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Data Marketing Course
More than 2 million students worldwide

Data Marketing Course

Master the full spectrum of data-driven marketing — from audience segmentation and predictive analytics to paid media optimization and personalization strategy. This course gives you the technical skills and strategic frameworks to turn raw data into measurable business results. If you're ready to make smarter marketing decisions backed by real evidence, this is where you start.

Dedika for Business

What you will learn:

You will learn how to collect, clean, and manage first-party marketing data using CDPs, CRMs, and tag management systems. You will build audience segments, run A/B tests, and design attribution models that connect campaigns to revenue. The course covers predictive analytics, customer lifetime value modeling, and machine learning applications in marketing. You will also develop skills in SQL, data visualization, and marketing automation workflows. By the end, you will be able to audit your organization's data maturity and build a prioritized roadmap aligned to business goals.

How you study in practice Data Marketing Course

How you practise Data Marketing Course

For companies looking to train their team

With Dedika for Business, the course includes exercises and examples tailored to your own business and the way your company needs.

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Course Content

8 Chapters • 41 LessonsDuration between 4 and 360 hours (you decide)

Chapter 1See details

Foundations of Data Marketing

  • Lesson 1 • Data Quality and Governance Basics

    Introduces accuracy, completeness, and consistency as quality dimensions. Connects poor data quality to wasted spend and missed targeting.

  • Lesson 2 • What Data Marketing Actually Is

    Defines data marketing by contrasting it with intuition-based approaches and maps its core components. Establishes shared vocabulary used throughout the course.

  • Lesson 3 • Ethical and Regulatory Foundations

    Covers consumer privacy rights, consent frameworks, and data minimization principles. Grounds ethical practice in business risk and consumer trust.

  • Lesson 4 • The Data Marketing Ecosystem

    Maps the tools, teams, and data sources that form a modern marketing stack. Shows how each element connects to campaign execution.

  • Lesson 5 • Types of Marketing Data

    Categorizes behavioral, demographic, transactional, and contextual data. Explains when each type drives the most actionable insights.

Chapter 2See details

Collecting and Managing Marketing Data

  • Lesson 1 • Tag Management and Pixel Implementation

    Explains how tags and pixels fire data to analytics and ad platforms. Teaches implementation logic without requiring deep coding skills.

  • Lesson 2 • Customer Data Platforms and CRMs

    Distinguishes CDPs from CRMs and explains when each is appropriate. Shows how unified profiles are built from multiple data sources.

  • Lesson 3 • Data Storage and Access Architecture

    Introduces data warehouses, data lakes, and marts as storage options for marketing data. Connects storage choice to query speed and team accessibility.

  • Lesson 4 • Data Cleaning and Preparation

    Teaches deduplication, normalization, and handling of missing values in marketing datasets. Prepares students to deliver analysis-ready data.

  • Lesson 5 • First-Party Data Collection Methods

    Covers website tracking, CRM inputs, surveys, and loyalty programs as primary collection channels. Emphasizes owned data as the most reliable marketing asset.

Chapter 3See details

Audience Segmentation and Targeting

  • Lesson 1 • Audience Activation Across Channels

    Covers how segments are pushed to ad platforms, email tools, and personalization engines. Addresses match rates and identity resolution in activation.

  • Lesson 2 • Lookalike and Predictive Audiences

    Explains how seed audiences are used to model and expand reach to similar prospects. Introduces predictive scoring as a targeting enhancement.

  • Lesson 3 • Segmentation Strategy Fundamentals

    Defines segmentation criteria and explains why granularity must match campaign objectives. Introduces the trade-off between segment size and specificity.

  • Lesson 4 • Segment Performance Measurement

    Defines KPIs for evaluating segment quality and campaign fit. Teaches iterative refinement based on performance feedback.

  • Lesson 5 • Behavioral and Psychographic Segmentation

    Uses purchase history, browsing patterns, and attitudinal data to form deeper audience profiles. Connects behavioral signals to messaging strategy.

Chapter 4See details

Marketing Analytics and Measurement

  • Lesson 1 • Dashboard Design and Reporting

    Teaches principles of effective marketing dashboards for different stakeholder audiences. Covers layout, chart selection, and automated reporting workflows.

  • Lesson 2 • Experimentation and A/B Testing

    Introduces hypothesis-driven testing, sample size calculation, and statistical significance for marketing experiments. Connects test results to iterative campaign improvement.

  • Lesson 3 • Web and Campaign Analytics

    Covers traffic analysis, session behavior, and campaign performance reporting using analytics platforms. Teaches UTM parameter strategy for accurate source attribution.

  • Lesson 4 • Core Marketing Metrics Framework

    Establishes a hierarchy of metrics from awareness to revenue and maps each to funnel stages. Prevents vanity metric traps by linking metrics to business outcomes.

  • Lesson 5 • Attribution Modeling

    Compares last-click, linear, time-decay, and data-driven attribution models. Guides model selection based on channel mix and data availability.

