User-Friendly Company Location Data APIs to Consider in 2026
If your product needs to enrich signups with verified company location data, filter sign-in traffic by geography, or audit where ads are running by market, accurate website classification is the backbone that makes it all work. The real challenge isn’t just “finding the city” — it’s reliably mapping a domain to a business, understanding what that business is about, and extracting consistent, structured signals like city, state, and country alongside categories you can trust. That’s exactly where the Klazify API shines: a single request that classifies the website, returns IAB-aligned categories, and provides company information — including location — you can put straight into your pipelines.
Why Klazify is the best fit for company location classification in 2026
Classifying websites to extract reliable company location data is a high-stakes task in ad tech, fraud detection, content filtering, CRM enrichment, and analytics. You need precision, broad coverage, and fresh signals. Klazify was purpose-built for this.
Accurate company and location categorization using AI
Klazify’s models analyze the content of a site, not just metadata. That content-first approach dramatically improves accuracy when mapping a domain to a company profile with fields like city, stateCode, and countryCode, especially for complex sites that host multiple sub-brands or blogs. For example, a domain landing page might highlight marketing content while a careers subpath lists office locations — Klazify’s domain and URL-level analysis helps discern the real company entity and its primary location signals.
Global coverage across languages and markets
If your signup flow welcomes users from São Paulo, Singapore, or Stockholm, you need a classifier that reads the web globally. Klazify analyzes sites in multiple languages, helping you normalize company data and geographies in your CRM, data lake, or analytics workspace with consistent countryCode outputs and contextual categories for each domain.
Real-time classification that keeps up with change
Company pages and location details evolve. Klazify emphasizes up-to-date domain analysis and content categorization so you can trust the location attributes you are enriching in near real time — essential for brand safety decisions, market-by-market ad permissions, and dynamic eligibility rules in your product.
Industry-level categories using IAB taxonomy
Location alone does not tell the full story. Klazify pairs location data with IAB-aligned categories, enabling rules such as “allow B2B SaaS domains registered in the US” or “flag consumer electronics retailers in a restricted region.” You get both context (the nature of the business) and place (where the company is located) in a single response.
Simple API integration for modern pipelines
With one REST endpoint, you can classify a website, retrieve company details, obtain IAB taxonomy categories, detect social links, and more. This minimizes moving parts in your architecture and lets you standardize enrichment and filtering with a single integration across ingestion services, ETL, or event-driven flows.
Superior compliance filtering and whitelisting
For brand safety, content filtering, or compliance workflows, Klazify’s combination of categories and company location fields helps you target by market, exclude restricted regions, and document decisions for auditors. The result is a cleaner, safer digital footprint — automatically enforced in your stack.
Scenario: Enriching signups with company location and category for routing
Imagine your SaaS platform receives a signup from an email at exampleco.com. Your CRM and in-app experience need the company’s city, stateCode, and countryCode to assign the right sales team, localize messaging, and ensure eligibility with your regional policies. You also want to know if the domain belongs to a consumer electronics business or a finance firm to tailor onboarding content and outreach.
With the Klazify API, your ingestion service can:
- Classify the website content and map it to IAB categories,
- Extract company details like name and location,
- Surface logo_url, social_media, and similar_domains for richer user profiles,
- Cache results per domain and reuse them across systems.
From the first request, your pipeline gains reliable location and category signals you can plug into routing, scoring, personalization, and compliance checks.
How the Klazify API addresses company location classification
Klazify’s main endpoint provides a comprehensive response that goes beyond simple categorization. In a single response payload, you’ll see categories with confidence scores, company fields (including location), domain registration metadata, technology signals, and related domains.
Main endpoint
Endpoint URL: https://www.klazify.com/api/categorize
Purpose: Website classification and content categorization with company location and business details.
Key capabilities that power location-focused workflows
- Website Classification and Content Categorization: Assigns categories grounded in on-page content.
- IAB Taxonomy Mapping: Aligns results to an industry standard you can use for ad tech and brand safety.
