How to build a tagging taxonomy in your research repository that scales across teams without becoming unwieldy

A research repository is only as useful as your ability to find things in it. When a single researcher is the only person adding and retrieving insights, informal organization can work well enough. But the moment a second team starts contributing—or a product manager tries to search for everything the organization has learned about onboarding—cracks appear fast.

Tags are the primary mechanism most teams use to make research findings discoverable. A well-designed tagging taxonomy turns a growing collection of notes, transcripts, and highlights into a searchable knowledge base. A poorly designed one creates the illusion of organization while quietly making the repository harder to use with every new study.

This article covers how to design a tagging taxonomy that works for multiple teams, how to govern it without creating bureaucratic overhead, and how to recognize when your taxonomy needs maintenance.

Why tagging taxonomies break down

Before getting into how to build a taxonomy well, it helps to understand the common failure modes.

Tag proliferation

Without clear guidelines, every contributor creates tags that make sense to them in the moment. One researcher tags a finding "onboarding." Another tags a similar finding "first-time experience." A third uses "FTUE." Within a few months the repository has dozens of tags that overlap, and no one can confidently retrieve all findings on a given topic.

Inconsistent granularity

Some tags are broad ("usability"), while others are hyper-specific ("dropdown-menu-mobile-iOS"). When tags operate at wildly different levels of abstraction, search results become unpredictable. A search for broad tags returns too much noise; a search for narrow tags misses relevant findings tagged differently.

Abandoned tags

Tags created for a single project or initiative linger in the system long after they stop being relevant. Over time, the tag list fills with options nobody uses, making it harder for new contributors to find the right tag and increasing the likelihood they will create yet another new one.

No ownership

When nobody is responsible for the taxonomy, nobody maintains it. Duplicate tags accumulate, naming conventions drift, and the taxonomy gradually stops reflecting the actual research themes the organization cares about.

Principles for a scalable taxonomy

A taxonomy that works across teams follows a few core principles. These are not rules to enforce rigidly—they are design values to guide decisions when trade-offs arise.

Organize around user problems, not team structure

It is tempting to create top-level tags based on which team conducted the research—"Growth team," "Platform team," "Enterprise team." This feels tidy at first, but it undermines the cross-team discoverability that makes a shared repository valuable in the first place.

Instead, organize tags around the topics, themes, and user problems the research addresses. Tags like "onboarding," "navigation," "pricing comprehension," and "trust and security" are meaningful regardless of which team produced the finding. A product manager searching for insights about onboarding should find results from every team that has studied it.

Use hierarchy deliberately

A flat list of tags works for small repositories but becomes unmanageable beyond a few dozen items. A simple hierarchy—parent tags with child tags underneath—adds structure without excessive complexity.

For example:

• Onboarding (parent)

  • First-run experience
  • Account setup
  • Team invitations

• Navigation (parent)

  • Information architecture
  • Search behavior
  • Menu structure

Limit hierarchy to two or three levels. Deeper nesting creates confusion about which level to tag at and makes browsing harder.

Prefer plain language

Tags should be immediately understandable to someone who did not create them. Avoid acronyms, internal project code names, and jargon. "Pricing page comprehension" is better than "PP-comp." "Mobile checkout" is better than "mCO."

If a tag requires explanation, it will be misused or ignored. Plain language also makes the taxonomy more welcoming to cross-functional collaborators—product managers, designers, and customer success leads—who may not share researchers' specialized vocabulary.

Make tags mutually exclusive where possible

When two tags overlap significantly, contributors have to guess which one to use, and searchers have to check both. Aim for tags that are clearly distinct from one another. When overlap is unavoidable, document the intended scope of each tag so contributors can make consistent choices.

How to build the taxonomy from scratch

If you are starting a new research repository or overhauling an existing one, the following process provides a practical starting point.

Step 1: Audit existing research

Before creating any tags, look at the research your organization has already produced. Gather the last 6–12 months of study reports, interview notes, usability test findings, and survey results. Read through them and note the recurring themes, topics, and questions.

This bottom-up approach ensures your taxonomy reflects actual research activity rather than hypothetical categories someone invented in a planning meeting. You will likely find 10–20 natural clusters of topics. These become your candidate parent tags.

Step 2: Draft a starter taxonomy

Organize the clusters into a simple hierarchy. For each parent tag, identify two to five child tags that represent meaningful subtopics. Do not try to be exhaustive—the goal is to capture the themes that come up repeatedly, not every conceivable topic.

Write a one-sentence description for each tag explaining what it covers and, where helpful, what it does not cover. These descriptions serve as lightweight documentation that helps contributors tag consistently.

Step 3: Test with real data

Take a sample of 20–30 recent findings and try to tag them using your draft taxonomy. Pay attention to friction points:

• Are there findings that do not fit any tag? You may need to add a category.
• Are there findings that could fit multiple tags? The boundaries between tags may need clarification.
• Are there tags that no findings map to? You may be anticipating a category that does not yet exist in your research.

Revise the taxonomy based on what you learn. Then ask two or three colleagues—ideally from different teams—to tag the same sample independently. Compare their results. Where they diverge, the taxonomy needs clearer definitions or restructuring.

