Classification Modeling: Applications

Name: Classification Modeling: Applications
Author: Briana Brownell

Learn about real-life scenarios and the future of classification modeling

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Course: On-Demand

Now we'll talk about some of the different applications of classification models that are common. The first one is in modeling customer behavior. One of the things that companies most often want to measure and model are customer satisfaction and customer churn. In understanding why customers are satisfied and what impacts their satisfaction, the company can have a look at the overall customer journey and improve it where there are gaps. So for instance, if a company sees that customer service is a perpetual issue and that is what is the greatest predictor of an unsatisfied customer, then the company may spend resources in training materials, for example, for the service agents, in order to ameliorate that problem. Customer satisfaction is often one of the more complex styles of modeling that is done. Because each customer may have a number of different touch points, the overall model that's built must take into consideration a lot of different pieces from a lot of different areas. So typically in organizations, a customer satisfaction program that is modeled by some type of classification modeling or other styles, such as prediction, usually this is a fairly comprehensive program. The data is generally collected by way of surveys and satisfaction is measured on some kind of a scale. One of the most common ones is called the net promoter score. So what this does is it rolls up the satisfaction scores into three different groups, detractors which give low ratings, the neutral group, which give an average rating, and then the advocate group, which give a very high rating. And so what you want to see as a company is you want to have a larger group of advocates than you have detractors. So often what companies will do is they will create a classification model to see what factors cause customers to become advocates, as well as what causes them to become detractors. Modeling the opportunity to cross sell additional products is also a common classification problem that is implemented by companies. In this case, what the company is trying to do is understand which potential or current customers are most likely to want to buy a specific product. This can allow them to tailor their marketing messages and to target their campaign towards those individuals. And then finally modeling customer churn. Especially with subscription businesses, figuring out the reasons that customers cancel their service and what kinds of things are nudging them to do so can help the company understand those behaviors and hopefully spend some time on their value proposition in order to keep that customer. We've all probably heard the saying that it's easier to keep a customer than acquire a new one. Well, that's the philosophy behind doing churn modeling because you want to keep your current customers happy rather than having them cancel their service or go shop elsewhere. You want to add to your value proposition so that that customer doesn't become someone else's customer. So now you've seen a few examples of how companies use classification modeling in understanding customer behavior and how they can implement it within their operations in order to keep their customers happy and improve their value proposition.

Intermediate Provider : Briana Brownell 4 Lessons · 10m in Arabic, German, English, Spanish, French, Portuguese, Chinese

Course Description

These lessons will take you through the various applications of classification modeling in real-life scenarios. You will learn how classification modeling and AI are being used in medical imaging, diagnosis, and prevention; and how researchers are hoping to help health care around the world.

You will also learn the ways businesses are using modeling and prediction to better understand customer behavior and customer churn. These lessons will also explore the importance and uses of image classification for websites and other online businesses. Finally, you will explore what is on the horizon with classification modeling and what the future possibilities are.

What You'll Learn

Explore real-world applications of classification modeling across different industries
Examine how classification modeling and AI are used in medical imaging, diagnosis, and prevention
Analyze how businesses apply modeling and prediction to understand customer behavior and customer churn
Apply image classification techniques for websites and other online businesses
Identify the challenges faced within real-world applications of classification modeling
Investigate the future possibilities and what is on the horizon for classification modeling

Key Takeaways

Classification modeling and AI are being used in medical imaging, diagnosis, and prevention, with researchers hoping to improve health care around the world.
Businesses use modeling and prediction to better understand customer behavior and customer churn.
Image classification is important and useful for websites and other online businesses.
Real-world applications of classification modeling come with challenges that must be examined alongside their benefits.
The course explores the future possibilities of classification modeling and what is on the horizon.

Frequently Asked Questions

What does this course cover?

The course covers the various applications of classification modeling in real-life scenarios, including its use in medicine and health care, customer behavior, image classification, and future possibilities. It also examines the challenges faced within these real-world applications.

How is classification modeling applied in health care according to this course?

The course explains how classification modeling and AI are being used in medical imaging, diagnosis, and prevention, and how researchers are hoping to help health care around the world.

How can businesses use classification modeling?

The course explores how businesses use modeling and prediction to better understand customer behavior and customer churn.

What lessons are included in this course?

The course includes four lessons: Customer Behavior, Medicine and Health Care, Image Classification, and Future Possibilities.

What skills will I gain from this course?

The course covers skills including analytic applications, applications of artificial intelligence, data classification, product classification, statistical classification, and disease modeling.