Tags - Article

Overview

Tags are one of the most powerful and foundational configuration mechanisms in the platform.

They form the taxonomy that connects users, content, and automation rules, allowing the platform to deliver training dynamically based on audience characteristics, organizational structure, or content relevance.

In practice, tags are used to describe attributes such as:

• Job roles
• Organizational structures
• Geographic regions
• Product focus
• Training priority
• Audience categories

Because these attributes can be attached to both users and training content, the platform can intelligently connect the right audience with the right training.

For example, tags may determine:

• Which courses appear in a storefront
• Which users receive a training assignment
• Which announcements are displayed to specific audiences
• Which discount campaigns apply to a specific group
• Which onboarding automations are triggered
• Which learning pages are recommended to a specific job role

This means that tags are not simply labels — they are the classification framework that powers many of the platform’s advanced features. When designed well, tags allow organizations to deliver training experiences that feel relevant, personalized, and scalable.

Tags As Platform Taxonomy

Tags are organized into vocabularies, which represent categories of classification. A vocabulary defines the type of attribute, while individual tags represent the values within that category.

For example, a vocabulary called Job Function may include values such as:

• Sales
• Field Technician
• Customer Support
• Manager

A vocabulary called Region may include:

• Europe
• North America
• Asia-Pacific

These vocabularies act as shared reference points across the platform. Because the same tag can be attached to both users and content, the system can automatically determine which learning experiences are most relevant for each user.

This shared classification structure is what allows features such as storefront targeting, automation rules, and learning recommendations to operate effectively.

Where Tags Are Configured

Tags are managed under: Settings → Tags.

From this page administrators can:

• Create and manage vocabularies
• Add or modify tag values within each vocabulary
• Control where specific vocabularies are used in the platform
• Control whether a vocabulary is active or deactivated, depending on whether it should be available for use in the platform

Administrators can activate or deactivate vocabularies using the More (⋯) menu next to each vocabulary. Deactivating a vocabulary hides it from configuration interfaces such as course settings, activity settings, and user profiles, while keeping the vocabulary and its tags stored in the system. This allows administrators to temporarily disable a classification structure without removing existing data or historical references.

Once created, tags become available across multiple areas of the platform where classification or targeting is supported.

Because tags can influence many other features, changes should be made thoughtfully and with awareness of how they may affect automation rules, storefront targeting, or content organization.

For example, modifying or removing a tag that is referenced in automation rules or storefront targeting may change how those configurations behave.

Language Management And Regional Terminology

Tags represent user-generated taxonomy, which means they must often reflect terminology used by different audiences or regions. In global organizations, product names, job titles, or organizational structures may vary across countries or markets.

For example:

• A product may be marketed under different names in different regions
• A role such as Field Engineer may be known as Service Technician in another market
• A training category used internally may differ from the terminology used in partner or customer environments

Because of this, administrators should consider language and regional differences when designing tag vocabularies.

In multilingual environments this may include:

• Translating tag values into multiple languages
• Aligning vocabulary names with terminology used in different markets
• Ensuring storefront filters and course descriptions reflect region-specific naming conventions

Tags therefore function not only as technical metadata but also as organizational language and product taxonomy.

How Tags Power Platform Features

Tags are referenced by many different features across the platform. Rather than operating as isolated metadata fields, they act as shared classification criteria used throughout the system.

This allows the platform to coordinate behavior across multiple areas simultaneously.

Because tags connect these different features, they become the foundation for personalization, automation, and audience targeting across the platform.

Special Tag Vocabularies

Most vocabularies can be freely designed and adapted to the organization’s needs. However, some tag vocabularies have specific functional relationships with certain platform features.

These should generally be used for their intended purpose.

Category

The Category vocabulary is often used to organize training content.

It may appear in:

• Course settings
• Activity settings
• User profiles
• User creation forms

Categories help structure training catalogs and storefront browsing experiences. The Category vocabulary cannot be deactivated, as it is required for several core platform features and forms part of the system’s minimum taxonomy.

Countries

The Countries vocabulary is primarily used to categorize content by geographic relevance.

It can be applied to courses and activities to indicate where training content may be applicable. This is particularly useful when training materials vary by regulatory region or market.

Job Function

The Job Function vocabulary plays an important role within the platform. In addition to audience targeting, it is integrated into course authoring features where learning pages can be recommended to specific job roles.

Because of this built-in functionality, administrators are generally advised not to repurpose this vocabulary for unrelated classifications.

Title

The Title vocabulary is typically used as a profile attribute and may appear in:

• User profiles
• User creation forms
• Storefront signup forms

This allows organizations to capture professional titles or role designations during registration.

Importance

The Importance vocabulary is typically applied to courses and activities to indicate the relative priority of training.

Examples may include:

• Mandatory
• Recommended
• Optional

This helps learners understand the significance of different training offerings within a program.

Tags And Learning Personalization

Tags also play an important role during content creation and course design. When courses are tagged with specific audience attributes, the platform can automatically connect related learning assets or recommendations.

For example:

• Learning pages may be recommended to users with a specific job function
• Content may adapt to a learner’s profile attributes
• Training materials can automatically align with the audience defined in course settings

This allows training designers to build courses that respond to different roles, responsibilities, or expertise levels.

Designing A Sustainable Tagging Strategy

Because tags influence so many features, organizations benefit from defining a clear tagging strategy early in the platform lifecycle. Tags should reflect stable organizational concepts rather than temporary classifications.

