conversion rates, cost per acquisition, customer acquisition cost, return on advertising spend, marketing return on investment, and customer lifetime value. The programme examines how to evaluate campaign performance at different stages of the customer journey, compare marketing channels, identify audience response patterns, and determine the contribution of individual campaigns to sales and revenue growth. Practical applications include campaign attribution, A/B testing, conversion funnel analysis, and budget effectiveness assessment.
The course further develops participants' capabilities in using modern business intelligence and marketing analytics technologies. Participants gain practical exposure to Microsoft Excel, Power BI, SQL, CRM platforms, marketing automation systems, and digital analytics environments for collecting, preparing, analyzing, and visualizing marketing information. They explore the development of interactive marketing dashboards, automated campaign reports, channel performance scorecards, and executive marketing intelligence presentations. Emerging technologies such as artificial intelligence, machine learning, predictive analytics, and generative AI are also examined for their applications in campaign optimization, audience targeting, marketing forecasting, sentiment analysis, and automated performance reporting.
Effective marketing intelligence requires reliable data, clear governance, and consistent measurement practices. Participants examine challenges associated with fragmented marketing data, inaccurate attribution, inconsistent performance definitions, data privacy, consent management, and integration across advertising platforms and customer relationship management systems. The programme also considers the implications of changing digital advertising environments, evolving privacy regulations, reduced availability of third-party cookies, mobile-first consumer behavior, social commerce, influencer marketing, and omnichannel customer engagement. These topics help participants understand how to build adaptable marketing measurement systems that remain relevant in a rapidly changing digital and commercial environment.
By the end of the course, participants will be able to develop marketing intelligence frameworks, analyze campaign performance, build interactive reporting dashboards, and translate marketing data into practical business recommendations. They will gain the ability to evaluate campaign profitability, identify high-performing channels, improve audience targeting, optimize marketing expenditure, and demonstrate the contribution of marketing activities to organizational objectives. The programme supports stronger evidence-based marketing decisions, more efficient campaign management, improved customer acquisition, and sustainable improvements in marketing return on investment.
Duration
5 days
Who Should Attend
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Chief Marketing Officers and Marketing Directors
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Marketing Managers and Marketing Strategy Professionals
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Digital Marketing Managers and Digital Campaign Specialists
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Marketing Business Intelligence Analysts
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Marketing Data Analysts and Data Scientists
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Campaign Managers and Advertising Specialists
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Brand Managers and Brand Performance Analysts
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Customer Relationship Management (CRM) Managers
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Marketing Automation and Customer Engagement Specialists
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Market Research and Consumer Insights Professionals
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Social Media and Content Marketing Managers
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Sales and Business Development Managers
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E-commerce and Digital Commerce Managers
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Business Intelligence and Reporting Specialists
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Financial Analysts responsible for marketing budgets and expenditure
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Consultants involved in marketing strategy and performance improvement
Course Objectives
By the end of this course, participants will be able to:
1. Explain the principles of marketing business intelligence and evaluate how data-driven insights support marketing strategy, campaign planning, customer acquisition, and organizational performance.
2. Identify and integrate marketing data from advertising platforms, CRM systems, websites, social media, sales databases, customer surveys, and market research sources.
3. Define relevant marketing performance indicators and establish measurement frameworks covering campaign reach, engagement, conversions, acquisition costs, revenue contribution, and profitability.
4. Apply analytical techniques to assess campaign effectiveness, compare marketing channels, identify audience behavior patterns, and evaluate performance across different customer segments.
5. Calculate and interpret campaign metrics, including click-through rates, conversion rates, cost per lead, cost per acquisition, return on advertising spend, and marketing return on investment.
6. Develop marketing attribution and conversion funnel analysis approaches to assess customer interactions, understand channel contributions, and improve the evaluation of marketing-driven business outcomes.
7. Use Microsoft Excel, Power BI, SQL, and other marketing analytics technologies to prepare data, automate reporting, and develop interactive campaign performance dashboards.
8. Apply predictive analytics, artificial intelligence, machine learning, and A/B testing techniques to improve audience targeting, forecast campaign outcomes, and optimize marketing decisions.
9. Establish reliable marketing data governance and measurement practices that address data quality, privacy, consent management, reporting consistency, and responsible use of customer information.
10. Translate marketing intelligence findings into actionable recommendations for improving campaign performance, optimizing marketing budgets, strengthening customer engagement, and increasing commercial returns.
Comprehensive Course Outline
Module 1: Fundamentals of Marketing Business Intelligence and Performance Analytics
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Understanding marketing business intelligence concepts, analytical principles, and their contribution to marketing strategy, competitive positioning, and organizational growth.
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Examining the relationship between marketing objectives, customer insights, market intelligence, campaign execution, and measurable business outcomes.
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Identifying marketing data requirements and understanding how internal and external information sources support evidence-based marketing decisions.
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Differentiating marketing performance measurement, marketing analytics, business intelligence, market research, and marketing effectiveness evaluation.
Module 2: Marketing Data Collection, Integration and Management
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Identifying marketing data sources, including digital advertising platforms, websites, social media, CRM systems, email marketing tools, sales records, and customer surveys.
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Applying data extraction, transformation, cleaning, validation, and integration techniques to consolidate marketing information from multiple systems.
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Understanding customer data platforms, marketing automation technologies, application programming interfaces, and cloud-based marketing data environments.
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Addressing data fragmentation, inconsistent reporting definitions, duplicate records, tracking limitations, and data quality issues affecting marketing analytics.
