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AI in Marketing and Sales

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AI in Marketing and Sales

Last Updated : July 30, 2025
F4courses
0 Lessons
0 Enrolled

About Course

This comprehensive course explores the transformative
impact of artificial intelligence across the entire
marketing and sales lifecycle. Participants will master AI
tools and methodologies for precise customer targeting
through advanced segmentation, optimizing digital
advertising campaigns with real-time bidding,
streamlining sales processes using predictive analytics
for lead scoring, and delivering hyper-personalized
customer experiences via intelligent chatbots and
dynamic content. The curriculum emphasizes practical
application, empowering students to leverage
unprecedented personalization, automation, and
actionable insights to drive significant business growth.

What Will You Learn?

  • Analyze the strategic impact of AI on core marketing funnels and sales pipelines.
  • Implement machine learning algorithms (e.g., clustering, classification) for granular customer segmentation and precise audience targeting.
  • Develop and deploy AI-powered personalization strategies for websites, emails, and social media channels.
  • Utilize predictive analytics models for accurate sales forecasting, efficient lead scoring, and identifying cross-sell/upsell opportunities.
  • Design, build, and integrate conversational AI solutions (chatbots, voice assistants) to enhance customer service and engagement.
  • Measure the ROI and optimize the performance of AI initiatives using key marketing and sales metrics.

Course Content

AI Transformation in Marketing and Sales
Explore the evolution of marketing and sales with AI, from foundational automation to advanced generative AI. Understand key technologies like NLP, computer vision, and predictive modeling driving this shift. Analyze AI maturity models for marketing organizations and dissect real-world case studies from industry leaders like Netflix (recommendations) and Amazon (personalization). Discuss emerging trends such as AI-driven content generation and the future outlook of AI in these domains.

Customer Analytics and Segmentation
Learn advanced customer segmentation techniques using unsupervised learning (e.g., K-Means, Hierarchical Clustering) with demographic, psychographic, and behavioral data. Develop predictive models for customer lifetime value (CLTV) using regression, churn prediction and prevention using classification, and next-best-action modeling with reinforcement learning. Master the creation of a 360-degree customer view by integrating diverse data sources (CRM, web analytics, social media) with machine learning.

Personalization and Recommendation Systems
Discover AI-driven content personalization strategies, including dynamic website content, personalized email campaigns, and product recommendations. Understand the mechanics of collaborative filtering and content-based recommendation algorithms (e.g., matrix factorization, deep learning-based recommenders). Implement real-time personalization techniques and omnichannel approaches (e.g., integrating online and in-store experiences), and learn to measure their effectiveness through A/B testing and conversion rates.

AI in Sales Optimization
Apply AI to predictive lead scoring and qualification using historical data and feature engineering. Enhance sales forecasting accuracy with time-series machine learning models (e.g., ARIMA, Prophet). Explore opportunity prioritization algorithms for sales teams, conversational AI for sales enablement (e.g., sales playbooks, coaching bots), and AI-driven insights for sales process optimization and territory planning based on market potential and sales representative performance.

Conversational Marketing and Chatbots
Design effective conversational experiences using Natural Language Processing (NLP) techniques like intent recognition and entity extraction for customer interaction. Gain skills in chatbot development platforms (e.g., Google Dialogflow, IBM Watson Assistant) and implementation strategies for customer support, lead qualification, and appointment booking. Understand the role of voice assistants (e.g., Amazon Alexa, Google Assistant) in marketing and sales, and learn to measure and optimize conversational AI performance metrics like resolution rate and customer satisfaction.

AI-Powered Campaign Optimization
Master predictive modeling for campaign performance (e.g., click-through rates, conversion rates) and multi-touch attribution with machine learning. Explore dynamic creative optimization (DCO) for personalized ad content, AI for programmatic media planning and buying, and automated A/B testing and multivariate experimentation for optimizing budget allocation across channels (e.g., Google Ads, Facebook Ads). Learn to interpret AI-driven insights for continuous campaign improvement.

Capstone Project
Design and develop an AI-powered marketing or sales solution addressing a specific business challenge for a chosen company (e.g., a customer churn prediction model for a subscription service, a personalized product recommendation engine for an e-commerce platform, or a predictive lead scoring tool for a B2B sales team). This project requires data acquisition planning, model selection and training, a comprehensive deployment strategy, conducting an ROI analysis based on projected business impact, and providing a technical demonstration of your solution's capabilities and user interface.

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