课程
Choice Modeling for Marketing in R
高级技能水平
更新时间 2024年8月
RProbability & Statistics4小时17 视频54 道练习4,100 XP6,935成就证明
创建您的免费帐户
继续使用 Google显示更多选项或
继续操作即表示您接受我们的《使用条款》和《隐私政策》,并同意您的数据存储在美国。
深受数千家公司学习者的喜爱
需要团队培训?
企业版试用课程描述
先决条件
Intermediate Regression in R1
Quickstart Guide
Our goal for this chapter is to get you through the entire choice modeling process as quickly as possible, so that you get a broad understanding of what we can do with choice models and how the choice modeling process works. The main idea here is that we can use a choice model to understand how customers' product choices depend on the features of those products. Do sportscar buyers prefer manual transmissions to automatic? By how much? In order to give you an overview, we will skip over many of the details. In later chapters, we will go back and cover important issues in preparing data, specifying and interpreting models and reporting your findings, so that you are fully prepared to use these methods with your own choice data.
2
Managing and Summarizing Choice Data
There are many different places to get choice data and different ways it can be formatted. In this chapter, we will take data that is provided in several alternative formats and learn how to get it into shape for choice modeling. We will also discuss how you can build a survey to collect your own choice data.
3
Building Choice Models
In this chapter, we take deeper dive into estimating choice models. To give you a foundation for thinking about choice models, we will focus on how the multinomial logit model converts the product features into a prediction for what the decision maker will choose. This will give you a framework for making decisions about which features to include in your model.
4
Hierarchical Choice Models
Different people have different tastes and preferences. This seems intuitively obvious, but there is also extensive research in marketing showing that this is true. This chapter covers choice models where we assume that different decision makers have different preferences that influence their choices. When our models recognize that different consumers have different preferences, they tend to make larger share predictions for niche products that appeal to a subset of consumers. Hierarchical models are used in most commercial choice modeling applications, so it is important to understand how they work.
Choice Modeling for Marketing in R
课程完成 加入超过19百万学习者,今天就开始Choice Modeling for Marketing in R!
创建您的免费帐户
继续使用 Google显示更多选项或
继续操作即表示您接受我们的《使用条款》和《隐私政策》,并同意您的数据存储在美国。
通过 DataCamp for Mobile 提升您的数据技能
随时随地通过我们的移动课程和每日 5 分钟编程挑战提升技能。