- Company Information from URL: Returns fields like city, stateCode, and countryCode along with name and URL.
- Logo URL Extraction and Social Media URL Detection: Adds recognizable assets to your profiles.
- Domain Registration Data: Useful for freshness checks, eligibility rules, and fraud screening.
- Similar Domains Identification: Assists with deduplication, lead expansion, and competitor clustering.
End-to-end path: From domain to location-aware decisions
1) Submit the domain or URL for classification
Your ingestion service posts a request with the domain or a specific URL to the categorize endpoint. Keep the request idempotent if you plan to cache results. For implementation specifics on request format, authentication, and available parameters, rely on the official documentation.
curl -X POST "https://www.klazify.com/api/categorize" --data-binary @request.json
Tip: request.json should include the URL or domain you want to analyze. Keep payloads small for low latency and easier batching in your data pipelines. Check out the full Klazify API documentation for details.
2) Parse the response to extract categories and location
After you receive the JSON, pull category names and confidence, plus company.city, company.stateCode, and company.countryCode. These become primary keys for downstream actions like lead routing, policy enforcement, and campaign segmentation.
3) Cache and reuse across systems
Cache normalized per-domain results and enforce sensible TTLs so you benefit from stable categorization while keeping pace with changes. When a domain reappears in any product surface (signup, pageview, partner import), reuse the cached profile to avoid unnecessary calls.
Example API responses and how to use them
Below is a sample response you can expect to parse. Note how the domain.categories array includes IAB taxonomy mappings and confidence scores, while objects.company returns normalized location data.
{
"domain": {
"categories": [
{
"confidence": 0.92,
"name": "/Computers & Electronics/Consumer Electronics",
"IAB-632-596": "Consumer Electronics/Technology & Computing/Consumer Electronics"
},
{
"confidence": 0.89,
"name": "/Internet & Telecom/Mobile & Wireless/Mobile Phones"
}
],
"social_media": null,
"logo_url": "https://klazify.s3.amazonaws.com/2110787991611585019600ed5fb1d1300.04730104.png"
},
"success": true,
"objects": {
"company": {
"url": "https://www.apple.com/",
"name": "Apple",
"city": "Cupertino",
"stateCode": "CA",
"countryCode": "US",
"employeesRange": "100K+",
"revenue": 274515000000,
"raised": null,
"tags": [
"E-commerce",
"Consumer Electronics",
"Mobile",
"B2C"
],
"tech": [
"omniture_adobe_analytics",
"atlassian_confluence",
"successfactors",
"apache_apex",
"talend",
"oracle_peoplesoft",
"salesforce",
"stripe",
"dell_boomi_atomsphere",
"gigya",
"sage_50cloud",
"quickbooks",
"webmethods",
"apache_tomcat",
"alteryx",
"tibco_rendezvous",
"atlassian_jira",
"..."
]
}
},
"domain_registration_data": {
"domain_age_date": "1987-02-19",
"domain_age_days_ago": "13026",
"domain_expiration_date": "2030-02-20",
"domain_expiration_days_left": "123"
},
"similar_domains": [
"bestbuy.com",
"icloud.com",
"microsoft.com",
"macrumors.com",
"google.com",
"samsung.com",
"twitter.com",
"hp.com",
"bhphotovideo.com",
"dell.com"
]
}
Interpreting key fields
- domain.categories: Use name for your policy filters and map IAB codes to your targeting taxonomy.
- objects.company.city, stateCode, countryCode: Normalize into your CRM or data warehouse for routing and geo segmentation.
- domain.logo_url: Store a stable logo reference for clear UI display in admin tools and sales dashboards.
- domain_registration_data: Helpful for freshness, eligibility, or anti-fraud rules.
- similar_domains: Seed account-based marketing (ABM) lookalikes or deduplicate multiple domains for the same organization.
Using the same response structure in multiple workflows
The same JSON output supports many different tasks. Below are repeated copies of the sample response to illustrate consistent parsing across contexts such as signup enrichment, ad safety checks, and cybersecurity auditing.
