---
title: "Best Company Headquarters Location API 2026 | Openbenchmarks"
description: "Best company headquarters location API: nine providers compared on 275 human-reviewed companies for HQ city and country accuracy, coverage and pricing."
url: https://openbenchmarks.com/company-enrichment/best-company-headquarters-location-api
---

[](https://openbenchmarks.com/) 

[Read the benchmark methodology →](https://openbenchmarks.com/company-enrichment#methodology) 

[benchmarks](https://openbenchmarks.com/) / [company enrichment](https://openbenchmarks.com/company-enrichment) / headquarters location 

 company enrichment · HQ data

# Best company headquarters location API 2026

Nine APIs—People Data Labs, Apollo, Parallel, Predict Leads, Explorium, CompanyEnrich, ZoomInfo, Exa, and Seltz—receive the same company domain and enrich it by API calls from their official docs.

**Parallel** has the highest measured HQ-location correct-field yield: **90.9%**, with 250/275 eligible company headquarters correct.

Their primary headquarters city and country were normalized and judged against human-reviewed Ground Truth. The table separates correct yield, coverage, and accuracy when returned.

eligible HQs

275 

providers

11 

field

1 

\[01\] measured HQ results

## Headquarters correctness, completeness, and writeback risk.

Correct-field yield is the primary ranking because it penalizes both missing and incorrect HQ locations. Coverage measures whether a provider returned a location; accuracy when returned measures how often a populated location was correct.

benchmarks/firmographic/by-attribute/hq-location live 

__Company enrichment providers ranked by correct headquarters locations__
| Provider | Correct-field yield | Field coverage | Accuracy when returned |
| --- | --- | --- | --- |
| [Parallel](https://parallel.ai "Open Parallel in a new tab") | **90.9%** 250/275 correct | 99.3% 273/275 returned | 91.6% |
| [People Data Labs](https://www.peopledatalabs.com "Open People Data Labs in a new tab") | **90.2%** 248/275 correct | 97.8% 269/275 returned | 92.2% |
| [Apollo](https://www.apollo.io "Open Apollo in a new tab") | **87.3%** 240/275 correct | 96.0% 264/275 returned | 90.9% |
| [Exa](https://exa.ai "Open Exa in a new tab") | **82.9%** 228/275 correct | 99.3% 273/275 returned | 83.5% |
| [Explorium](https://www.explorium.ai "Open Explorium in a new tab") | **73.5%** 202/275 correct | 96.0% 264/275 returned | 76.5% |
| [ZoomInfo](https://gtm.ai "Open ZoomInfo in a new tab") | **73.1%** 201/275 correct | 90.9% 250/275 returned | 80.4% |
| [PredictLeads](https://predictleads.com "Open PredictLeads in a new tab") | **68.4%** 188/275 correct | 95.3% 262/275 returned | 71.8% |
| [Nimble](https://www.nimbleway.com "Open Nimble in a new tab") | **68.0%** 187/275 correct | 81.5% 224/275 returned | 83.5% |
| [CompanyEnrich](https://companyenrich.com "Open CompanyEnrich in a new tab") | **57.8%** 159/275 correct | 98.5% 271/275 returned | 58.7% |
| [Nimble](https://www.nimbleway.com "Open Nimble in a new tab") | **52.0%** 143/275 correct | 68.7% 189/275 returned | 75.7% |
| [Seltz](https://seltz.ai "Open Seltz in a new tab") | **35.6%** 98/275 correct | 37.1% 102/275 returned | 96.1% |

\[02\] all field results

## Compare HQ performance across every scored field.

This is the main benchmark's per-field table for HQ location, industry, employee band, founded year, and LinkedIn URL. Each value is correct-field yield against the eligible reviewed references for that attribute. Read the [main benchmark methodology](https://openbenchmarks.com/company-enrichment#methodology) for the frozen cohort and public evidence.

