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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/data-analytics-methods-for-marketing
课程评论：没有评论
课程名称：营销数据分析方法 课程概述：本课程探讨营销人员常用的数据分析方法。您将学习如何通过K均值聚类定义目标受众，探索线性回归如何帮助营销人员进行计划和预测。此外，您将学习使用实验和观察方法评估广告的效果，并探索优化营销组合的方法，包括营销组合建模和归因分析。最后，您将学习评估和优化销售漏斗形状。 完成该课程后，您将能够： - 描述数据分析在营销中最常用的场景 - 使用分析和变量描述理解受众 - 使用聚类分析将人群细分为不同的受众 - 利用历史数据规划多渠道营销 - 使用线性回归预测营销结果 - 描述营销组合建模 - 描述归因模型及其应用 - 评估广告效果并描述其不足之处 - 描述使用实验评估广告效果的方法 - 解释A/B测试的工作原理以及如何利用其优化广告 - 评估实验结果并评估实验的有效性 - 评估和优化销售漏斗 本课程适合希望学习如何规划和预测营销工作，以及评估和优化营销方法和销售漏斗的人士。学习者无须具备营销或数据分析经验，但应具备基本的互联网导航技能，并乐于参与。理想学习者已经完成该项目的第一课程（营销分析基础）、第二课程（数据分析入门）和第三课程（营销统计）。 课程大纲： 1. 发现受众与细分 - 描述：第一周，您将学习细分在营销中的重要性以及使用细分确定目标受众的不同方法。 2. 规划和预测的分析 - 描述：本周您将概述营销的常见描述性指标，包括广告支出回报率和投资回报率。您将了解到客户生命周期价值的重要性及如何利用线性回归分析进行营销结果预测。 3. 评估广告效果 - 描述：在第三周，您将深入使用实验评估营销效果，学习A/B测试及其如何帮助优化您的活动。 4. 优化营销组合 - 描述：在最后一周，您将学习营销组合建模和不同的归因模型，以及如何使用它们提出营销策略建议。您将学习可视化和分析销售漏斗，并使用这些信息来推荐营销活动的后续步骤。
Name:Find Your Audience With Segmentation
Description:In the first week you will learn about the importance of segmentation in marketing and different methods to use segmentation to determine target audiences for your marketing.
Name:Analytics for Planning and Forecasting
Description:This week you will get an overview of common descriptive metrics for marketing, including Return on Ad Spend and Return on Investment. You will be introduced to the importance of Customer Lifetime Value and how to forecast marketing outcomes using linear regression analysis.
Name:Evaluating Advertising Effectiveness
Description:In week three, you’ll dig into using experiments to evaluate marketing effectiveness. You’ll also learn about A/B testing and how it can help you optimize your campaigns.
Name:Optimizing Your Marketing Mix
Description:In the final week, you will be introduced to marketing mix modeling and different attribution models and how to use them to make marketing strategy recommendations. You’ll wrap up the week by learning how to visualize and analyze sales funnels and how to use them to recommend next steps in a marketing campaign.
This course explores common analytics methods used by marketers. You’ll learn how to define a target audience using segmentation with K-means clustering. You’ll also explore how linear regression can help marketers plan and forecast. You’ll learn to evaluate the effectiveness of advertising using experiments as well as observational methods and you’ll explore methods to optimize your marketing mix; marketing mix modeling and attribution. Finally, you’ll learn to evaluate sales funnel shapes, visualize and optimize them. By the end of this course you will be able to: • Describe when analytics is most commonly used in marketing • Understand your audience using analytics and variable descriptions • Segment a population into different audiences using cluster analysis • Use historical data to plan your marketing across different channels • Use linear regression to forecast marketing outcomes • Describe marketing mix modeling • Describe attribution modeling • Apply different attribution models • Evaluate advertising effectiveness and describe the shortcomings • Describe the use of experiments to evaluate advertising effectiveness • Explain how A/B testing works and how you can use it to optimize ads • Evaluate results of an experiment and assess the strength of the experiment • Evaluate and optimize your sales funnel This course is for people who want to learn how to plan and forecast marketing efforts as well as evaluate marketing methods and sales funnels for optimization. Learners don't need marketing or data analysis experience, but should have basic internet navigation skills and be eager to participate. Ideally learners have already completed course 1 (Marketing Analytics Foundation), course 2 (Introduction to Data Analytics), and course 3 (Statistics for Marketing) in this program.