Signup enrichment
{
"domain": {
"categories": [
{
"confidence": 0.92,
"name": "/Computers & Electronics/Consumer Electronics",
"IAB-632-596": "Consumer Electronics/Technology & Computing/Consumer Electronics"
},
{
"confidence": 0.89,
"name": "/Internet & Telecom/Mobile & Wireless/Mobile Phones"
}
],
"social_media": null,
"logo_url": "https://klazify.s3.amazonaws.com/2110787991611585019600ed5fb1d1300.04730104.png"
},
"success": true,
"objects": {
"company": {
"url": "https://www.apple.com/",
"name": "Apple",
"city": "Cupertino",
"stateCode": "CA",
"countryCode": "US",
"employeesRange": "100K+",
"revenue": 274515000000,
"raised": null,
"tags": [
"E-commerce",
"Consumer Electronics",
"Mobile",
"B2C"
],
"tech": [
"omniture_adobe_analytics",
"atlassian_confluence",
"successfactors",
"apache_apex",
"talend",
"oracle_peoplesoft",
"salesforce",
"stripe",
"dell_boomi_atomsphere",
"gigya",
"sage_50cloud",
"quickbooks",
"webmethods",
"apache_tomcat",
"alteryx",
"tibco_rendezvous",
"atlassian_jira",
"..."
]
}
},
"domain_registration_data": {
"domain_age_date": "1987-02-19",
"domain_age_days_ago": "13026",
"domain_expiration_date": "2030-02-20",
"domain_expiration_days_left": "123"
},
"similar_domains": [
"bestbuy.com",
"icloud.com",
"microsoft.com",
"macrumors.com",
"google.com",
"samsung.com",
"twitter.com",
"hp.com",
"bhphotovideo.com",
"dell.com"
]
}
Ad placement safety
{
"domain": {
"categories": [
{
"confidence": 0.92,
"name": "/Computers & Electronics/Consumer Electronics",
"IAB-632-596": "Consumer Electronics/Technology & Computing/Consumer Electronics"
},
{
"confidence": 0.89,
"name": "/Internet & Telecom/Mobile & Wireless/Mobile Phones"
}
],
"social_media": null,
"logo_url": "https://klazify.s3.amazonaws.com/2110787991611585019600ed5fb1d1300.04730104.png"
},
"success": true,
"objects": {
"company": {
"url": "https://www.apple.com/",
"name": "Apple",
"city": "Cupertino",
"stateCode": "CA",
"countryCode": "US",
"employeesRange": "100K+",
"revenue": 274515000000,
"raised": null,
"tags": [
"E-commerce",
"Consumer Electronics",
"Mobile",
"B2C"
],
"tech": [
"omniture_adobe_analytics",
"atlassian_confluence",
"successfactors",
"apache_apex",
"talend",
"oracle_peoplesoft",
"salesforce",
"stripe",
"dell_boomi_atomsphere",
"gigya",
"sage_50cloud",
"quickbooks",
"webmethods",
"apache_tomcat",
"alteryx",
"tibco_rendezvous",
"atlassian_jira",
"..."
