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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/meaningful-marketing-insights
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课程名称：有意义的营销洞察 课程概述：随着营销人员成为组织中数据使用的主要用户，理解组织收集的各种消费者数据显得尤为重要。调查、交易历史和账单记录都能为消费者未来行为提供洞察力，前提是能够正确解读这些数据。在《营销分析导论》课程中，我们介绍了学员所需的工具，以将原始数据转化为营销洞察。课程中的练习将使用Microsoft Excel进行，确保学员具备从可用数据中提取信息的能力。课程还提供了对重要工具的接触，包括探索性数据分析和可以用来调查营销活动对聚合数据（例如销售）和个人选择数据（例如品牌选择）影响的回归方法。 课程大纲： 1. 介绍讲师德维德·施韦德尔及课程概述：在这一模块中，学员将了解讲师及课程的整体安排。 2. 数据可视化与描述性统计探索（第一部分）：本模块专注于识别适合不同类型数据的描述性统计（集中趋势和离散度测量），以及使用参考命令对数据进行重编码。此外，学员将使用Excel中的透视表对数据进行处理和汇总，生成适合分析类型的数据可视化，并解读统计和可视化结果，以得出解决相关营销问题的结论。 3. 数据可视化与描述性统计探索（第二部分）：与第一部分相似，本模块继续深入描述性统计的应用，数据处理，以及可视化结果的解读。 4. 营销数据的回归分析：在本模块中，学员将了解不同类型营销数据适用的回归类型，并进行回归分析，评估营销行动对结果（如销售、流量和品牌选择）的影响。同时，学员还需解读回归输出，以理解整体模型表现和不同预测变量的重要性，并使用合适的回归模型进行预测。 5. 从分析到行动：最后一个模块将会把回归分析的结果与营销决策联系起来。学员将学习构建工具，帮助用户根据不同的营销决策评估结果，并描述根据所选择的营销决策对结果的不确定性程度。 学习本课程需要具备Microsoft Excel。如没有Excel，您可以在此下载免费30天试用版：https://products.office.com/en-us/try
Name:Meet Dr. Schweidel & Course Overview
Description:In this module, students will be introduced to the instructor, Dr. David Schweidel and get and overview of the course.
Name:Exploring your Data with Visualization and Descriptive Statistics, Part 1
Description:Modules 2 and 3 focus on identifying appropriate descriptive statistics (measures of central tendency and dispersion) for different types of data, as well as recoding data using reference commands to prepare it for analysis. Additionally, you will manipulate and summarize data using pivot tables in Excel, produce visualizations that are appropriate based on the type of data being analyzed, and interpret statistics and visualizations to draw conclusions to address relevant marketing questions.
Name:Exploring your Data with Visualization and Descriptive Statistics, Part 2
Description:Modules 2 and 3 focus on identifying appropriate descriptive statistics (measures of central tendency and dispersion) for different types of data, as well as recoding data using reference commands to prepare it for analysis. Additionally, you will manipulate and summarize data using pivot tables in Excel, produce visualizations that are appropriate based on the type of data being analyzed, and interpret statistics and visualizations to draw conclusions to address relevant marketing questions.
Name:Regression Analysis for Marketing Data
Description:In this module, you will be asked to determine the appropriate type of regression for different types of marketing data and will perform regression analysis to assess the impact of marketing actions on outcomes of interest, such as sales, traffic, and brand choices. You will also be asked to interpret regression output to understand overall model performance and importance of different predictors, as well as make predictions using the appropriate regression model.
Name:From Analysis to Action
Description:This final module will connect the results of regression analysis to marketing decisions. You will learn to build tools that allow users to evaluate outcomes based on different marketing decisions, as well as characterize the extent of uncertainty in outcomes based on the selected marketing decisions.
With marketers are poised to be the largest users of data within the organization, there is a need to make sense of the variety of consumer data that the organization collects. Surveys, transaction histories and billing records can all provide insight into consumers’ future behavior, provided that they are interpreted correctly. In Introduction to Marketing Analytics, we introduce the tools that learners will need to convert raw data into marketing insights. The included exercises are conducted using Microsoft Excel, ensuring that learners will have the tools they need to extract information from the data available to them. The course provides learners with exposure to essential tools including exploratory data analysis, as well as regression methods that can be used to investigate the impact of marketing activity on aggregate data (e.g., sales) and on individual-level choice data (e.g., brand choices). To successfully complete the assignments in this course, you will require Microsoft Excel. If you do not have Excel, you can download a free 30-day trial here: https://products.office.com/en-us/try
