Alluvere Vanguard – AI, Automation & Analytics in Digital Marketing
Where Marketing Meets Machine Intelligence
The future of marketing is here — and it’s powered by AI, automation, and data. Alluvere Vanguard is a specialized program designed for digital marketers who want to go beyond channels and creatives, and dive into the technical backbone of modern marketing.
Curriculum
Google Analytics & Tag Manager
Module 1: Introduction to GA4
- Analytics Fundamentals: What digital analytics is and its importance for data-driven decisions.
- GA4 vs. Universal Analytics: Key differences and the paradigm shift to event-based tracking.
- Account and Property Setup: Creating a GA4 account, setting up a property for a website or app, and configuring data streams.
- Measurement Planning: Defining business objectives and aligning them with your analytics setup.
Module 2: GA4 Data Collection and Configuration
- Events: Understanding the event-based data model, including automatically collected, enhanced measurement, recommended, and custom events.
- Conversions: Identifying and marking key events that measure business objectives, such as purchases or sign-ups.
- Audiences: Creating custom audiences for advanced analysis, reporting, and remarketing.
- Data Accuracy: Excluding internal traffic and using filters to ensure clean data.
- Data Privacy: Overview of privacy controls and cookieless measurement.
Module 3: GA4 Reporting and Analysis
- Standard Reports: Navigating the GA4 interface and using pre-built reports for real-time traffic, acquisition, engagement, and monetization.
- Explorations: Going beyond standard reports with advanced analysis techniques.
- Funnel Exploration: Visualizing the user journey to identify drop-off points.
- Path Exploration: Understanding how users navigate your website or app.
- Free-Form Reports: Creating custom reports with specific metrics and dimensions.
- Customization: Tailoring the reporting experience by creating custom reports, dimensions, and metrics.
- Data Interpretation: Learning to translate data into actionable insights to improve website and campaign performance.
Module 4: Integration and Advanced Topics
- Google Ads Integration: Linking GA4 with Google Ads for in-depth campaign performance analysis.
- BigQuery Integration: Exporting GA4 data to BigQuery for large-scale, advanced querying and analysis.
- Custom Data Upload: Enriching your data by uploading additional data from other systems.
Module 5: GTM Fundamentals
- Introduction to GTM: What GTM is, its benefits, and how it differs from traditional hardcoded tag implementation.
- GTM Architecture: Understanding the core components of tags, triggers, and variables.
- Setup and Installation: Creating a GTM account, container, and installing the container snippet on a website.
- Interface Overview: Navigating the GTM dashboard, workspaces, and version control.
Module 6: Tags, Triggers, and Variables
- Tags: Deploying various tag types, including:
- Google Tags: GA4 Configuration Tag, GA4 Event Tag, and Google Ads Conversion and Remarketing Tags.
- Third-Party Tags: Implementing tags for other platforms, such as the Facebook Pixel.
- Triggers: Defining conditions for when a tag should fire, such as page views, clicks, form submissions, and video plays.
- Variables: Using built-in, user-defined, and Data Layer variables to pass dynamic information to tags.
Module 7: Advanced GTM Techniques
- The Data Layer: Understanding the Data Layer, a JavaScript object that GTM uses to retrieve and pass information.
- Event Tracking: Setting up tracking for specific user interactions, such as:
- Button clicks
- Scroll depth
- Form submissions
- Video views
- Enhanced E-commerce: Configuring GA4’s e-commerce tracking to collect valuable data on product views, add-to-cart actions, and purchases.
- Cross-Domain Tracking: Setting up tracking for user journeys that span multiple websites.
Module 8: Testing, Debugging, and Optimization
- Preview Mode: Using the GTM Preview mode and DebugView in GA4 to test tag configurations before publishing.
- Testing and QA: Implementing robust testing practices to prevent errors and ensure accurate data collection.
- Workspaces and Environments: Collaborating with teams and managing different versions of your tags.
- Google Consent Mode: Configuring GTM to respect user consent for privacy regulations.
- Server-Side Tagging: An introduction to server-side GTM for improved performance, security, and data accuracy.
AI, CRM & Automation
Module 1: Foundations of CRO
- Introduction to CRO: Define CRO, its importance, and how it fits into the broader digital marketing landscape alongside Search Engine Optimization (SEO) and Pay-Per-Click (PPC).
- Core concepts and terminology: Understand key terms such as conversion goals (macro and micro), conversion funnels, and calculating conversion rates.
- The CRO process: Learn the scientific method behind CRO, which involves gathering data, formulating hypotheses, running tests, analyzing results, and iterating.
- User-centric design principles: Explore how user experience (UX) and user interface (UI) design affect conversion, focusing on clarity, reducing friction, and creating a seamless mobile experience.
