AI Powered Customer Insights and Business Intelligence #245014

Upon completion of this course, participants will be able to:

• Understand the AI-BI Landscape: Define how AI and Machine Learning augment traditional analytics and BI processes to create a competitive advantage.

• Master Data Strategy for AI: Identify, integrate, and prepare diverse data sources (first-party, third-party, structured, unstructured) for AI-driven analysis.

• Apply Advanced Analytical Techniques: Utilize key AI-powered methods such as predictive analytics, customer segmentation (clustering), sentiment analysis (NLP), and churn prediction.

• Visualize and Communicate Insights: Create dynamic, AI-driven dashboards and data visualizations that tell a story and prescribe actionable business strategies.

• Build a Roadmap for Implementation: Develop a strategy for integrating AI-powered insights tools into their organization’s existing workflows and data culture.

• Evaluate Ethical Implications: Address critical issues of data privacy, algorithmic bias, and ethical use of customer data in AI analytics.

This course is designed for professionals who use data to understand customers, measure performance, and guide business strategy:

• Business Intelligence (BI) Analysts & Developers: Professionals looking to integrate AI and machine learning into their reporting and analytics platforms.

• Data Analysts & Scientists: Analysts who want to shift from descriptive reporting to predictive and prescriptive modeling focused on business outcomes.

• Marketing & Customer Insights Professionals: Marketers, CRM managers, and insights managers who need to understand customer behavior at a deeper level to personalize experiences and improve retention.

• Product Managers & Strategists: Individuals responsible for product direction who need to use customer usage data and market trends to inform roadmap decisions.

• Digital & Growth Strategists: Professionals focused on user acquisition, engagement, and monetization who rely on data to optimize campaigns and funnels.

• Business Leaders & Executives: Directors, VPs, and C-suite executives (CMOs, CPOs, CDOs) who need to make data-informed strategic decisions and manage AI-powered insights teams.

• Sales Operations & Revenue Analysts: Those who analyze sales data, forecast performance, and identify growth opportunities

• Pre-assessment
• Live group instruction
• Use of real-world examples, case studies and exercises
• Interactive participation and discussion
• Power point presentation, LCD and flip chart
• Group activities and tests
• Each participant receives a binder containing a copy of the presentation
• slides and handouts
• Post-assessment

Day 1: The New Frontier: Integrating AI with Traditional BI

• AM: From Descriptive to Predictive and Prescriptive

  • The evolution of BI: Dashboards vs. Intelligent Automation.

  • Key AI Concepts for BI: Overview of Machine Learning, Natural Language Processing (NLP), and Clustering.

  • The AI-Augmented Analyst: How AI transforms the role of insights professionals.

• PM: Building a Data-First Foundation

  • Data Sourcing and Strategy: Connecting CRM, web analytics, transactional data, and unstructured data (e.g., social media, reviews).

  • Introduction to AI-BI Platforms: Overview of tools like Power BI with AI, Tableau CRM, and specialized AI platforms.

  • Workshop: Auditing your organization’s data readiness for AI.

Day 2: Understanding the Customer with AI

• AM: Deep Customer Segmentation and Persona Development

  • Moving beyond RFM: Using AI clustering algorithms (e.g., K-Means) for dynamic, behavior-based segmentation.

  • Creating 360-degree customer views with AI data integration.

  • Case Study: How Netflix/Amazon uses clustering for personalization.

• PM: Sentiment and Voice of the Customer (VoC) Analysis

  • Using Natural Language Processing (NLP) to analyze customer feedback, reviews, and support tickets at scale.

  • Real-time sentiment tracking and trend identification.

  • Workshop: Using a tool (e.g., MonkeyLearn, pre-built API) to analyze a dataset of product reviews for key themes and sentiment.

Day 3: Predicting the Future with Predictive Analytics

• AM: Forecasting and Trend Analysis

  • Introduction to predictive models for demand forecasting, sales prediction, and inventory management.

  • Hands-on with automated forecasting in BI tools (e.g., Facebook Prophet, Azure AutoML).

• PM: Churn Prediction and Customer Lifetime Value (CLV)

  • Building models to identify customers at high risk of churning.

  • Calculating and predicting CLV using machine learning to prioritize retention efforts.

  • Workshop: Interpreting the output of a pre-built churn model to define a targeted marketing action plan.

Day 4: Generating and Communicating Actionable Insights

• AM: AI-Powered Data Visualization and Storytelling

  • Creating interactive dashboards that surface AI-driven recommendations, not just data.

  • Natural Language Generation (NLG): Having AI write summary insights and reports in plain language.

  • Workshop: Using a BI tool to generate a narrative summary from a dataset.

• PM: Prescriptive Analytics and Decision Intelligence

  • Moving from “what will happen” to “what should I do?”

  • Simulating business outcomes based on AI-driven recommendations.

  • Building a culture of data-driven decision-making.

Day 5: Strategy, Implementation, and Ethics

• AM: Building Your AI-Powered Insights Roadmap

  • Prioritizing use cases based on business impact and feasibility.

  • Overcoming organizational hurdles: Skills, culture, and change management.

  • Measuring the ROI of your AI insights initiatives.

• PM: Capstone Project and Ethical Governance

  • Capstone Exercise: Teams work on a comprehensive case study, from data analysis using AI techniques to creating a presentation with prescriptive recommendations for the executive team.

  • Ethical Considerations: Algorithmic bias in models, data privacy (GDPR/CCPA), and building trustworthy AI systems.

  • Course Wrap-Up: Final Presentations and Developing a Personal Action Plan.