In this specialization you will learn how to:
• Find, extract, organize and describe data to support business decisions
• Identify, quantify and interpret relationships between variables
• Derive customer insights from your data
• Develop spreadsheet models to analyze data, evaluate risk and optimize business decisions
• Present and justify a course of action to management
The capstone project will give you an opportunity to apply what has been covered in the specialization to solve a marketing analytics problem.
專項課程 的運作方式
加入課程
Coursera 專項課程是幫助您掌握一門技能的一系列課程。若要開始學習，請直接註冊專項課程，或預覽專項課程並選擇您要首先開始學習的課程。當您訂閱專項課程的部分課程時，您將自動訂閱整個專項課程。您可以只完成一門課程，您可以隨時暫停學習或結束訂閱。訪問您的學生面板，跟踪您的課程註冊情況和進度。
實踐項目
每個專項課程都包括實踐項目。您需要成功完成這個（些）項目才能完成專項課程並獲得證書。如果專項課程中包括單獨的實踐項目課程，則需要在開始之前完成其他所有課程。
獲得證書
在結束每門課程並完成實踐項目之後，您會獲得一個證書，您可以向您的潛在雇主展示該證書並在您的職業社交網絡中分享。
此專項課程包含 6 門課程
課程1
Meaningful Marketing Insights
4.4
112 個評分
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
課程2
Managing Uncertainty in Marketing Analytics
4.2
34 個評分
Marketers must make the best decisions based on the information presented to them. Rarely will they have all the information necessary to predict what consumers will do with complete certainty. By incorporating uncertainty into the decisions that they make, they can anticipate a wide range of possible outcomes and recognize the extent of uncertainty on the decisions that they make. In Incorporating Uncertainty into Marketing Decisions, learners will become familiar with different methods to recognize sources of uncertainty that may affect the marketing decisions they ultimately make. We eschew specialized software and provide learners with the foundational knowledge they need to develop sophisticated marketing models in a basic spreadsheet environment. Topics include the development and application of Monte Carlo simulations, and the use of probability distributions to characterize uncertainty.
課程3
Forecasting Models for Marketing Decisions
4.2
39 個評分
How will customers act in the future? What will demand for our products and services be? How much inventory should we order for the next season? Beyond simply forecasting what customers will do, marketers need to understand how their actions can shape future behavior. In Developing Forecasting Tools with Excel, learners will develop an understanding of the basic components of a forecasting model, how to build their own forecasting models, and how to evaluate the performance of forecasting models. All of this is done using Microsoft Excel, ensuring that learners can take their skills and apply them to their own business problems.
課程4
Survey analysis to Gain Marketing Insights
4.3
30 個評分
How do consumers see your brand relative to your competitors? How should a new product be positioned when it’s launched? Which customer segments are most interested in our current offerings? For these questions and many others, surveys remain the tried and true method for gaining marketing insights. From one-off customer satisfaction surveys to brand tracking surveys that are administered on a continuous basis, they provide the information that marketers need to understand how their products, services and brands are seen by consumers. In Analytic Methods for Survey Data, learners will become familiar with established statistical methods for converting survey responses to insights that can support marketing decisions. Techniques discussed include factor analytics, cluster analysis, discriminant analysis and multi-dimensional scaling. These techniques are presented within the STP (Segmentation, Positioning, Targeting) Framework, enabling learners to apply the analytic techniques to develop a marketing strategy. It is recommended that you complete the Meaningful Marketing Insights course offered by Coursera before taking this course.
Note: This course would require using XL Stat, an Excel Add-on that students would need to purchase. XL Stat offers a 30-day free trial, so students could complete this course without incurring additional expense.
講師
David Schweidel
Associate Professor of MarketingGoizueta Business School
關於 艾莫利大学
Emory University, located in Atlanta, Georgia, is one of the world's leading research universities. Its mission is to create, preserve, teach and apply knowledge in the service of humanity.
常見問題
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可以！点击您感兴趣的课程卡开始注册即可。注册并完成课程后，您可以获得可共享的证书，或者您也可以旁听该课程免费查看课程资料。如果您订阅的课程是某专项课程的一部分，系统会自动为您订阅完整的专项课程。访问您的学生面板，跟踪您的进度。
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我可以免费学习课程吗？
此课程是 100% 在线学习吗？是否需要现场参加课程？
此课程完全在线学习，无需到教室现场上课。您可以通过网络或移动设备随时随地访问课程视频、阅读材料和作业。
完成专项课程后我会获得大学学分吗？
此专项课程不提供大学学分，但部分大学可能会选择接受专项课程证书作为学分。查看您的合作院校了解详情。
完成专项课程需要多长时间？
Courses are designed to be self-paced.
What background knowledge is necessary?
This specialization is designed for learners that are familiar with business and marketing concepts, as well as have some experience with statistics.
Do I need to take the courses in a specific order?
It is recommended, but not required, that learners complete courses in the order in which they are presented, as some content builds off of previous concepts.
What will I be able to do upon completing the Specialization?
After taking this specialization, the learner will be able to apply for marketing analytics and insight roles that require data analysis; be familiar with techniques to summarize and describe data; analyze survey data by identifying key themes and customer segments; use Excel to build interactive decision support tools; and build statistical models to forecast customer behavior.
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