How does document categorization work?
Document categorization works by grouping files based on content, characteristics, or purpose. The process varies according to the method you use. For example, an HR department can manually organize resumes by job title or let software automatically label them based on key terms.
Let’s review the most common ways of categorizing documents and the key steps to organize content faster and with fewer mistakes.
Key highlights:
- The document categorization process involves defining categories, tagging documents, testing your system, and using tools to sort content faster and more accurately
- Common document categorization methods include rule-based systems, clustering, machine learning, and semantic analysis
- Document categorization and classification are distinct concepts — classification assigns documents to predefined categories, often using machine learning, while categorization broadly groups them by topic, type, use, or other criteria
- Box helps you categorize files with document management and intelligent content workflows so they stay secure and easy to access
What does it mean to categorize files and documents?
Categorizing files and documents means organizing them with precise criteria that align with your business needs. For instance, if your customer support team needs rapid access to onboarding materials, you can label these files with descriptive names or tags and store them in a dedicated folder within your document management system (DMS).
This process streamlines digital asset management by reducing search time and creating a more organized and accessible workspace. Document categorization also brings other benefits.
- Better compliance and risk management: By creating categories based on sensitivity or regulatory needs, you simplify tracking and disposal in line with compliance requirements
- Improved workflow efficiency: Implementing digital workflow automation is easier with a clear categorization system — labeled, structured documents allow automation tools to process and retrieve files without manual intervention, saving time spent on those tasks
- Enhanced data analysis: Integrating technologies like artificial intelligence (AI) into categorization makes it easier to pull out insights from your documents — for example, extracting trends from customer feedback to improve your products, services, or marketing strategies
Learn how Intelligent Content Management platforms unlock more value from your data.
Examples of content categorization
Here are a few content categorization methods you could try:
- By content: Define categories of documents based on the subject or topic they cover, such as marketing materials, research papers, and technical documentation
- By characteristic: Categorize documents according to their format, metadata, or other attributes — for instance, organizing files by sensitivity level (confidential, public, internal)
- By purpose: Create document categories for various uses, like training manuals and content subject to record retention policies
Key document categorization methods
You can set up document categories by hand, but maintaining a manual system is like organizing a library with sticky notes — it can quickly turn into chaos as files multiply. Managing increasing data is challenging for many organizations, which is why the document management system market is on the rise. A forecast by Fortune Business Insights projects that the DMS market will grow from $7.16B in 2024 to $24.91B by 2032, with a CAGR of 16.9% during that period. To prevent mistakes and simplify the document management process, consider these four file categorization methods.
1. Rule-based categorization
Rule-based categorization typically works by matching keywords, patterns, or metadata. This method starts with manual setup to define the rules, but once that’s done, the process runs automatically. For example, if a piece of content within your cloud storage system contains the word “invoice” and a dollar amount, you can create a rule to file it under the document category “financial records.” A rule-based system works well for structured data and predictable document types, where consistent patterns make rule-setting straightforward.
2. Clustering
This type of categorization groups documents based on similarities. For example, in life sciences, researchers can organize scientific papers by topic or field of study, making it easier to navigate large volumes of content. Creating clusters allows you to manage unstructured data and label documents without clear categories.
3. Machine learning-based categorization
This method uses document categorization software powered by ML algorithms that identify patterns to label new documents automatically. It’s a good choice for handling complex content and plays a key role in intelligent document processing (IDP), enabling automatic extraction, categorization, and processing of data from contracts, medical records, purchase orders, and other documents.
4. Semantic analysis
This categorization method relies on natural language processing (NLP) to analyze and interpret the content of documents, grouping them based on meaning. For example, your sales department can identify and prioritize leads based on the sentiment expressed in their communications, focusing on categorized documents with positive signals.