]
}
},
"domain_registration_data": {
"domain_age_date": "1987-02-19",
"domain_age_days_ago": "13026",
"domain_expiration_date": "2030-02-20",
"domain_expiration_days_left": "123"
},
"similar_domains": [
"bestbuy.com",
"icloud.com",
"microsoft.com",
"macrumors.com",
"google.com",
"samsung.com",
"twitter.com",
"hp.com",
"bhphotovideo.com",
"dell.com"
]
}
Cybersecurity and compliance
{
"domain": {
"categories": [
{
"confidence": 0.92,
"name": "/Computers & Electronics/Consumer Electronics",
"IAB-632-596": "Consumer Electronics/Technology & Computing/Consumer Electronics"
},
{
"confidence": 0.89,
"name": "/Internet & Telecom/Mobile & Wireless/Mobile Phones"
}
],
"social_media": null,
"logo_url": "https://klazify.s3.amazonaws.com/2110787991611585019600ed5fb1d1300.04730104.png"
},
"success": true,
"objects": {
"company": {
"url": "https://www.apple.com/",
"name": "Apple",
"city": "Cupertino",
"stateCode": "CA",
"countryCode": "US",
"employeesRange": "100K+",
"revenue": 274515000000,
"raised": null,
"tags": [
"E-commerce",
"Consumer Electronics",
"Mobile",
"B2C"
],
"tech": [
"omniture_adobe_analytics",
"atlassian_confluence",
"successfactors",
"apache_apex",
"talend",
"oracle_peoplesoft",
"salesforce",
"stripe",
"dell_boomi_atomsphere",
"gigya",
"sage_50cloud",
"quickbooks",
"webmethods",
"apache_tomcat",
"alteryx",
"tibco_rendezvous",
"atlassian_jira",
"..."
]
}
},
"domain_registration_data": {
"domain_age_date": "1987-02-19",
"domain_age_days_ago": "13026",
"domain_expiration_date": "2030-02-20",
"domain_expiration_days_left": "123"
},
"similar_domains": [
"bestbuy.com",
"icloud.com",
"microsoft.com",
"macrumors.com",
"google.com",
"samsung.com",
"twitter.com",
"hp.com",
"bhphotovideo.com",
"dell.com"
]
}
How to plug the response into your pipeline
Transforming and storing the key fields
- Normalize location fields into your master data model: company_city, company_state_code, company_country_code.
- Persist category names and any IAB mapping keys so you can join or filter downstream.
- Store a consistent logo_url for display layers.
- Record domain_age_date and expiration metadata for compliance or fraud scoring.
Batching and concurrency at a high level
- Group domains into micro-batches during ingestion to smooth throughput in your ETL or stream processor.
- Apply backoff and retry patterns for transient network issues.
- Deduplicate incoming domains per time window to avoid redundant calls.
Caching strategy
- Cache by registered domain (and subdomain if you classify at URL-level granularity).
- Set different TTLs for domains known to change frequently vs. static corporate sites.
- Warm the cache for top traffic referrers or frequent partners you encounter often.
Handling unknown or new domains
- If the company object is partial or location fields are missing, queue the domain for recheck while applying a neutral policy in the interim.
- Log low-confidence category results for review; fallback to conservative filters if your workflow demands strict safety.
Mapping categories to your internal taxonomy
Many teams operate with bespoke taxonomies. Use the IAB mapping present in categories to drive an explicit mapping table. Keep a registry that associates each Klazify category name or IAB code with your internal standard, including audit notes for any special cases (e.g., mixed-content publishers or marketplaces).
Code examples to jumpstart integration
Python snippet: Request and parse location + categories
The following code shows how you might call the endpoint, parse the JSON, and extract category and location details for storage. Replace authentication and request payload handling based on your environment and reference documentation for the exact request format.
