Marketing Analytics
本课程教授如何运用数据分析方法衡量和优化营销效果。课程内容包括：营销度量指标体系（ROI、CLV、转化率、获客成本等）、营销组合模型（MMM）、客户分群与RFM分析、A/B测试与实验设计、归因分析模型、预测建模与机器学习在营销中的应用、营销仪表盘设计。学生将使用Excel、Python等工具进行实际数据分析。
This course teaches how to use data analysis methods to measure and optimize marketing effectiveness. Topics include marketing metrics framework (ROI, CLV, conversion rate, customer acquisition cost), marketing mix modeling (MMM), customer segmentation and RFM analysis, A/B testing and experimental design, attribution analysis models, predictive modeling and machine learning in marketing, and marketing dashboard design. Students use Excel and Python for hands-on data analysis.
学生使用真实或模拟的企业营销数据集（包括销售数据、广告投放数据、用户行为数据等），完成完整的营销分析项目。内容包括：数据清洗与探索性分析、关键营销指标计算与诊断、客户分群与画像、营销活动效果评估与归因分析、A/B测试结果解读、基于数据的营销优化建议、以及制作交互式营销仪表盘。
Students work with real or simulated enterprise marketing datasets (including sales data, advertising data, user behavior data) to complete a comprehensive marketing analytics project. The project includes data cleaning and exploratory analysis, key marketing metrics calculation and diagnosis, customer segmentation and profiling, campaign effectiveness evaluation and attribution analysis, A/B test result interpretation, data-driven marketing optimization recommendations, and an interactive marketing dashboard.