# Classification Models

### Customer Service

Improving customer service systems is one of the most active areas for deploying language understanding systems. Let’s look at a couple of examples where text classifiers improve these systems.

#### Topic classification and message routing

For businesses that deal with a large volume of inbound communication, a lot of time and effort can be saved by automatically routing customer messages to the people who can resolve them.

<img src="../img/fern/assets/images/aaccf8f-image.png" alt="">
This routing can either be actually forwarding an email or integrating with Customer Service software (like Zendesk or Freshdesk) that assigns the relevant person to look at the ticket.

A more advanced system is one that can automatically answer frequently asked questions instead of routing them to agents to answer them repeatedly. This is a common use case for chatbots to handle.

#### Chatbots and intent classification

Modern chatbots can be used to answer commonly asked user questions.

<img src="../img/fern/assets/images/b854425-image.png" alt="">
Text classification is a cornerstone of how these systems work. More specifically, most chatbots employ a classifier that detects the intent behind the user’s message. Intents are broader than topic classifiers as they include intents like “greeting” that enable them to react when a user says “hi” or “bye”, for example.

<img src="../img/fern/assets/images/cb2a64d-image.png" alt="">
Chatbots tend to pair intent classifiers with entity extractors – another language processing functionality to extract the “breakfast special” from a menu item question so the system knows exactly which item the user is asking about.

#### Content Moderation

A significant portion of human interaction now happens online through social media, online forums, and group chats (like Discord or Slack). More often than not, these online communities [need moderation to keep their communities safe](https://cohere.com/blog/cohere-for-content-moderation/) from different types of online harm. Language understanding systems can empower moderation teams in combating toxic, abusive, and hateful language.

A content filter can classify texts as either neutral or toxic:

<img src="../img/fern/assets/images/91296cb-image.png" alt="">
In [Content Moderation with Classify](https://docs.cohere.ai/classify-content-mod?ref=txt.cohere.com&amp;__hstc=14363112.fb39cf5aec47995e64cd26603e2e04d9.1682489949734.1683571482981.1683573460217.34&amp;__hssc=14363112.27.1683573460217&amp;__hsfp=3887566761), we show how you can build such a classifier with [Classify](https://docs.cohere.ai/text-classification?ref=txt.cohere.com&amp;__hstc=14363112.fb39cf5aec47995e64cd26603e2e04d9.1682489949734.1683571482981.1683573460217.34&amp;__hssc=14363112.27.1683573460217&amp;__hsfp=3887566761). This includes the ability to finetune a model on your labeled data so the classifier can specialize to solve this problem.

### Other text classification problems

Building the best classifier and evaluating it for a specific dataset is a deep topic with a rich history and plenty of ongoing work. But for a developer just approaching the topic, this article aims to communicate the intuition of how to think of text classification as a language understanding capability that can improve software systems that handle text and communication.

<img src="../img/fern/assets/images/3b8e370-image.png" alt="">
If you're able to map real-world problems to text classification problems, that's a good first step to start your path in creating language processing systems.

### Conclusion

In this chapter you learned what a classification model is, and how they can be used for numerous applications.

[https://txt.cohere.com/text-classification-use-cases/](https://cohere.com/blog/text-classification-use-cases/)

### Original Source

This material comes from the post [Text Classification Intuition for Software Developers](https://cohere.com/blog/text-classification-use-cases/)

## Related pages

- [Changelog](../changelog.md)
- [Cohere](../index.md)
- [Cohere API](./cohere-api-index.md)
- [Cohere Labs](./cohere-labs-index.md)
- [Cohere Platform](./cohere-platform-index.md)
- [Cookbooks](./cookbooks-index.md)
- [Deployment Options](./deployment-options-index.md)
- [Embeddings (Vectors, Search, Retrieval)](./embeddings-vectors-search-retrieval-index.md)
- [Get Started](./get-started-index.md)
- [Going to Production](./going-to-production-index.md)

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