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所在平台: Udemy |
课程主页: https://www.udemy.com/course/machine-learning-for-campaign-management/
课程评论：没有评论
课程名称：机器学习与营销活动管理 课程概述： 在数据驱动营销的时代，成功的营销活动依赖于洞察和智能优化。本课程——机器学习与营销活动管理，旨在为营销人员、数据分析师及有志于成为数据科学家的学员提供利用机器学习转变营销活动的工具和技术。从活动趋势分析到收入优化，本全面课程涵盖了营销活动管理的各个方面。 课程亮点： 1. **引言**：深入分析Google广告支出、最佳关键词及活动趋势，了解活动环境。学习如何有效地可视化活动支出结果。 2. **机器学习进行活动预测**：探索预测模型的强大功能。学习如何预处理数据集、构建集成模型，并执行活动管道，以预测活动表现和优化转化率。 3. **活动趋势分析**：识别并分析新兴活动趋势。获得构建和可视化趋势模型的实践经验，以便做出明智决策。 4. **活动比较 - 收入优化**：掌握比较分析技术，以预测预算与转化率并可视化基准，从而优化多个活动的收入。 5. **活动曝光预测**：深入了解数据管道，使用随机森林和梯度提升构建机器学习模型，以预测Instagram、Google和Facebook等平台的曝光量。 6. **使用随机森林模型进行点击预测**：利用随机森林模型预测点击率。学习构建和执行模型管道，扩展数据集并提供可行的洞见。 7. **市场细分分析**：探索细分分析以了解客户留存和市场分割。使用先进的技术如K均值聚类和RFM（近期、频率、货币）评分来可视化和解释市场数据。 8. **利润提升模型**：构建以利润为中心的模型，结合逻辑回归、XGBoost和利润估算公式。学习使用SMOTE处理不平衡数据集，并开发利润曲线以增强决策能力。 9. **产品购买意愿模型**：构建意愿模型以预测客户购买行为，并制定有针对性的营销策略。 本课程将理论知识与实践实施相结合，确保您能获得活动预测、优化与分析的实践经验。课程结束时，您将掌握设计数据驱动的营销活动的专业技能，实现最大化的盈利能力和效率。 立即注册，利用机器学习的力量，转变您的营销活动管理方式！
In the age of data-driven marketing, campaigns thrive on insights and intelligent optimization. This course, Machine Learning for Campaign Management, is designed to empower marketers, data analysts, and aspiring data scientists with the tools and techniques to transform marketing campaigns using machine learning. From campaign trend analysis to revenue optimization, this comprehensive course covers every facet of campaign management.Course Highlights:1. Introduction: Understand your campaign's landscape with an in-depth analysis of Google Ad spends, top-performing keywords, and campaign trends. Learn how to visualize campaign spend results effectively.2. Campaign Prediction Using Machine Learning: Discover the power of predictive models. Learn how to preprocess datasets, build ensemble models, and execute campaign pipelines to anticipate campaign performance and optimize conversion rates.3. Campaign Trend Analysis: Identify and analyze emerging campaign trends. Gain hands-on experience building and visualizing trend models to make informed decisions.4. Campaign Comparison - Revenue Optimization: Master comparative analysis techniques to forecast budget vs. conversion rates and visualize benchmarks to optimize revenue across multiple campaigns.5. Campaign Impression Prediction: Dive deep into data pipelines and build machine learning models using Random Forest and Gradient Boosting to predict impressions for platforms like Instagram, Google, and Facebook.6. Click Prediction Using Random Forest Models: Leverage Random Forest models to predict click rates. Learn to build and execute model pipelines, scale datasets, and deliver actionable insights.7. Marketing Cohort Analysis: Explore cohort analysis to understand customer retention and segmentation. Use advanced techniques like K-Means clustering and RFM (Recency, Frequency, Monetary) scoring to visualize and interpret marketing data.8. Profit Booster Model: Build profit-centric models that incorporate logistic regression, XGBoost, and profit estimation equations. Learn to use SMOTE for handling imbalanced datasets and develop profit curves for enhanced decision-making.9. Propensity Model for Product Purchase: Build propensity models to predict customer purchase behavior and develop targeted marketing strategies.This course blends theoretical knowledge with practical implementations, ensuring that you gain hands-on experience in campaign prediction, optimization, and analysis. By the end of this course, you'll be equipped with the expertise to design data-driven marketing campaigns that achieve maximum profitability and efficiency.Enroll now to transform your approach to campaign management with the power of Machine Learning!