Step 4: Launch with guidance, not just a tag list

When you roll out the taxonomy, do not simply share a list of tags. Provide brief documentation that includes:

• The purpose of the taxonomy and why consistency matters
• The full tag hierarchy with descriptions
• Guidelines for when to request a new tag versus using an existing one
• The name of the person or group responsible for taxonomy decisions

A short onboarding session—even 15 minutes—significantly improves initial adoption. Walk through a few tagging examples so contributors develop a shared mental model.

Governing the taxonomy over time

A taxonomy is not a one-time project. It requires ongoing maintenance to stay useful as research priorities shift and new teams join the repository.

Assign taxonomy stewards

Designate one to three people as taxonomy stewards. Their responsibilities include:

• Reviewing and approving new tag requests
• Merging duplicate or overlapping tags
• Retiring tags that are no longer relevant
• Updating tag descriptions as scope evolves

Stewardship does not need to be a large time commitment. A 30-minute monthly review is often sufficient. What matters is that someone is clearly accountable.

Establish a lightweight request process

Contributors should have a simple way to propose new tags—a shared channel, a form, or a dedicated thread. The process should be low-friction enough that people actually use it rather than creating tags unilaterally, but structured enough that stewards can evaluate requests against the existing taxonomy before approving them.

When evaluating a new tag request, stewards should ask:

• Does this topic already fall under an existing tag?
• Is this a theme that will recur across multiple studies, or is it specific to a single project?
• Does the proposed tag name follow existing naming conventions?

Schedule periodic taxonomy reviews

Every quarter, review the full taxonomy against actual usage. Most research repository tools—including Dovetail—let you see which tags are being used frequently and which are rarely applied. This data informs practical maintenance decisions:

• Merge tags that contributors use interchangeably
• Rename tags that cause confusion
• Archive tags with zero or very few uses in the past quarter
• Split tags that have grown too broad, as indicated by an unusually high volume of tagged items covering diverse subtopics

Document decisions

Keep a simple changelog that records what was added, merged, renamed, or retired, and why. This log prevents repeated debates about the same questions and helps new team members understand the rationale behind the current structure.

Common mistakes to avoid

Creating tags for internal projects or initiatives

Tags like "Q3 discovery sprint" or "Project Phoenix" make sense to the people involved but are meaningless to everyone else six months later. Tag findings by topic, not by the project that produced them. If you need to associate findings with a specific initiative, use a separate metadata field rather than a tag.

Over-engineering before you have data

Resist the urge to design an elaborate taxonomy before your repository has meaningful content. A taxonomy built on assumptions will almost certainly need a major overhaul once real research starts flowing in. Start simple, observe how people use it, and iterate.

Treating tags as the only organizational mechanism

Tags work well for thematic categorization, but they are not the only way to organize a repository. Properties like research method, participant segment, product area, and date provide additional dimensions for filtering and search. Use tags for what they do best—capturing themes and topics—and lean on other metadata for structural attributes.

Scaling across teams

When multiple teams share a repository, the taxonomy needs to accommodate different research contexts without fragmenting into team-specific silos.

Shared core, flexible edges

Maintain a core set of tags that apply organization-wide—topics like "onboarding," "accessibility," "performance," and "trust." These are the tags that enable cross-team discovery. Allow teams to propose specialized child tags under these parents when their research consistently surfaces subtopics that the core taxonomy does not cover.

This approach balances consistency with flexibility. The shared core keeps the repository coherent; the specialized edges let teams capture nuance without polluting the global tag list.

Cross-functional input

Invite product managers, designers, and other research consumers to participate in taxonomy reviews. They often search the repository differently than researchers do, and their perspective highlights gaps in the taxonomy that researchers might not notice. A tag structure that works for the people creating findings but not for the people consuming them defeats the purpose.

Use your tooling

Modern research repositories like Dovetail support structured tagging with features like tag hierarchies, descriptions, and usage analytics. These capabilities make it significantly easier to maintain a clean taxonomy at scale compared to managing tags in spreadsheets or documents. If your repository tool supports controlled vocabularies—where only approved tags can be applied—enable that feature. It is the single most effective way to prevent tag sprawl.

When to revisit the whole taxonomy

Sometimes incremental maintenance is not enough. Signs that a more fundamental restructuring is needed include:

• Contributors routinely ignore the taxonomy and create ad hoc tags
• Searchers consistently cannot find findings they know exist
• The tag list has grown beyond 200 items with no clear hierarchy
• Multiple teams have developed parallel, incompatible tagging conventions

In these situations, treat the restructuring as a fresh build: audit existing content, draft a new hierarchy, test it against real data, and roll it out with clear communication. Migrate existing tags to the new structure in batches, retiring the old taxonomy as migration completes.

The bottom line

A tagging taxonomy is infrastructure. Like any infrastructure, it requires intentional design, clear ownership, and regular maintenance. The organizations that get the most value from their research repositories are not necessarily the ones with the most sophisticated taxonomies—they are the ones that treat taxonomy as an ongoing practice rather than a one-time setup task.

Start with a small, well-defined set of tags grounded in actual research themes. Assign stewards. Review usage quarterly. Merge and retire tags aggressively. Keep the barrier to contribution low and the barrier to creating new tags just high enough to prevent chaos.

The result is a repository where any team member—researcher, product manager, designer, or executive—can find relevant insights quickly, regardless of who conducted the original research or when it was done.