benchmarks/firmographic/by-attribute all fields 

__Correct values per attribute, as a share of the companies carrying a verified reference for that attribute__
| Provider | Official docs | HQ location | Industry | Employee band | Founded year | LinkedIn URL |
| --- | --- | --- | --- | --- | --- | --- |
| [ Apollo ](https://www.apollo.io) | [Apollo official docs ↗ ](https://docs.apollo.io/reference/organization-search) | 87.3% 240/275 | 95.4% 269/282 | 78.2% 219/280 | 91.8% 191/208 | 90.8% 256/282 |
| [ CompanyEnrich ](https://companyenrich.com) | [CompanyEnrich official docs ↗ ](https://docs.companyenrich.com/reference/get%5Fcompanies-enrich) | 57.8% 159/275 | 75.9% 214/282 | 54.6% 153/280 | 90.0% 189/210 | **91.8%** 259/282 |
| [ Exa ](https://exa.ai) | [Exa official docs ↗ ](https://docs.exa.ai/reference/search) | 82.9% 228/275 | **96.1%** 271/282 | 33.2% 93/280 | **97.6%** 203/208 | 5.3% 15/282 |
| [ Explorium ](https://www.explorium.ai) | [Explorium official docs ↗ ](https://explorium-api.readme.io/reference/match%5Fbusinesses) | 73.5% 202/275 | 84.8% 239/282 | **88.9%** 249/280 | 0.0% 0/208 | 86.5% 244/282 |
| [ Nimble lite ](https://www.nimbleway.com) | [Nimble lite official docs ↗ ](https://docs.nimbleway.com/api-reference/search/search) | 52.0% 143/275 | 70.9% 200/282 | 44.3% 124/280 | 36.7% 77/210 | 63.1% 178/282 |
| [ Nimble standard ](https://www.nimbleway.com) | [Nimble standard official docs ↗ ](https://docs.nimbleway.com/api-reference/search/search) | 68.0% 187/275 | 85.8% 242/282 | 47.1% 132/280 | 63.3% 133/210 | 82.3% 232/282 |
| [ Parallel ](https://parallel.ai) | [Parallel official docs ↗ ](https://docs.parallel.ai/api-reference/responses-api/create-response) | **90.9%** 250/275 | 92.9% 262/282 | 80.7% 226/280 | 76.4% 159/208 | 86.2% 243/282 |
| [ People Data Labs ](https://www.peopledatalabs.com) | [People Data Labs official docs ↗ ](https://docs.peopledatalabs.com/docs/reference-company-enrichment-api) | 90.2% 248/275 | 94.0% 265/282 | 86.4% 242/280 | 93.8% 195/208 | 84.0% 237/282 |
| [ Predict Leads ](https://predictleads.com) | [Predict Leads official docs ↗ ](https://docs.predictleads.com/guide/extended%5Fcompanies%5Fdataset) | 68.4% 188/275 | 88.3% 249/282 | 78.2% 219/280 | 89.9% 187/208 | 84.8% 239/282 |
| [ Seltz ](https://seltz.ai) | [Seltz official docs ↗ ](https://docs.seltz.ai/api-reference/answer) | 35.6% 98/275 | 37.6% 106/282 | 7.9% 22/280 | 34.8% 73/210 | 35.5% 100/282 |
| [ ZoomInfo ](https://gtm.ai) | [ZoomInfo official docs ↗ ](https://gtm.ai/docs/mcp/tools/enrich-companies) | 73.1% 201/275 | 74.5% 210/282 | 47.9% 134/280 | 61.4% 129/210 | 62.4% 176/282 |

\[03\] questions

### How much does company headquarters location data cost per record, and which API is cheapest?

At each provider's public entry self-serve rate, Nimble lite was the cheapest for the full 282-company run at $0.31, about $0.00 per company record. Pricing is for the whole enrichment call, not this field alone; no provider prices company headquarters location data separately. Cheapest is not best: read cost beside this page's accuracy table.

### Which API has the most accurate company headquarters data?

Parallel has the highest measured end-to-end HQ-location yield at 90.9% (250/275 eligible headquarters correct). Compare coverage and accuracy when returned separately if missing values and incorrect CRM writebacks have different costs.

### What location does this benchmark measure?

It measures the company's primary headquarters city and country. It does not score street address, postal code, legal domicile, incorporation jurisdiction, branch offices, service areas, or every operating location.

### How do I enrich a list of company domains with headquarters locations?

Send the same normalized primary domain to each candidate API, map the result into separate city and country fields, and measure missing and incorrect values separately. Keep HQ enrichment distinct from address verification or office-location discovery, which require different Ground Truth.

open/benchmarks [company enrichment](https://openbenchmarks.com/company-enrichment) [methodology](https://openbenchmarks.com/company-enrichment#methodology) © 2026 Openbenchmarks