Module 3: Marketing Performance Indicators and Measurement Frameworks
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Defining marketing key performance indicators covering campaign reach, impressions, engagement, website traffic, leads, conversions, customer acquisition, and revenue generation.
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Calculating and interpreting click-through rates, cost per click, cost per lead, cost per acquisition, conversion rates, and customer acquisition costs.
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Measuring return on advertising spend, marketing return on investment, customer lifetime value, revenue attribution, and campaign profitability.
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Developing marketing performance scorecards, measurement frameworks, reporting standards, and target-setting methodologies aligned with organizational objectives.
Module 4: Campaign Performance Analysis and Optimization
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Evaluating campaign effectiveness across search advertising, display advertising, social media, email marketing, content marketing, influencer campaigns, and traditional media.
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Applying campaign segmentation and comparative analysis to evaluate performance by channel, audience, geographic market, product, and customer category.
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Conducting conversion funnel analysis to identify customer drop-off points, engagement gaps, lead generation challenges, and opportunities for improving campaign outcomes.
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Using A/B testing, multivariate testing, and controlled experiments to compare campaign messages, creative formats, landing pages, and audience targeting strategies.
Module 5: Customer Analytics, Audience Intelligence and Marketing Attribution
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Developing customer profiles and audience segments using demographic, geographic, psychographic, transactional, and behavioral information.
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Applying RFM analysis, customer lifetime value analysis, propensity modeling, and customer journey mapping to improve marketing targeting and personalization.
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Understanding first-touch, last-touch, linear, time-decay, and data-driven attribution approaches for evaluating marketing channel contributions.
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Exploring omnichannel attribution challenges, cross-device customer journeys, privacy-related tracking limitations, and measurement approaches in evolving digital advertising environments.
Module 6: Marketing Business Intelligence Tools and Dashboard Development
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Understanding the applications of Microsoft Excel, SQL, Power Query, Power BI, CRM analytics, and marketing automation platforms in marketing performance management.
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Preparing marketing datasets, developing analytical calculations, and creating reusable reporting models for campaign and channel performance analysis.
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Designing interactive marketing dashboards featuring campaign metrics, conversion trends, advertising expenditure, customer acquisition, and revenue performance.
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Applying data visualization, automated refresh schedules, drill-down analysis, executive scorecards, and dynamic reporting to improve marketing decision support.
Module 7: Digital Marketing Analytics, Social Media Intelligence and Emerging Technologies
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Analyzing website performance, search engine marketing, search engine optimization, social media engagement, email campaign effectiveness, and digital conversion behavior.
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Evaluating social media reach, audience growth, engagement rates, sentiment, referral traffic, influencer performance, and brand interaction trends.
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Exploring artificial intelligence and machine learning applications in predictive campaign optimization, customer targeting, automated bidding, and marketing forecasting.
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Applying generative AI and natural language processing to customer feedback analysis, campaign content insights, automated marketing reports, and sentiment monitoring with appropriate human oversight.
Module 8: Marketing Budget Analytics, Forecasting and Return on Investment
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Analyzing marketing budgets, campaign expenditure, channel allocation, cost efficiency, and spending patterns to identify opportunities for improved resource utilization.
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Developing marketing forecasts using historical campaign results, seasonal trends, sales performance, customer demand, and market intelligence.
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Evaluating campaign profitability through revenue attribution, incremental sales analysis, contribution margins, and return on marketing investment.
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Applying scenario analysis and predictive modeling to assess alternative budget allocations, forecast campaign outcomes, and support marketing investment decisions.
Module 9: Marketing Intelligence Governance, Privacy and Strategic Reporting
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Establishing marketing intelligence governance frameworks covering data ownership, measurement standards, reporting responsibilities, and analytical quality assurance.
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Examining customer data protection, consent management, cybersecurity, ethical marketing analytics, and applicable regulatory requirements.
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Addressing third-party cookie restrictions, evolving digital advertising policies, algorithmic bias, data sharing risks, and responsible AI in marketing environments.
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Preparing executive marketing reports and presentations that communicate campaign results, performance gaps, market opportunities, and recommendations for strategic action.
Module 10: Practical Marketing Intelligence and Campaign Analytics Implementation
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Conducting a practical marketing performance assessment using campaign data to evaluate channel effectiveness, audience response, conversion performance, and expenditure efficiency.
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Developing an integrated marketing intelligence dashboard incorporating campaign KPIs, customer segmentation, attribution metrics, and return on investment indicators.
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Interpreting dashboard results to identify underperforming campaigns, high-value customer segments, channel opportunities, and areas requiring corrective action.
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Preparing a marketing analytics implementation roadmap covering data integration, technology requirements, reporting schedules, team responsibilities, and continuous performance improvement.
Training Approach
This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.
Tailor-Made Course
This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: training@upskilldevelopment.com Tel: +254 721 331 808
Training Venue
The training will be held at our Upskill Training Centre. We also offer training for a group (at a discount of 10% to 50%) at requested location all over the world. The Onsite course fee covers the course tuition, training materials, two break refreshments, buffet lunch, airport transfers, Upskill gift package, and guided tour.
Visa application, travel expenses, dinners, accommodation, insurance, and other personal expenses are catered by the participant
Certification
Participants will be issued with Upskill certificate upon completion of this course.
Airport Pickup and Accommodation
Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: training@upskilldevelopment.com, +254 721 331 808
Terms of Payment:
Unless otherwise agreed between the two parties’ payment of the course fee should be done 3 working days before commencement of the training so as to enable us to prepare better.
