How to Find Similar Companies

You need to automatically discover companies similar to a domain your users enter, so you can enrich sign‑ups, build competitor clusters, flag risky partners, or run brand‑safety checks at scale. By the end of this guide, you’ll call a single API to retrieve up to 10 related sites for any domain, parse the response, and plug those results into your pipeline with caching, batching, and fallback strategies.

Why Klazify is the best API for finding similar companies

When you’re clustering competitors, building lookalike segments, or auditing partners, the quality of “similar companies” matters. Klazify specializes in domain intelligence—classifying websites and surfacing related domains you can trust in production.

• Accurate website categorization using AI: Klazify analyzes on‑site content (not just metadata), which helps produce meaningful clusters of similar domains even in niche markets. If you’re segmenting by product focus, editorial beat, or solution area, the underlying categorization lifts similarity results.
• Global coverage: Similar companies span regions and languages. Klazify’s content analysis adapts to multilingual sites, helping you discover peers across markets for broader enrichment and targeting.
• Real‑time classification: Rather than relying on stale lists, Klazify evaluates current content, so newly pivoted or rebranded sites still return relevant neighbors.
• Industry‑level categories (IAB): Similarity becomes more actionable when grounded in standardized taxonomies. You can combine “similar domains” with IAB categories from the categorization endpoint to route outcomes (e.g., whitelist by vertical, flag adjacency risks).
• Simple API integration: A single REST call returns a concise list of related domains. Integrate in minutes, then expand to categorization, logos, and company data as needed.
• Compliance and filtering ready: Use similarity to expand blocklists, vet partners, or create conservative clusters for brand‑safety use cases.

Scenario: from a single domain to a reliable competitor list

Suppose your product needs to enrich an inbound company domain with its top competitors so the sales team can tailor outreach. Or your ad platform wants to ensure placements don’t appear near close competitors. With Klazify, you’ll:

1. POST the domain to the Similar Domain endpoint.
2. Read the similar_domains list (up to 10 related sites).
3. Optionally call categorization to fetch IAB categories, logo_url, and company data for each neighbor to refine actions.
4. Cache results and handle unknowns gracefully.

What the response looks like and which fields to use

The categorization response below is the official sample. It shows how you can combine categories, logo, and company objects with similar_domains to enrich downstream pipelines such as blocking rules, CRM enrichment, or partner discovery.

{
    "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 use these fields:

• domain.categories: Identify the site’s topical focus and corresponding IAB taxonomy. Use this to constrain or score similarity results by vertical.
• domain.logo_url: Enrich UI and CRM records with a logo reference.
• objects.company: Useful for enrichment (name, location, employeesRange, revenue, tags, tech). These attributes help prioritize or cluster neighbors.
• domain_registration_data: Optional age/expiration context for fraud checks or lead scoring.
• similar_domains: The up to 10 related domains to act on (e.g., expand suppression lists, drive lookalike discovery, or power competitor widgets).

Make a Similar Domain request

Use a POST request with a Bearer token and a JSON body containing the URL you want to analyze. Replace YOUR_API_KEY with your token.

curl -X POST "https://www.klazify.com/api/similar_domain" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"url":"https://cbsnews.com"}'

Operational notes:

• Authentication: Bearer token in the Authorization header.
• Body: JSON object with a single url field.
• Failed or unreachable calls are not billed.
• Starter plan is $39.99/mo and includes a 7‑day trial. For details, see the Documentation.

Code sample: fetch and act on similar domains

The following Python example shows how to call the Similar Domain endpoint, normalize inputs, and cache results to limit repeated calls during high‑throughput processing.

import os
import time
import json
import requests
from urllib.parse import urlparse

API_KEY = os.getenv("KLAZIFY_API_KEY", "YOUR_API_KEY")
API_URL = "https://www.klazify.com/api/similar_domain"

# In-memory cache: domain -> { "similar_domains": [...], "ts": epoch_seconds }
CACHE_TTL_SECONDS = 7 * 24 * 3600  # Cache for 7 days
cache = {}

def normalize_domain(input_url: str) -> str:
    # Accept raw domains or URLs and return hostname without scheme/path.
    parsed = urlparse(input_url if "://" in input_url else f"https://{input_url}")
    host = parsed.hostname or input_url
    return host.lower()

def get_similar_domains(input_url: str):
    domain = normalize_domain(input_url)

    # Cache lookup
    now = int(time.time())
    if domain in cache:
        age = now - cache[domain]["ts"]
        if age < CACHE_TTL_SECONDS:
            return cache[domain]["similar_domains"]

    headers = {
        "Authorization": f"Bearer {API_KEY}",
        "Content-Type": "application/json"
    }
    payload = {"url": f"https://{domain}"}

    try:
        resp = requests.post(API_URL, headers=headers, data=json.dumps(payload), timeout=15)
        # Not billed if unreachable/failed; still handle errors explicitly.
        resp.raise_for_status()
        data = resp.json()

        # Defensive parsing: prefer an empty list when missing.
        similar = data.get("similar_domains") or []

        # Cache and return
        cache[domain] = {"similar_domains": similar, "ts": now}
        return similar

    except requests.exceptions.RequestException as e:
        # Network or HTTP error: don't raise in batch mode; log and degrade gracefully.
        print(f"Similar domain request failed for {domain}: {e}")
        return []

# Example usage
if __name__ == "__main__":
    target = "example.com"
    neighbors = get_similar_domains(target)
    print(f"Similar to {target}:")
    for d in neighbors:
        print(f"- {d}")

What to do with similar_domains next:

• Suppression lists: Add neighbors to a no‑bid/no‑serve set in your ad system to avoid competitor adjacency.
• CRM enrichment: Attach a “Top 10 peer domains” field on company records for SDR research and qualification.
• Content moderation: If a site is flagged, propagate scrutiny to its neighbors to reduce evasion.