Because vocabularies may be referenced by storefront targeting, automation rules, or course configurations, administrators should avoid deleting or restructuring tags that are already in active use. If a classification structure is no longer needed, it is often better to deactivate the vocabulary rather than remove it entirely. This preserves historical references while preventing further use.

Examples of strong vocabulary foundations include:

• Job roles
• Product families
• Business units
• Certification levels
• Market segments

💡 Overly granular or temporary tags can quickly create complexity if they become referenced by automation rules or storefront configurations. A well-designed taxonomy allows the platform to scale while remaining manageable.

How To Design Your First Tagging Strategy

Designing a tagging structure is one of the most important early decisions when configuring the platform. Because tags influence storefront targeting, automation rules, training assignments, and personalization, a well-designed taxonomy will significantly improve how effectively the platform can scale.

Rather than creating tags reactively as new needs arise, it is recommended to define a clear tagging strategy before implementing automation rules or complex storefront targeting.

The following approach can help administrators design a sustainable structure.

Step 1 — Identify Your Core Audience Segments

Start by identifying the primary characteristics that determine who should receive which training.

These often include:

• Job roles
• Departments or business units
• Partner types
• Customer segments
• Product responsibilities

These characteristics usually become the primary vocabularies in the tagging structure. For example:

These tags are commonly used to drive automation rules and training assignments.

Step 2 — Define Content Classification

Next, identify how training content should be organized in the catalog. This classification helps learners navigate the training environment and helps administrators structure storefront filters and learning catalogs.

Common examples include:

• Product families
• Training categories
• Certification tracks
• Skill levels
• Industry segments

For example:

These tags are commonly applied to courses and activities.

Step 3 — Identify Attributes Used For Automation

Many platform features rely on tags to determine when training should be assigned automatically. Before implementing automation rules, administrators should identify which attributes will trigger training delivery.

Examples include:

• New employee onboarding
• Role-based training requirements
• Product certification programs
• Partner onboarding

For example:

• A new user tagged with Sales may automatically receive a Sales Onboarding Learning Path
• A partner tagged with Gold Partner may receive access to advanced certification courses

Designing these attributes in advance helps avoid restructuring tags later when automation rules become more complex.

Step 4 — Align Tags With Organizational Terminology

Tags should use terminology that is already familiar within the organization. This improves clarity for administrators and ensures that tagging remains intuitive when used across storefront filtering, automation rules, and reporting.

For example:

If the organization refers to field technicians as Service Engineers, the tag vocabulary should reflect that terminology rather than introducing a new internal label. Consistency between the platform taxonomy and organizational language helps improve adoption and reduce confusion.

Step 5 — Plan For Global And Multilingual Use

Organizations operating in multiple regions should consider how tags will appear across different markets and languages. Product names, job titles, and training categories may vary across regions.

For example:

• A product marketed as Product Alpha in one region may be branded differently elsewhere
• A role such as Customer Success Manager may be known as Account Manager in another market

When designing vocabularies, administrators should consider whether to:

• Maintain a global standardized taxonomy
• Introduce regional tag variations
• Use a hybrid approach combining global and regional classifications

Planning for this early can prevent the need for large-scale taxonomy changes later.

Step 6 — Keep The Initial Structure Simple

It is common for organizations to create too many vocabularies early in implementation. A good starting point typically includes:

• Job Function
• Department or Audience Segment
• Product Line
• Training Category

Additional vocabularies can always be introduced later when needed. Starting with a smaller number of well-designed vocabularies helps keep the taxonomy manageable while the platform evolves.

Best Practice Recommendations

In short, we recommend following these guidelines as general best practice. They apply broadly and can be used as a reference when designing or maintaining your tagging strategy.

Common Tag Taxonomy Designs

Because tags power so many features across the platform, organizations benefit from designing a tagging structure that reflects how their training programs are delivered and how their audiences are segmented. The exact structure will vary depending on the platform’s purpose, but most deployments follow recognizable patterns.

The examples below illustrate common approaches used in different learning environments.

Corporate Learning Environment

In internal corporate learning environments, tags are often aligned with the organization’s structure and employee roles. Typical vocabularies may include:

In this type of setup, tags commonly power:

• Onboarding automation for new employees
• Mandatory compliance training assignments
• Learning path targeting based on role or department
• Regional training content distribution

Partner Academy

Partner training platforms often use tags to reflect partner hierarchy, product expertise, and certification requirements. Typical vocabularies may include:

Tags may influence:

• Storefront access to partner-only training
• Eligibility for certification programs
• Partner incentive campaigns
• Discount campaigns for training access

Customer Education Platforms

Customer training platforms typically structure tags around product usage and customer segments. Typical vocabularies may include:

This approach allows organizations to:

• Present product training relevant to each customer
• Personalize storefront catalogs
• Target product updates and announcements
• Assign onboarding programs based on product adoption

Product And Certification Academies

Platforms focused on certification programs often structure taxonomy around training progression and specialization. Typical vocabularies may include:

Tags help automate:

• Certification program enrollment
• Learning path progression
• Storefront catalog filtering
• Course recommendations based on skill level

Choosing The Right Structure

While these examples illustrate common patterns, every organization’s taxonomy should reflect its actual operational structure and audience segmentation. When designing a tagging strategy, administrators should ask:

• How are our training audiences segmented?
• What characteristics determine which training someone should receive?
• Which attributes will be used in automation rules or storefront targeting?
• Which classifications will remain stable over time?

Tags work best when they represent long-term structural attributes rather than temporary campaign labels. Designing this taxonomy thoughtfully ensures that the platform can scale efficiently as new content, audiences, and automation rules are introduced.