import json
import requests
ENDPOINT = "https://www.klazify.com/api/categorize"
def classify_domain(request_payload, headers=None):
# request_payload should include the URL or domain you want to analyze
# headers may include your authorization if required by your environment
response = requests.post(ENDPOINT, data=json.dumps(request_payload), headers=headers or {"Content-Type": "application/json"})
response.raise_for_status()
return response.json()
def pick_primary_category(categories):
if not categories:
return None
# Example: choose the highest confidence category
return sorted(categories, key=lambda c: c.get("confidence", 0), reverse=True)[0]
def parse_company_location(data):
company = (data.get("objects") or {}).get("company") or {}
return {
"name": company.get("name"),
"url": company.get("url"),
"city": company.get("city"),
"stateCode": company.get("stateCode"),
"countryCode": company.get("countryCode"),
}
def parse_categories(data):
domain = data.get("domain") or {}
return domain.get("categories") or []
def parse_logo(data):
domain = data.get("domain") or {}
return domain.get("logo_url")
# Example usage (fill 'request_payload' accordingly, per documentation)
# request_payload = {"url": "https://www.apple.com/"} # see docs for exact format
# result = classify_domain(request_payload)
# primary_cat = pick_primary_category(parse_categories(result))
# company_loc = parse_company_location(result)
# logo = parse_logo(result)
Sample JSON you’ll parse
{
"domain": {
"categories": [
{
"confidence": 0.92,
"name": "/Computers & Electronics/Consumer Electronics",
"IAB-632-596": "Consumer Electronics/Technology & Computing/Consumer Electronics"
},
{
"confidence": 0.89,
"name": "/Internet & Telecom/Mobile & Wireless/Mobile Phones"
}
],
"social_media": null,
"logo_url": "https://klazify.s3.amazonaws.com/2110787991611585019600ed5fb1d1300.04730104.png"
},
"success": true,
"objects": {
"company": {
"url": "https://www.apple.com/",
"name": "Apple",
"city": "Cupertino",
"stateCode": "CA",
"countryCode": "US",
"employeesRange": "100K+",
"revenue": 274515000000,
"raised": null,
"tags": [
"E-commerce",
"Consumer Electronics",
"Mobile",
"B2C"
],
"tech": [
"omniture_adobe_analytics",
"atlassian_confluence",
"successfactors",
"apache_apex",
"talend",
"oracle_peoplesoft",
"salesforce",
"stripe",
"dell_boomi_atomsphere",
"gigya",
"sage_50cloud",
"quickbooks",
"webmethods",
"apache_tomcat",
"alteryx",
"tibco_rendezvous",
"atlassian_jira",
"..."
]
}
},
"domain_registration_data": {
"domain_age_date": "1987-02-19",
"domain_age_days_ago": "13026",
"domain_expiration_date": "2030-02-20",
"domain_expiration_days_left": "123"
},
"similar_domains": [
"bestbuy.com",
"icloud.com",
"microsoft.com",
"macrumors.com",
"google.com",
"samsung.com",
"twitter.com",
"hp.com",
"bhphotovideo.com",
"dell.com"
]
}
Technical approach: Company location through content classification
Domain and URL-level analysis
Klazify can classify entire domains and also specific URLs. This is important for multi-tenant sites or content-rich publishers where the homepage may emphasize brand while subpages enumerate offices or regional offers. You can:
- Classify at the domain level for stable identity and location signals.
- Classify at the URL level for nuanced content decisions, then reconcile to the core company profile for location fields.
Semantic understanding and contextual mapping
Accurate location extraction often requires more than a string match of “Headquarters.” Klazify’s content categorization and semantic understanding helps distinguish between global office lists, mailing addresses, and true headquarters signals. By combining categories, tags, and company fields, you achieve higher precision and cleaner records.
IAB taxonomy for policy controls
When your policy engine combines geographic rules with content categories, you can express high-fidelity controls such as “allow consumer electronics retailers in US/CA markets for this campaign” or “enforce additional checks on mobile phone vendors in restricted regions.” IAB mappings in the response let you operationalize these rules with industry-aligned consistency.
Benefits of accurate company location classification
- Lead Routing: Assign signups to the right regional team immediately using company.city, stateCode, and countryCode.
- Brand Safety: Approve or exclude inventory based on both market and content category, reinforced by confidence scores.
- Compliance: Enforce data residency or export controls by geographic eligibility rules tied to domains.
- Fraud Reduction: Correlate domain age and location signals with known patterns to flag suspicious traffic.
- Personalization: Localize content and outreach by region while aligning copy to the domain’s industry category.
Data model: Fields you will use most
| Field | Type | Usage |
|---|---|---|
| domain.categories[].name | String | Primary category path for filtering and targeting. |
| domain.categories[].confidence | Number | Weight category decisions by confidence. |
| objects.company.city | String | City-level routing and personalization. |
| objects.company.stateCode | String | State or region controls and reporting. |
| objects.company.countryCode | String | Country-level eligibility, compliance, analytics. |
| domain.logo_url | String (URL) | UI display for accounts and admin consoles. |
| domain_registration_data | Object | Enrich risk models and lifecycle checks. |
| similar_domains[] | Array | ABM expansion and deduplication. |
Real-world applications specific to company location data
1) Enrich signups and score leads by region
Use company.city, stateCode, and countryCode to auto-assign owners and apply region-specific scoring criteria. For example, weighted MQL thresholds can vary by market maturity or quota model.
