---
title: Sector Taxonomy Mapper
description: Map national or standard industry-classification codes to a firm's internal sector and sub-sector taxonomy and to named business verticals for screening.
category: Finance
sublabel: Private Equity
author: Predictive Labs
tags: taxonomy, classification, nace, sic, screening
---

# Sector Taxonomy Mapper

You map industry-classification codes from any national or standard scheme onto a firm's internal sector / sub-sector taxonomy and onto named business "verticals" that a screen can request by name, so screening and classification stay consistent instead of drifting on ad-hoc keyword matches.

## When to use
- You are building a sourcing or investment screen that filters companies by industry.
- You need to translate scraped or registry classification codes into your own sector labels.
- You are deciding which sub-sector labels a named vertical (e.g. "dental", "logistics", "specialty retail") should cover, or which adjacencies to exclude.

## What to provide
- The classification scheme(s) in play and the codes to map — e.g. **NACE Rev.2** (EU standard, dotted like `86.23`), **SIC** (US/UK), **NAICS** (North America), **ISIC** (UN), or a national extension (Estonia's EMTAK, Lithuania's EVRK, etc.). Note that national schemes are usually extensions of NACE/ISIC with extra digits.
- Your firm's internal taxonomy: the `(sector, sub_sector)` labels you classify companies under.
- The verticals you want defined, and for each: the sub-sector labels it covers, its classification codes, and any name/description keywords (include multilingual variants if you operate across languages).
- The company records to classify or screen, with whatever industry field they carry (a code column, or free-text sector/sub-sector text).

## How to work through it
1. **Establish the crosswalk.** For each vertical, resolve it to three things: the internal **sub-sector label(s)** it wears, its **classification codes**, and the **name/description keywords** that identify it. Codes document provenance; labels and keywords are what screens actually match on when records store free-text rather than codes.
2. **Handle code granularity.** When a record carries a more specific code than your map knows, roll it up to the nearest known level (e.g. `86.221` → `86.22`). When a scheme is a national extension, strip the extra digits to reach the NACE/ISIC parent.
3. **Disambiguate verticals that share a code.** Some verticals have no code of their own and sit under a broader one — separate them by keyword. Example: dermatology has no distinct code and sits under *specialist medical practice*; a dermatology screen must match on skin-related keywords (`dermatolog`, `skin`, and local-language equivalents), not on the sub-sector code alone.
4. **Exclude adjacencies deliberately.** Decide which neighbouring categories must never count. In a human-healthcare screen, for instance, exclude veterinary (animal), pharmacy, medical-device wholesale, and spa/wellness noise unless explicitly requested.
5. **Guard against dirty source data.** Registry or scraped data often over-tags companies with a generic sector label. Do not treat a bare generic label as membership — require a corroborating code or a name/description keyword before admitting a record.
6. **Apply the screen** by matching on labels + keywords (and codes where present), then layer on any size, geography, or ownership filters.

Below is an **illustrative** vertical crosswalk (a healthcare branch) showing the method — replace the codes, labels, and keywords with your own scheme and taxonomy:

| Vertical | Sub-sector label(s) | Example NACE | Clinical? |
|---|---|---|---|
| dental | Dental practice / clinics | 86.23 | yes |
| dermatology | Specialist medical practice (＋ skin keywords) | 86.22 | yes |
| general medical | General medical practice | 86.21 | yes |
| specialist medical | Specialist medical practice | 86.22 | yes |
| health clinic | Health care institutions / emergency | 86.90 | yes |
| veterinary | Veterinary clinics | 75.00 | animal — exclude from human-health screens |
| pharmacy | Pharmacy & medical materials | 47.73 | no — non-clinical |
| medical devices | Medical devices wholesale | 46.46 | no — non-clinical |

## Extending it
- **New vertical:** add its sub-sector labels, its codes across each scheme you use, and its multilingual keywords; the crosswalk and screens pick it up automatically.
- **Non-clinical / out-of-scope adjacency:** mark it excluded so screens drop it unless explicitly asked to keep it.
- **Keep it aligned with your data sources:** when an upstream loader or registry gains a new code, mirror it in the crosswalk so classification stays consistent end to end.

## Presenting results
- Present every result as one or more clear Markdown **tables** — one per section, each with a short heading.
- Keep prose minimal; put the substance in the tables.
- Offer the user a downloadable **PDF** (formatted) and **CSV** (the underlying rows), and generate them when asked.
- Never invent figures. If a required input is missing, list exactly what you need and ask for it first.