Module 2: Conversion research
- Qualitative research: Learn how to gain insights into user motivations and pain points through:
- On-site surveys and feedback polls
- Customer interviews
- User personas
- Quantitative research: Use analytics to understand user behavior by identifying what users do on your site. This includes:
- Website analytics: Analyze traffic sources, user flow, and conversion funnels using tools like Google Analytics.
- Behavioral analytics: Visualize user interactions with heatmaps, click maps, scroll maps, and session recordings using tools like Hotjar or Crazy Egg.
- Form analytics: Pinpoint friction points in your forms to increase form completion rates.
Module 3: Optimizing for conversion
- Landing page optimization: Craft high-converting landing pages by refining messaging, optimizing page layout, and simplifying forms.
- Call-to-action (CTA) optimization: Learn how to design compelling CTAs by testing different colors, copy, and placement.
- Persuasive copywriting: Write clear, compelling, and benefit-driven copy that addresses customer pain points and objections.
- Conversion psychology: Apply principles like social proof, urgency, and scarcity to influence user behavior and build trust.
Module 4: Advanced CRO topics
- E-commerce CRO: Master specialized techniques for online stores, including abandoned cart recovery, optimizing product pages, and streamlining the checkout process.
Mobile conversion optimization: Focus on the specific challenges and opportunities of optimizing for mobile users, from page speed to user interface design.
Data Analysis
Module 1: Foundational concepts
This module introduces core ideas that every data-savvy marketer must understand.
- Introduction to marketing analytics: The role of data in modern marketing, aligning data with business objectives, and overcoming challenges like data silos.
- The analytical mindset: Shifting from intuition to evidence-based decision-making.
- Types of data analytics: Understanding the four primary approaches.
- Descriptive analytics: What happened? (e.g., summarizing monthly sales).
- Diagnostic analytics: Why did it happen? (e.g., investigating why a campaign underperformed).
- Predictive analytics: What will happen? (e.g., forecasting future sales).
- Prescriptive analytics: What should we do? (e.g., optimizing an advertising budget)
- Data fundamentals for marketers:
- Data collection: Identifying key data sources, such as website analytics, social media, and CRM software.
- Data types: Recognizing and working with different types of data, including first-party, second-party, and third-party data.
- Data hygiene: Understanding the importance of cleaning and preparing data for analysis.
Module 2: Essential tools and metrics
This section focuses on the practical tools and calculations used in marketing data analysis.
- Spreadsheet mastery: Using Microsoft Excel or Google Sheets for foundational analysis, including PivotTables, PivotCharts, and functions.
- Web analytics with Google Analytics: Navigating reports to understand website traffic, user behavior, conversions, and acquisition channels.
- Key marketing metrics and KPIs: Learning to track and interpret vital performance indicators.
- Customer-centric: Customer Lifetime Value (CLV), Customer Acquisition Cost (CAC), and churn rate.
- Campaign performance: Conversion rate, Click-Through Rate (CTR), and Return on Ad Spend (ROAS).
- Financial: Return on Marketing Investment (ROMI).
Module 3: Customer and campaign analysis
Here, marketers apply analytical techniques to solve common marketing problems.
- Customer segmentation and targeting: Using data to divide an audience into meaningful groups based on demographics, behavior, or value.
- RFM analysis: Segmenting customers by recency, frequency, and monetary value.
- Marketing mix analysis: Measuring the effectiveness and ROI of different channels like email, social media, and paid ads.
- Experimentation and optimization: Conducting A/B testing to evaluate and optimize campaign elements.
- Sales funnel analysis: Evaluating the conversion path, identifying drop-off points, and understanding user journeys.
Module 4: Data visualization and storytelling
This module teaches how to communicate insights effectively to stakeholders.
- Fundamentals of data visualization: Learning best practices for creating clear and impactful charts, graphs, and dashboards.
- Choosing the right visualization: Selecting the most effective format for telling a specific data story.
- Dashboard creation: Building real-time, interactive dashboards using BI tools like Tableau or Power BI to monitor and share key performance indicators.
- Communicating insights: Translating complex data into compelling, actionable recommendations for marketing strategies.
Module 5: Project and Market Analysis
This final module integrates all concepts into a comprehensive project and introduces more advanced techniques.
- Capstone project: Applying all learned skills by analyzing a real-world marketing dataset from start to finish.
- Introduction to advanced topics:
- Market basket analysis: Finding associations between purchased items.
- Sentiment analysis: Using text mining to analyze customer feedback from social media.
- Social network analysis: Mapping relationships and influence among social media users.
- Marketing analytics ethics: Understanding and navigating the privacy regulations and ethical considerations in handling customer data.
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Course Benefits
Get The Globally Recognized Certificates
Get The Real-World Experience
Career Guidance by Industry Experts
Learn From The Industry Experts
Courses are designed to make you Industry-Ready not to get the certifications only.
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