How to Get Monthly Visits

You need to know how many visits a domain gets each month so you can make high‑stakes decisions: block low‑quality inventory, enrich a signup with traffic signals, or audit where your ads are actually running. By the end of this guide, you’ll call Klazify’s domain traffic intelligence endpoint, extract monthly_visits and related fields, and wire them into your pipeline with caching, batching, and fallback logic.

Why Klazify is the best fit for getting reliable monthly visit signals

Monthly traffic is only useful if it’s accurate, current, and tied to the broader profile of the domain. Klazify combines traffic intelligence with domain classification, logos, social profiles, and IAB-aligned categories, giving you traffic metrics in context.

• Accurate website categorization using AI: Monthly visits are far more actionable when you also know what the site is about. Klazify analyzes on-page content (not just metadata) to align sites with IAB categories, so you can weigh traffic by relevance for ad tech, brand safety, or filtering.
• Global coverage: Many domains serve non‑English audiences. Klazify handles multiple languages, so monthly visits reflect global usage patterns you can segment by top countries.
• Real-time classification: Traffic intelligence is only as good as its freshness. Klazify’s real-time classification helps ensure the category and context you attach to traffic metrics are up to date.
• Industry-level categories: Because Klazify maps to the IAB taxonomy, you can cross-reference monthly_visits with standardized industry categories in your downstream systems.
• Simple API integration: One REST call gives you traffic intelligence; pair it with categorization for a unified enrichment step in your ETL, CDP, or ad decisioning layer.
• Compliance and filtering: Combine monthly_visits with IAB categories to fine-tune allowlists, blocklists, and DLP controls by both content type and audience size.

For teams building domain intelligence at scale, it’s efficient to get traffic, categorization, and company signals from a single API. Start quickly with a free trial, then move to the Starter plan at $39.99/mo with a 7‑day trial. Failed or unreachable calls are not billed.

What you will build: a clean path to monthly_visits for any domain

You’ll implement a POST request to the traffic intelligence endpoint with a URL and read the following fields in the response:

• monthly_visits
• global_rank
• country_rank
• category_rank
• engagement
• traffic_sources
• top_countries

We’ll also show how to cache results per domain, retry gracefully, and map traffic metrics into your own scoring model.

Endpoint for traffic metrics: request and authentication

Use the traffic intelligence endpoint with a Bearer token and a JSON body that includes the URL you want to analyze. The following curl is copy‑pasteable; swap YOUR_API_KEY with your token.

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

The response will include traffic and engagement metrics for the domain you requested. Use HTTPS only. For production, set a short network timeout and implement retries with exponential backoff for transient errors. Failed or unreachable calls are not billed.

Reading the response: monthly visits and the fields you’ll wire up

When parsing the response, read the following fields directly:

• monthly_visits: numeric estimate of total visits in the most recent monthly window.
• global_rank, country_rank, category_rank: ranks that help you benchmark the site globally, in its top country, and within its content category.
• engagement: typically includes dwell-time or visit quality signals relevant for prioritizing where to place ads or which leads to qualify first.
• traffic_sources: distribution across sources such as search, direct, referrals, or social to understand acquisition mix.
• top_countries: which countries drive the most traffic, useful for geo-specific brand safety, compliance, and localization.

These fields are designed to drop into a scoring function. A straightforward approach is z-scoring or min-max scaling each metric, then combining with task-specific weights (for example, heavier weight on top_countries coverage if you’re geo-targeting).

Full categorization JSON you can use alongside traffic

Klazify can also classify the domain using the main categorize endpoint. Below is the official sample response you can reference to combine traffic intelligence with IAB-aligned categories, logos, and related company fields.

{
"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 you’ll use this with traffic intelligence:

• domain.categories: Drive brand-safety filters or contextual targeting rules that also consider monthly_visits.
• domain.logo_url: Show recognizable visuals when rating domains in internal tools.
• objects.company.*: Enrich CRM records with company name, size, and tags; pair with monthly_visits to qualify leads.
• domain_registration_data: Track recency and risk signals in combination with traffic changes.
• similar_domains: Suggest alternates when a domain lacks sufficient traffic or fails policy checks.

End-to-end code: fetch monthly visits and normalize them

The snippet below calls the traffic endpoint, extracts key fields, and shows a basic mapping strategy you can adapt to your pipeline. It assumes JSON responses with the fields described earlier.

import os
import json
import time
import requests

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

def get_domain_traffic(url, timeout=8, retries=2):
payload = {"url": url}
headers = {
"Authorization": f"Bearer {API_KEY}",
"Content-Type": "application/json",
}
for attempt in range(retries + 1):
try:
resp = requests.post(API_URL, headers=headers, json=payload, timeout=timeout)
# Failed or unreachable calls are not billed
if resp.status_code >= 500:
raise requests.RequestException(f"Server error {resp.status_code}")
data = resp.json()
return data
except (requests.Timeout, requests.RequestException) as e:
if attempt == retries:
raise
time.sleep(2 ** attempt)

def normalize_traffic(doc):
# Adapt to your schema. Illustrative only: read fields you need.
# Expect keys: monthly_visits, global_rank, country_rank, category_rank,
# engagement, traffic_sources, top_countries
return {
"monthly_visits": doc.get("monthly_visits"),
"global_rank": doc.get("global_rank"),
"country_rank": doc.get("country_rank"),
"category_rank": doc.get("category_rank"),
"engagement": doc.get("engagement"),
"traffic_sources": doc.get("traffic_sources"),
"top_countries": doc.get("top_countries"),
}

if __name__ == "__main__":
domain_url = "https://cbsnews.com"
doc = get_domain_traffic(domain_url)
traffic = normalize_traffic(doc)
print(json.dumps(traffic, indent=2))

