AI in Marketing and Customer Segmentation Training Course

Module 1: The AI-Powered Marketing Ecosystem

• Evolution of marketing: From mass media to individual-level AI targeting
• Identifying high-impact AI use cases across the customer journey
• Overview of the AI marketing stack: CDPs, automation tools, and ML platforms
• The role of Big Data in driving marketing intelligence and agility
• Understanding the "Black Box" challenge in algorithmic decision-making
• Practical session: Conducting a marketing technology audit and identifying AI gaps in a sample business case

Module 2: Data Engineering for Customer Insights

• Consolidating data: Integrating CRM, website analytics, and social media feeds
• Feature engineering for marketing: Creating behavioral, transactional, and demographic variables
• Handling imbalanced datasets in marketing (e.g., low conversion rates)
• Data cleaning and normalization protocols for consistent customer profiles
• Techniques for identity resolution and building a Single Customer View (SCV)
• Practical session: Building a customer data pipeline and engineering features for behavioral analysis

Module 3: Machine Learning for Customer Segmentation

• Moving beyond demographics: Behavioral and psychographic segmentation with AI
• Implementing K-Means and Hierarchical Clustering for automated segment discovery
• Using Principal Component Analysis (PCA) to visualize high-dimensional customer data
• RFM (Recency, Frequency, Monetary) analysis enhanced by machine learning
• Validating segments: Silhouette scores and cluster stability over time
• Practical session: Training a K-Means clustering model to identify high-value customer personas

Module 4: Predictive Analytics for Churn and Retention

• Identifying the early warning signs of customer disengagement
• Implementing classification models (Logistic Regression, XGBoost) to predict churn
• Calculating "Propensity to Buy" scores for targeted re-engagement campaigns
• Survival analysis for estimating the length of the customer relationship
• Evaluating churn models: Accuracy, precision, recall, and the Lift chart
• Practical session: Building a churn prediction model and identifying the top five risk drivers

Module 5: Customer Lifetime Value (CLV) Modeling

• Theoretical frameworks for CLV: Historic vs. Predictive modeling
• Using regression and probabilistic models (BG/NBD) to forecast future revenue
• Segmenting customers based on potential future value vs. current spend
• Allocating marketing budgets based on predicted CLV tiers
• Strategies for increasing CLV through AI-driven upsell and cross-sell
• Practical session: Implementing a predictive CLV model to forecast the 12-month value of new cohorts

Module 6: Recommendation Engines and Personalization

• Collaborative Filtering vs. Content-Based Filtering architectures
• Hybrid recommendation systems: Combining user behavior with product attributes
• Real-time personalization: Adapting website content and emails in the moment
• Measuring recommendation success: Click-through rates (CTR) and conversion lift
• Addressing the "Cold Start" problem for new users and products
• Practical session: Designing and testing a product recommendation engine for an e-commerce dataset

Module 7: Natural Language Processing (NLP) for Sentiment Analysis

• Mining customer reviews and social media mentions for brand sentiment
• Using NLP to identify emerging customer needs and pain points
• Automated topic modeling: Discovering what customers are talking about most
• Enhancing customer service through AI chatbots and automated response routing
• Analyzing competitor sentiment to identify market opportunities
• Practical session: Using a pre-trained NLP model to perform sentiment analysis on product reviews

Module 8: AI-Driven Lead Scoring and Conversion Optimization

• Moving from manual to predictive lead scoring in B2B and B2C
• Identifying high-intent behaviors through multi-touch attribution models
• Dynamic pricing: Using AI to optimize discounts and price points in real-time
• A/B testing at scale: Using Multi-Armed Bandits for continuous optimization
• Predictive website personalization: Changing UI/UX based on visitor intent
• Practical session: Developing a lead scoring algorithm to prioritize sales outreach efforts

Module 9: Generative AI for Automated Content Marketing

• Using Large Language Models (LLMs) for automated copywriting and ad generation
• Personalized email marketing at scale: Generating unique content for every user
• Visual AI: Creating custom brand imagery and social media assets
• Managing brand voice and consistency across AI-generated content
• Streamlining the creative workflow: From ideation to automated distribution
• Practical session: Creating a multi-channel campaign using generative AI tools while maintaining brand voice

Module 10: AI Marketing Ethics, Privacy, and Strategy

• Navigating GDPR, CCPA, and the ethics of consumer data tracking
• Identifying and mitigating bias in marketing algorithms and targeting
• Building transparency: Communicating AI usage to consumers effectively
• Developing a 12-month AI marketing roadmap and measuring long-term ROI
• Future trends: The shift toward cookie-less marketing and decentralized AI
• Practical session: Drafting an AI data ethics policy and a strategic implementation roadmap

Requirements:

• Participants should be reasonably proficient in English.
• Applicants must live up to Armstrong Global Institute admission criteria.

Terms and Conditions

1. Discounts: Organizations sponsoring Four Participants will have the 5th attend Free

2. What is catered for by the Course Fees: Fees cater for all requirements for the training – Learning materials, Lunches, Teas, Snacks and Certification. All participants will additionally cater for their travel and accommodation expenses, visa application, insurance, and other personal expenses.

3. Certificate Awarded: Participants are awarded Certificates of Participation at the end of the training.

4. The program content shown here is for guidance purposes only. Our continuous course improvement process may lead to changes in topics and course structure.

5. Approval of Course: Our Programs are NITA Approved. Participating organizations can therefore claim reimbursement on fees paid in accordance with NITA Rules.

Booking for Training

Simply send an email to the Training Officer on training@armstrongglobalinstitute.com and we will send you a registration form. We advise you to book early to avoid missing a seat to this training.

Or call us on +254720272325 / +254725012095 / +254724452588

Payment Options

We provide 3 payment options, choose one for your convenience, and kindly make payments at least 5 days before the Training start date to reserve your seat:

1. Groups of 5 People and Above – Cheque Payments to: Armstrong Global Training & Development Center Limited should be paid in advance, 5 days to the training.

2. Invoice: We can send a bill directly to you or your company.

3. Deposit directly into Bank Account (Account details provided upon request)

Cancellation Policy

1. Payment for all courses includes a registration fee, which is non-refundable, and equals 15% of the total sum of the course fee.

2. Participants may cancel attendance 14 days or more prior to the training commencement date.

3. No refunds will be made 14 days or less before the training commencement date. However, participants who are unable to attend may opt to attend a similar training course at a later date or send a substitute participant provided the participation criteria have been met.

Tailor Made Courses

This training course can also be customized for your institution upon request for a minimum of 5 participants. You can have it conducted at our Training Centre or at a convenient location. For further inquiries, please contact us on Tel: +254720272325 / +254725012095 / +254724452588 or Email training@armstrongglobalinstitute.com

Accommodation and Airport Transfer

Accommodation and Airport Transfer is arranged upon request and at extra cost. For reservations contact the Training Officer on Email: training@armstrongglobalinstitute.com or on Tel: +254720272325 / +254725012095 / +254724452588