Understanding the difference between classification and categorization of documents
Document classification and categorization might sound similar, but they’re not the same. Take a look at the nuances that set these concepts apart.
| Process | Document classification | Document categorization |
| Definition | A strict, limited process that relies on tools to assign documents to specific classifications based on predefined rules, sensitivity levels, or compliance needs | AA broad, flexible process of grouping documents based on diverse criteria like topic, type, or metadata — which you can do manually or with the help of content management platforms |
| Purpose | Automatically or systematically classify documents, often to restrict access and meet compliance standards | Organize documents to establish a hierarchical and interconnected system that facilitates retrieval, analysis, and management |
| Performed by | Automated systems, data scientists, compliance officers, or any other individuals who need to ensure accurate classification for security, compliance, or other legal purposes | Any person who needs to group documents based on specific needs — like a publisher organizing content for publication according to a calendar |
| Methods | Often integrates machine learning (ML) for automated classification | Can include both manual and automated document categorization |
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Why your business needs file categorization
Without a clear system for organizing content, you create information silos that hinder business productivity, collaboration, and decision-making. AIIM’s State of the Intelligent Information Management Industry shows that one of the top roadblocks to digital transformation is the lack of a solid strategy for managing information assets. This challenge includes critical processes like categorizing documentation. To address these concerns, here’s a structured approach to categorize your documents.
How to categorize documents in five steps
Here’s a quick guide on how to categorize documents — remember to adapt the process to suit the type and volume of information you manage.
1. Create document categories and subcategories
Review how departments interact with different types of documents. This practice helps develop a folder structure with consistent naming conventions and implement robust data security and compliance controls.
Consider whether you want to give users the freedom to create and organize their own folders or if you’d prefer that administrators manage file and folder permissions and hierarchy. Begin by defining main categories (like “contracts,” if you work in legal), then break them down into subcategories (for example, “vendor contracts”).
Next, use cloud workspaces and portals to categorize documents by department or project, making it easier to manage permissions and collaborate on files.
2. Choose a document categorization method
Think about your document collection: is it structured, unstructured, or a mix of both? See how they differ:
- Structured content: Data organized in a predefined format, such as spreadsheets, databases, or forms, making it easy to process and analyze
- Unstructured content: Data that lacks a defined format, including product descriptions, research papers, and multimedia content
Understanding the nature of your files will help you choose the right categorization method. Many systems use a hybrid approach, combining rule-based methods for specific documents and ML for general automatic categorization. Don’t forget to consider your team’s experience — choose a system that’s easy for them to maintain.
3. Apply metadata and tags to enable easy document retrieval
Metadata includes information like the document’s author, date created, keywords, and other relevant details. By tagging documents with metadata, you help your system quickly understand what the document is about, making it easier to retrieve later.
When selecting your document categorization software, choose a solution that facilitates enterprise metadata management so you can automate metadata extraction and tagging, reducing manual effort and errors.
4. Review and test your content categorization system
Select a few documents and check if you categorized them correctly. Can you easily find what you need? If you’re using an automated document categorization system, does it apply your rules correctly? Refine your system based on team feedback and test results, and adapt it to changing information needs and business processes.
5. Use automated document categorization tools that align with your workflows
Whether it’s cloud storage or document management software, make sure the platform you use integrates with your existing workflows and supports automated document categorization. According to the ODSC’s 2025 AI Trends and Adoption Survey, 76% of data scientists and AI practitioners say workplace automation will be the most impactful AI trend in the coming years.
To strengthen your business process automation strategy, look for features like AI-powered document processing, intelligent document retrieval, and metadata extraction.
Explore the basic steps to build a successful enterprise AI strategy.
Keep your categorized documents organized and secure with Box
With Box, you organize your files efficiently and securely in the cloud. Our leading Intelligent Content Management platform combines storage, document management, and AI-powered capabilities to automate workflows and maximize the value of your content.
By offering a single source of truth to manage and govern documents, Box equips you with:
- Workspaces and portals to categorize and locate files faster via Box Hubs
- Box AI to build intelligent workflows that speed up content creation and extract insights from your unstructured data
- Real-time co-editing through Box Notes, where teams collaborate effortlessly and you organize documents in collections
- Security and compliance to encrypt and control access to your sensitive information
- Box app integrations to connect your content across +1,500 platforms so you can build document-centric processes with a seamless, unified experience
Let’s connect and discuss how to power up document categorization with Box.
*While we maintain our steadfast commitment to offering products and services with best-in-class privacy, security, and compliance, the information provided in this blog post is not intended to constitute legal advice. We strongly encourage prospective and current customers to perform their own due diligence when assessing compliance with applicable laws.