2) Gate features by compliance region
Control access to features that are restricted to certain regions. Use countryCode to enforce gating rules at account creation and upgrade flows, paired with IAB categories to handle special industry requirements.
3) Market segmentation for analytics
Bucket traffic and account activity by countryCode for reporting. Layer in categories to analyze product adoption by vertical and market simultaneously.
4) Ad placement audits
Verify that campaigns only appear in approved countries and on inventory with allowed categories. When discrepancies appear, your diagnostics can cite precise categories and location fields from the response.
5) Cybersecurity triage
Combine domain_registration_data, company location, and categories to prioritize investigations. A sudden spike of signups from domains with very recent domain_age_date in sensitive markets might trigger additional verification workflows.
Implementation best practices and integration tips
Architecture patterns
- Event-driven enrichment: Attach a “classify_domain” step to signup and partner-import events. Store normalized outputs.
- ETL enrichment: Nightly jobs classify new or unclassified domains and backfill missing location fields.
- Synchronous checks: For live policy decisions (e.g., ad placement), use cached results for speed, refreshing asynchronously.
Data quality management
- Standardize location fields: Always store countryCode, stateCode, city in a normalized schema using uppercase ISO-like patterns.
- Confidence-aware logic: Set thresholds for auto-allow and auto-review based on category confidence.
- Cross-validation: For critical flows, compare company.countryCode with user IP geolocation or billing country.
Batching and queuing
- Use small batch sizes to balance throughput and latency.
- Queue reclassifications for domains flagged as high-change or after significant website updates.
- Track classification attempts and caching outcomes for observability.
Monitoring and observability
- Log top categories, confidence distributions, and location codes to detect drifts.
- Build dashboards for enrichment freshness, cache hit rate, and classification coverage.
- Set alerts for surges of unknown or null location fields to trigger triage.
From “unknown domain” to actionable profile
When a new, unfamiliar domain hits your system, you want to move quickly from “unknown” to “trusted profile” with as few steps as possible. The Klazify response helps you fast-track that journey:
- Company location fields provide immediate geographic context for routing and gating.
- Categories with confidence suggest the appropriate vertical playbook and messaging.
- Domain age and expiration data add temporal insights for risk models.
- Similar domains inform deduplication checks and multi-domain account mapping.
Concrete example: Auditing where ads run by market
A demand-side platform or in-house ad buyer might maintain a rule: “Run only in North America on consumer tech inventory.” A Klazify-based audit process can sample domains where impressions occurred, classify them, and verify:
- The company’s countryCode is US or CA, and
- Categories include paths like Consumer Electronics or Mobile Phones.
When a mismatch occurs, you can present exact evidence in a report: the category name, confidence, and company.countryCode as returned in the response. This supports rapid troubleshooting and transparent conversations with partners.
Governance: Mapping Klazify categories to your internal taxonomy
Enterprises often maintain a canonical internal taxonomy for verticals, lines of business, and eligibility tags. Using Klazify’s IAB-aligned data:
- Create a mapping table that associates IAB strings and category names with your internal tags.
- Version and track changes to the mapping as your business rules evolve.
- Run a data migration to retroactively align previous classifications when mappings change.
Future trends in location-aware website classification
Deeper page-level intelligence
As businesses expand microsites and localized content, URL-level classification will become more central. You’ll increasingly weigh domain identity against specific page context to make policy decisions that are both safe and flexible.
Converging identity signals
Expect tighter correlation of company profiles with verified social handles, technology stacks, and domain registration cues. This strengthens confidence in location fields and reduces ambiguity in multi-brand ecosystems.