Integrate this in your ETL: store results keyed by registrable domain (e.g., example.com), set a TTL (for example, a few days), and only refresh when expired to reduce latency and cost.

Practical pipeline design: batching, caching, and unknown domains

Batching at a high level

If you ingest many domains daily, group them by priority queues (e.g., active ad inventory first, then long‑tail). Use concurrent workers that each maintain their own retry/backoff logic. Respect service limits documented in the Documentation. If you reach backpressure, throttle producers and persist work in a durable queue.

Caching and TTLs

• Cache per registrable domain: normalize www.subdomains to their base domain unless you explicitly need subdomain granularity.
• Use a short TTL for fast‑moving sites; a longer TTL for stable sites. Store a last_seen timestamp and only refresh when expired.
• Cold-start handling: for new or unknown domains, proceed with a default “insufficient data” policy until the first successful response is cached.

Unknown or unreachable domains

• Network errors: retry with exponential backoff; failed or unreachable calls are not billed.
• No data yet: mark as pending and requeue with a deferred schedule. Do not block your main pipeline.
• Permanent failures (e.g., malformed URL): validate inputs early, log once, and drop.

Mapping traffic metrics to your taxonomy and controls

Monthly visits on their own aren’t a policy. You’ll often map them into your existing scoring or categorization:

• Ad tech and brand safety: Combine monthly_visits thresholds with IAB categories to allowlist well‑known, on‑topic properties and de-prioritize low‑traffic, risky categories.
• Content filtering: If a category is permitted but monthly_visits are extremely low, require additional signals before allowing it (e.g., domain age and engagement).
• CRM enrichment: Use monthly_visits alongside company size or tags to qualify leads with real audience reach.

If you maintain your own taxonomy, keep a table that maps IAB categories to your internal codes and apply it during enrichment, so monthly_visits ties back to internal segments without post‑processing.

Side-by-side: which fields to use for common decisions

Official categorization sample JSON (for reference #2)

You can use the same categorization output structure consistently across your pipeline. This is the official sample again for quick copy/paste into tests and mocks.

{
"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"
]
}

Official categorization sample JSON (for reference #3)

One more copy here so you can keep this post self-contained during development without hopping to another page.

{
"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 act on monthly_visits across common scenarios

• Blocking a category with low quality traffic: If domain.categories map to categories your policy disallows, block immediately. If allowed but monthly_visits are below a threshold, review other signals (engagement, domain age) before allowing.
• Enriching a signup: On form submit, look up the domain behind the email, fetch monthly_visits, and store it alongside company size. Use it for immediate tiering in your CRM.
• Auditing ad placements: Join impression logs (by domain) to monthly_visits and top_countries to ensure spend matches audience scale and geo targets.

Operational notes that save time

• Units: monthly_visits is a count of visits in a monthly window. Ranks are ordinal (1 is higher than 2).
• Timestamps and timezone: Store your own fetched_at timestamp (UTC) when persisting results. Refresh on your own cadence.
• Idempotency: Deduplicate by normalized domain (lowercase, ASCII/Punycode where relevant).
• Pagination: Not applicable to single-domain lookups. For bulk, orchestrate your own queues and checkpointing.
• Security: Keep API keys in a secret manager. Only expose normalized outputs to untrusted clients.

Where to go next

Pair traffic intelligence with categorization from the main endpoint to enrich analytics, content filtering, or ad decisioning in one pass. See the Documentation for request/response details across endpoints and learn how to manage your keys and usage in MCP.

FAQ

• Can I query subdomains or only root domains? Query with a full URL; normalize to the registrable domain in your cache unless you specifically need subdomain granularity. Many policies operate at the registrable domain level.
• How often should I refresh monthly_visits? Start with a TTL of a few days for high-importance domains and longer for long-tail. If a domain is pivotal for your decisions, refresh more often.
• What should I do if the API times out? Retry with exponential backoff and short timeouts. Log the failure and proceed with a safe default. Failed or unreachable calls are not billed.
• How do I map Klazify categories to my internal taxonomy? Maintain a mapping table from IAB categories to your internal labels. Apply it during enrichment so monthly_visits are stored against your own segments.
• Can I get traffic and categorization in one flow? Yes. Call the traffic intelligence endpoint for monthly_visits and related metrics, then the categorize endpoint for IAB categories and company enrichment. Cache both under the same domain key.

Spin up your integration now. Create a free account, get your API key, and start pulling monthly visits in minutes: Register. For full endpoint and field references, head to the Documentation.