Operational guidance for production use

Batching and throughput

• Batch your input domains and de‑duplicate before calling the API. Many users paste the same homepages repeatedly; a dedupe pass reduces calls substantially.
• Parallelize with a small worker pool and exponential backoff for transient network errors.

Caching and refresh cadence

• Cache by normalized hostname for 7–30 days depending on how dynamic your market is. The example above uses 7 days.
• Warm caches for your top domains during off‑peak hours if you have predictable traffic.

Handling unknown or new domains

• If similar_domains returns an empty list, treat it as “no known neighbors yet.” Fall back to high‑level categories via categorization for routing decisions.
• Queue a recheck in a few days; new sites may gain neighbors as content evolves.

Domain normalization

• Normalize inputs to the registrable domain (e.g., sub.example.co.uk → example.co.uk) when it makes sense for your business logic. At minimum, lowercase and strip paths/query strings.
• Preserve protocol (https) in the API body as shown in the examples.

Resilience and observability

• Log raw response payloads for a sample of calls to aid debugging and audits.
• Instrument success ratios and latency per endpoint. If a call fails, don’t block user flows—degrade gracefully to cached or default behavior.

Combining Similar Domains with Categorization

You’ll often want both a cluster of neighbors and the taxonomy signals that explain why they cluster. Use the main categorization endpoint to retrieve IAB taxonomy, logo, and company attributes for each neighbor you get from similar_domains. That lets you filter, score, or present the cluster in your UI.

Implementation tip: For each similar domain, optionally call categorization in a rate‑limited queue and merge results into your record model. Cache per domain to avoid N+1 storms.

Pipeline patterns for common teams

• Ad tech and brand safety: Given a publisher domain, fetch similar_domains and add them to sensitive placement lists. Then call categorization to confirm IAB vertical alignment before enforcing hard blocks.
• Content filtering: Use similar_domains to expand your block/allow sets when a site violates policy, so peers get closer review. Add domain_registration_data signals to prioritize investigations.
• CRM and lead enrichment: On signup, find neighbors to auto‑link “peer companies” in the contact’s account view. Pull logo_url and tags to improve SDR context.
• Cybersecurity and analytics: If a domain is suspicious, enumerate similar_domains and watch for correlated activity. Categorization helps separate false positives by vertical.

Field-by-field: what to persist

For each input domain, store:

• similar_domains: array of strings. Primary artifact for competitor clustering and expansion logic.
• domain.categories: array with name and optional IAB mapping. Useful for guardrails when acting on similarity.
• domain.logo_url: string. Display in UI and CRM.
• objects.company: structured object. Use to enrich records and power deduping/merging flows.
• domain_registration_data: optional context for risk scoring.
• success: boolean. Log for monitoring and retries.

Timestamp your cache entries and include the request domain and normalized hostname in your key so you can trace behavior across microservices.

Batching strategies and rate management

• Batch input lists and run through a worker pool. Many domains will repeat; deduplicate first.
• Apply a jittered backoff to avoid thundering herds during deploys or data replays.
• Use a dead‑letter queue for domains that repeatedly fail due to network errors; retry later. Failed or unreachable calls are not billed.

Testing and QA guidelines

• Create fixtures with domains across multiple verticals. Assert that similar_domains is non‑empty for known, content‑rich domains and empty or minimal for brand‑new sites.
• Validate IAB mappings returned by categorization against your internal taxonomy crosswalk.
• Monitor enrichment match rates over time. If results drift, increase cache refresh intervals or add validation logic (e.g., require at least one overlapping IAB category across neighbors).

Where to go from here

Most teams start with similar_domains for fast neighbor discovery, then selectively apply categorization to the top neighbors that pass business rules. Keep an in‑memory or Redis cache for low latency, and persist enriched clusters to your data warehouse for analytics and QA.

Explore additional capabilities and payload shapes in the Documentation, and see available integrations in the MCP.

FAQ

• How many similar domains can I expect? Up to 10 related sites are returned in similar_domains for a given input.
• What if the API doesn’t find neighbors? Treat an empty similar_domains as “no known neighbors yet.” Cache the empty result and schedule a refresh; optionally call categorization to make decisions by vertical.
• Can I submit either a raw domain or a full URL? Yes. Normalize inputs to a hostname on your side; the request body should include the url field as shown in the examples.
• Are failed or unreachable calls billed? No. Failed or unreachable calls are not billed.
• Where can I see all fields and endpoints? Refer to the Documentation.

Get started

Create your account to call the Similar Domain endpoint and start enriching your pipeline. Starter is $39.99/mo with a 7‑day trial. Sign up here: Register. Visit the homepage at https://www.klazify.com for product overview and links to more tools.