Contextual targeting with stronger guardrails
With privacy-first shifts across the ecosystem, contextual and content-based targeting paired with robust location data will keep gaining importance. Granular category data and reliable company country codes will power performant, compliant campaigns.
Additional full response example for developer testing
Use the following sample response in staging to validate your parsers for categories, IAB mappings, company location, and registration data. It mirrors the structure you’ll see in production:
{
"domain": {
"categories": [
{
"confidence": 0.92,
"name": "/Computers & Electronics/Consumer Electronics",
"IAB-632-596": "Consumer Electronics/Technology & Computing/Consumer Electronics"
},
{
"confidence": 0.89,
"name": "/Internet & Telecom/Mobile & Wireless/Mobile Phones"
}
],
"social_media": null,
"logo_url": "https://klazify.s3.amazonaws.com/2110787991611585019600ed5fb1d1300.04730104.png"
},
"success": true,
"objects": {
"company": {
"url": "https://www.apple.com/",
"name": "Apple",
"city": "Cupertino",
"stateCode": "CA",
"countryCode": "US",
"employeesRange": "100K+",
"revenue": 274515000000,
"raised": null,
"tags": [
"E-commerce",
"Consumer Electronics",
"Mobile",
"B2C"
],
"tech": [
"omniture_adobe_analytics",
"atlassian_confluence",
"successfactors",
"apache_apex",
"talend",
"oracle_peoplesoft",
"salesforce",
"stripe",
"dell_boomi_atomsphere",
"gigya",
"sage_50cloud",
"quickbooks",
"webmethods",
"apache_tomcat",
"alteryx",
"tibco_rendezvous",
"atlassian_jira",
"..."
]
}
},
"domain_registration_data": {
"domain_age_date": "1987-02-19",
"domain_age_days_ago": "13026",
"domain_expiration_date": "2030-02-20",
"domain_expiration_days_left": "123"
},
"similar_domains": [
"bestbuy.com",
"icloud.com",
"microsoft.com",
"macrumors.com",
"google.com",
"samsung.com",
"twitter.com",
"hp.com",
"bhphotovideo.com",
"dell.com"
]
}
Operational checklist for production teams
- Define a cache policy (TTL, refresh triggers, and invalidation events) for domain profiles.
- Establish a confidence threshold for automated actions vs. manual review.
- Set up observability: percent classified, percent with populated location, drift of category distributions.
- Create a taxonomy mapping registry and unit tests for mapping changes.
- Integrate a dead-letter queue for unparseable or transiently failing requests, with periodic reprocessing.
Security and compliance considerations
- Store only the fields you need. If your use case needs location and categories, avoid persisting extraneous data.
- Encrypt data at rest and in transit inside your platform.
- Audit access to enrichment results, especially those used in regulatory controls or user eligibility decisions.
Team workflows that benefit from Klazify-powered location data
- Sales Operations: Auto-ownership and territory assignment upon lead creation.
- Marketing Ops: Dynamic nurture journeys localized by region and personalized by vertical.
- Trust & Safety: Geofenced feature gating and regional compliance enforcement.
- Data Engineering: A single, consistent enrichment API to populate downstream marts and data products.
- Product Management: Feature flags by market and category for controlled rollouts.
Putting it all together: A reference flow
- Inbound domain captured at signup, pageview, or partner data import.
- Send to Klazify categorize endpoint; parse categories, IAB mapping, company location.
- Normalize fields and cache per domain.
- Apply business rules: routing by region, ad safety by category, compliance checks by countryCode.
- Log decisions with category name, confidence, and location fields for auditing.
- Refresh classifications on schedule or upon content change signals.
Common pitfalls and how to avoid them
- Treating location as always HQ: Use company location fields as canonical, but consider cross-validation when a domain clearly represents a different regional brand or franchise.
- Ignoring confidence: Always interpret category confidence; route low-confidence classifications to secondary checks.
- One-size-fits-all TTL: Choose TTLs based on your risk tolerance and the volatility of the sites you classify most.
