What a taxonomy is and how to build it
Most recruitment databases look full but act empty. Thousands of profiles, yet you still end up on LinkedIn. The reason is simple. The data inside the Applicant Tracking System (ATS) is not structured. Skills are inconsistent. Job titles vary. Industries are vague. Without a clear taxonomy, the system cannot recognise who is who. It cannot group similar candidates. It cannot support fast sourcing or clear reporting. A strong taxonomy gives your ATS a common language. It turns scattered fields into a structured card index where every profile has a clear place.
Below is the playbook for building that structure.
Step 1. Define your categories
Categories are the broad domains you recruit for. They help you segment your market and keep the ATS organised at the highest level.
Examples:
IT
Engineering
Finance
Life Sciences
Construction
If your agency operates in one niche, you can skip this step. Categories only add value if they help you filter or navigate your data. The rule is simple. If no recruiter ever filters by it, it should not be a category.
Clean categories matter because they anchor every specialty and skill. They stop candidates from being mixed across unrelated domains.
Step 2. List the specialties within each category
Specialties represent real roles or job families. They should match the language your clients use, not internal jargon.
Examples in IT:
Software developer
DevOps engineer
Data scientist
Network engineer
Each specialty should describe a type of work you place regularly. Avoid long lists. Keep them tight. A specialty loses meaning if you create ten variations for the same job.
Clear specialties matter because they drive search precision. When every profile is linked to the right specialty, you can shortlist in minutes rather than rebuild the same Boolean query every time.
Step 3. Map the core skills for each specialty
Skills are where most ATS data breaks. Synonyms, abbreviations, and inconsistent naming make it impossible to match profiles accurately.
Create one standard version per skill, for example:
React
JavaScript
AWS
SolidWorks
Not:
React.js
Javascript
Amazon Web Services
Solid Works
Keep skills clean, consistent, and specific. Remove duplicates. Decide on one naming style and apply it everywhere.
Clean skills matter because they turn keyword search into structured search. Once the ATS holds proper skill data, your matching improves and your shortlist time drops.
Step 4. Add industries, sectors, or company types
Most agencies stop at roles and skills. The best ones also classify where candidates have worked. This context changes how relevant someone is for a client.
Examples:
Accounting firm
In-house finance
SaaS
Manufacturing
Consultancy
Industry context matters because it helps you match experience to the right environment. A project manager from a consultancy behaves differently from a project manager inside a product company. Your taxonomy should reflect that.
Step 5. Validate the structure with your recruiters
Bring three to five senior recruiters into the review. They know how the market speaks and where the edge cases sit. Ask them to check:
Does each specialty match what clients request?
Would you filter on this category or is it noise?
Are any skills unclear or duplicated?
Would you use these options during a shortlist?
A taxonomy that looks good on paper but does not fit real workflows will not be used. Validation ensures adoption.
Step 6. Keep it lean and current
A taxonomy is never finished. New tools appear. Roles evolve. Markets shift. Review it every few months. Add new skills sparingly. Remove outdated ones. Combine specialties if recruiters treat them as the same.
Lean structures matter because bloat slows down the team. Your goal is clarity, not volume.
QA: Common mistakes and how to avoid them
Too many specialties
Split roles only if recruiters treat them as different. Otherwise merge them.
Skills that are actually job titles
For example "project management" appears as both a skill and a specialty. Choose one place and stick to it.
Mixing industries with skills
For example "finance" appears as both. Keep industry context separate from skill data.
Not cleaning duplicates
A taxonomy only works if fields are consistent. Duplicates erode search accuracy.
Letting personal preferences creep in
A taxonomy is a shared system. It is not an individual cheat sheet.
Conclusion
A clear taxonomy is the base layer that makes your ATS usable again. It aligns skills, specialties, and industries into one structured system. Recruiters gain speed because they can filter clean data instead of relying on guesswork. Business development becomes easier because candidate and company data follow the same logic. Define your categories. Set your specialties. Standardise your skills. Add industry context. Validate with your team. Keep it lean. Once that structure exists, Daidalo keeps it clean, complete, and current. It applies the correct classifications across your entire database so recruiters stop fixing the data manually and start using it.
