Ai For B2B Marketing

Harnessing Machine Learning to Transform B2B Marketing Strategies and Drive Business Growth

What you'll learn

Build B2B Marketing Models using Machine Learning

Start Marketing of your Business with understanding of B2B Intent data and propensity of Ad Sales

Prioritize Business Marketing with Machine Learning

Augment Marketing Department with AI B2B Models

Requirements

Basic Machine Learning

Description

In today's rapidly evolving business landscape, leveraging artificial intelligence (AI) has become essential for effective B2B marketing. This course, AI for B2B Marketing, is designed for individuals with beginner to intermediate experience in machine learning who are eager to apply these skills in a business context.Participants will explore how to build robust B2B marketing models utilizing machine learning techniques, enabling them to make data-driven decisions that enhance marketing effectiveness. You will learn to identify and interpret B2B intent data, gaining insights into customer behavior and preferences. This understanding will empower you to prioritize marketing efforts based on the propensity for ad sales, ensuring your strategies align with customer needs.The course also focuses on augmenting traditional marketing departments with AI-driven models, providing you with the tools to optimize campaigns and improve ROI. Through practical exercises and real-world examples, you will develop the skills necessary to implement machine learning solutions that can transform your business’s marketing approach.By the end of the course, you will be equipped to build, analyze, and implement innovative marketing strategies that drive engagement and growth in the B2B sector. Join us to elevate your marketing expertise and harness the power of AI in your business!

Overview

Section 1: Introduction

Lecture 1 Introduction

Lecture 2 Overview of Intent Prediction

Lecture 3 Import Dataset

Lecture 4 Build Function for Feedback Score

Lecture 5 Encode Data

Lecture 6 Build Logistic Model

Lecture 7 Confusion Matrix

Lecture 8 Create Prediction Result

Lecture 9 Generalized Linear Model

Lecture 10 Build Intent Prediction results

Lecture 11 Draw ROC AUC Curve

Section 2: Propensity Model for Buy Product

Lecture 12 Introduction

Lecture 13 Import Dataset

Lecture 14 Visualize Data

Lecture 15 Feature Selection Lasso-Ridge Regularization

Lecture 16 Feature Selection and Elimination

Lecture 17 Display Selected Features

Lecture 18 Display Selected Features Contd

Lecture 19 Build Model Pipeline

Lecture 20 Build Model Pipeline Contd

Lecture 21 Build Deeplearning Model

Lecture 22 Voting Classifier

Lecture 23 Implement Voting Classifier

Lecture 24 Model Predictions

Section 3: Customer Life Time Value Prediction - Pending

Lecture 25 CLTV Import Data

Lecture 26 Introduction to Gamma Distribution

Lecture 27 Analyze Dataset

Lecture 28 Find Outliers

Lecture 29 Perform Data Aggregation

Lecture 30 Recency, Frequency, Monetary Calculation

Lecture 31 Implement BetaGeoFitter for prediction

Lecture 32 Implement Gamma Model for prediction

Lecture 33 CLTV Segmentation

Lecture 34 Compare Frequency of Customers Actual Vs Predicted

Beginner and Intermediate Experience in Machine learning. Anyone who is looking to Build B2B Business.