- Hard-coding mappings: Maintain a managed mapping table for IAB to internal taxonomy; avoid in-code constants that are hard to update.
Governed experimentation: Test and learn with your policies
As you evolve your enrichment strategy, run controlled experiments by market and vertical. Measure lift in lead conversion when routing by company.countryCode, or reduction in support tickets when content is localized by region and category. Because Klazify provides a stable schema, your experiments remain clean and replicable across teams.
Reference: Verify your integration with a final sample response
Use this final copy of the response to finalize your unit tests, ensuring all expected fields are parsed and stored correctly across your services:
{
"domain": {
"categories": [
{
"confidence": 0.92,
"name": "/Computers & Electronics/Consumer Electronics",
"IAB-632-596": "Consumer Electronics/Technology & Computing/Consumer Electronics"
},
{
"confidence": 0.89,
"name": "/Internet & Telecom/Mobile & Wireless/Mobile Phones"
}
],
"social_media": null,
"logo_url": "https://klazify.s3.amazonaws.com/2110787991611585019600ed5fb1d1300.04730104.png"
},
"success": true,
"objects": {
"company": {
"url": "https://www.apple.com/",
"name": "Apple",
"city": "Cupertino",
"stateCode": "CA",
"countryCode": "US",
"employeesRange": "100K+",
"revenue": 274515000000,
"raised": null,
"tags": [
"E-commerce",
"Consumer Electronics",
"Mobile",
"B2C"
],
"tech": [
"omniture_adobe_analytics",
"atlassian_confluence",
"successfactors",
"apache_apex",
"talend",
"oracle_peoplesoft",
"salesforce",
"stripe",
"dell_boomi_atomsphere",
"gigya",
"sage_50cloud",
"quickbooks",
"webmethods",
"apache_tomcat",
"alteryx",
"tibco_rendezvous",
"atlassian_jira",
"..."
]
}
},
"domain_registration_data": {
"domain_age_date": "1987-02-19",
"domain_age_days_ago": "13026",
"domain_expiration_date": "2030-02-20",
"domain_expiration_days_left": "123"
},
"similar_domains": [
"bestbuy.com",
"icloud.com",
"microsoft.com",
"macrumors.com",
"google.com",
"samsung.com",
"twitter.com",
"hp.com",
"bhphotovideo.com",
"dell.com"
]
}
FAQ: Company location data and website classification
How do I get the company’s city, state, and country from a domain?
Call the categorize endpoint and read objects.company.city, objects.company.stateCode, and objects.company.countryCode from the response. Normalize these fields into your data model for easy joins and filters.
Can I use the categories to enforce regional ad safety rules?
Yes. Combine domain.categories (and any IAB mappings present) with company.countryCode to implement policies like “allow only specific categories in certain countries.” Use confidence values to decide when to auto-allow vs. route to review.
What if a domain has multiple brands or regions?
Classify at the domain level for a stable identity, and optionally classify at the URL level for page-specific context. Keep a cache keyed by domain and reconcile page-level nuances to your company profile for location fields.
How should I handle low-confidence classifications?
Set a confidence threshold. Below that threshold, apply conservative policies or queue a recheck. You can also use domain_registration_data and similar_domains to inform any additional verification steps.
What’s the best way to map Klazify categories to our internal taxonomy?
Create a mapping table that associates each category name or IAB mapping with your internal tags. Version-control it and write unit tests so changes don’t break your pipelines.
How often should I refresh classifications?
Adopt a TTL that fits your risk and freshness needs. Refresh more frequently for domains known to change often. Use asynchronous refresh so user-facing experiences remain fast.
Which additional fields are most helpful beyond location?
logo_url for UI clarity, domain_registration_data for risk and lifecycle analysis, and similar_domains for deduplication and ABM expansion are especially valuable alongside categories and location.
Try Klazify API for free and start enriching domains with precise company location data, IAB-aligned categories, and the site intelligence your teams need to build safer, smarter products.
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