Chapter 5See details

Personalization and Customer Experience

  • Lesson 1 • Email and CRM Personalization

    Covers dynamic content, behavioral triggers, and lifecycle-based messaging in email and CRM systems. Ties personalization depth to open, click, and conversion rates.

  • Lesson 2 • Personalization Strategy and Maturity

    Maps personalization from rule-based to AI-driven and helps students assess their organization's current maturity. Frames personalization as a business capability, not just a tactic.

  • Lesson 3 • Omnichannel Personalization Orchestration

    Explains how to coordinate personalized messages across email, paid, web, and in-store channels. Addresses data synchronization and message sequencing.

  • Lesson 4 • Privacy-Safe Personalization Techniques

    Covers contextual targeting, cohort-based personalization, and on-device processing as privacy-preserving alternatives. Balances relevance with consumer trust.

  • Lesson 5 • Website and App Personalization

    Teaches real-time content adaptation based on user segments, behavior, and context. Covers recommendation engines and on-site testing.

Chapter 6See details

Paid Media and Data-Driven Advertising

  • Lesson 1 • Search and Social Campaign Targeting

    Covers keyword intent data, audience layering, and custom audience uploads for search and social platforms. Teaches targeting refinement using performance data.

  • Lesson 2 • Paid Media Data Fundamentals

    Introduces the data signals that power paid media targeting and bidding decisions. Connects first-party data quality to ad platform performance.

  • Lesson 3 • Budget Allocation and Bid Optimization

    Teaches data-driven budget allocation across channels using performance signals and marginal return analysis. Covers automated bidding strategy selection.

  • Lesson 4 • Programmatic Advertising and DSPs

    Explains real-time bidding, deal types, and data management in programmatic buying. Covers brand safety and inventory quality controls.

  • Lesson 5 • Creative Data and Ad Testing

    Uses performance data to guide creative decisions, ad format selection, and iterative testing. Introduces dynamic creative optimization principles.

Chapter 7See details

Predictive Analytics and Machine Learning in Marketing

  • Lesson 1 • Customer Lifetime Value Modeling

    Teaches CLV calculation methods and their use in acquisition budget setting and retention prioritization. Connects CLV to long-term revenue strategy.

  • Lesson 2 • Model Deployment and Monitoring

    Covers the steps from model training to production deployment and ongoing performance monitoring. Addresses model drift and retraining triggers.

  • Lesson 3 • Recommendation Systems in Marketing

    Explains collaborative filtering, content-based, and hybrid recommendation approaches. Covers implementation considerations for e-commerce and content platforms.

  • Lesson 4 • Predictive Analytics Foundations

    Introduces regression, classification, and clustering as the core model types used in marketing. Frames each model type by the marketing question it answers.

  • Lesson 5 • Churn Prediction and Retention Models

    Builds churn prediction models using behavioral and transactional features. Translates model output into targeted retention interventions.

Chapter 8See details

Data Marketing Strategy and Roadmap

  • Lesson 1 • Aligning Data Strategy to Business Goals

    Translates business objectives into data marketing priorities and measurable success criteria. Prevents strategy-execution misalignment.

  • Lesson 2 • Measuring and Evolving the Strategy

    Establishes review cadences, performance benchmarks, and feedback loops to keep the strategy current. Connects ongoing measurement to strategic iteration.

  • Lesson 3 • Technology and Vendor Selection

    Teaches a structured evaluation process for selecting marketing technology based on data needs and integration requirements. Covers build vs. buy decisions.

  • Lesson 4 • Building a Data-Driven Marketing Team

    Defines the roles, skills, and operating models needed to execute a data marketing strategy. Covers hybrid team structures and capability development.

  • Lesson 5 • Auditing Current Data Marketing Maturity

    Provides a structured framework for assessing data, technology, talent, and process maturity. Identifies gaps between current state and strategic goals.

  • Lesson 6 • Roadmap Development and Prioritization

    Guides students through building a phased data marketing roadmap with clear milestones and resource requirements. Covers prioritization frameworks for competing initiatives.

Certification

Your valid completion certificate

This course is for you:

  • Marketing manager: wants to stop guessing and start deciding with data.

  • Digital advertising specialist: needs sharper targeting skills to improve campaign returns.

  • Career changer: moving from a non-marketing role into a data-focused marketing position.

  • Small business owner: ready to use customer data to grow revenue more efficiently.

  • Marketing analyst: looking to expand beyond reporting into strategy and predictive modeling.

  • Product marketer: seeking to connect user behavior data to messaging and positioning decisions.

What our students say

Your classes are perfect. I purchased the one-year package and finally have the opportunity to follow various topics of interest without needing to switch platforms... I thank you for everything you do, I've already recommended you to other people...
Giulio Carlo
Giulio CarloDigital Marketing Student
I like how the lessons are straight to the point and how I can change chapters and skip content I don't need.
Mariana Ferres
Mariana FerresPhotography Student
I like the content and the presentation style and video transcription, which speeds up the process!
Luciana Alvarenga
Luciana AlvarengaNail Design Student
The platform is fast, simple to use. The diversity of content and complementary videos really help with learning.
André Felipe
André FelipePrompt Engineering Student

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