How to Integrate Cricket URL Classification APIs

Why Klazify is the best API for classifying cricket-related websites

When your product needs to detect, categorize, and enrich cricket-focused URLs at scale—think live score portals, team pages, equipment stores, match analysis blogs, or tournament microsites—you can’t rely on shallow signals or outdated lists. You need an API that understands real content, updates in real-time, and maps results to industry-standard categories for ad tech, brand safety, CRM enrichment, and analytics. That’s exactly where Klazify excels for cricket URL classification APIs.

Klazify analyzes the full web page, not just metadata, and maps content to hierarchical, IAB-aligned categories. This approach is critical for the cricket domain, where subtle differences—like separating match commentary from betting content, or distinguishing grassroots clubs from professional leagues—directly impact targeting, filtering, and compliance workflows.

• Accurate website categorization using AI: Klazify’s models parse actual content across landing pages and deep links, allowing it to identify topics like match previews, player bios, tournament schedules, cricket gear reviews, and more—even when SEO metadata is sparse or misleading.
• Global coverage for international cricket: Cricket is truly global. Klazify handles multilingual pages and international domains (e.g., India, UK, Australia, Pakistan, South Africa), making classification robust across official boards, news outlets, and fan communities.
• Real-time classification: Cricket content shifts hourly during series. Klazify emphasizes current analysis so your pipelines can respond to new match pages, roster changes, or post-match articles without waiting on static lists.
• Industry-level IAB taxonomy mapping: You get granular, industry-standard categories suitable for ad targeting, contextual matching, and brand safety guardrails across cricket news, equipment, training, and more.
• Simple API integration: A developer-friendly REST endpoint returns categorization, logos, company metadata, similar domains, and additional domain signals in one response—ideal for shipping fast and maintaining fewer dependencies.
• Superior compliance and filtering: Use category-based controls to include or exclude cricket-adjacent topics, flag risky contexts, or segment professional vs. grassroots content sources.

The result is a high-signal classification service that understands cricket’s content ecosystem and scales with your ingestion volumes, across enrichment, compliance, analytics, and contextual targeting workloads.

The concrete scenario: control where cricket ads run, enrich signups, and audit inventory

Let’s ground this in real-world tasks:

• Brand safety for cricket ad buys: Ensure ads only run on verified cricket news, live score sites, or official team domains—exclude unrelated or sensitive contexts by category and confidence thresholds.
• CRM and lead enrichment: When a customer signs up with a domain from a cricket retailer or academy, enrich with company name, size, logo, and category tags so sales teams can prioritize outreach and routing.
• Inventory audits: If you run a sports ad network, programmatically check which partner pages are cricket-focused and whether any placements drift into off-topic content over time.

In all of these, you’ll send URLs or domains to a single API call and use the response fields—categories, logo URLs, company data, and similar domains—to power downstream automations with minimal manual review.

How Klazify classifies cricket URL content

From content to IAB-mapped categories

Klazify’s categorization engine reads what’s on the page—titles, headings, main text, and context-rich cues—then assigns hierarchical categories mapped to IAB taxonomy. That’s essential for cricket, where a “match report” differs contextually from “equipment reviews,” and “team roster” pages carry different ad suitability from “betting tips.”

Because the model operates at the page level, you can classify deep URLs (e.g., specific match pages) rather than relying on domain-only labels. This page-scoped capability helps teams maintain granular control over placements, blocks, and enrichment logic.

Signals beyond classification

The response also includes related signals that make your integration richer from day one:

• Logo URLs: Display consistent logos in dashboards, CRM enrichment, and UI overlays.
• Company information: If the domain belongs to a recognizable entity (e.g., a cricket retailer, a sports board, a league), you can retrieve its name, location, revenue, employee range, and tags.
• Similar domains: Discover related properties for expanded targeting lists or auditing coverage across the cricket ecosystem.
• Domain registration data: Leverage age and expiration insights as secondary quality signals for unknown cricket sites.

End-to-end path: from cricket URL input to action

1) Send a URL or domain to the Klazify categorize endpoint

Provide the cricket URL (like a club site, score service, or league page) to the endpoint. Keep classification per-page when your use case demands precision (e.g., distinguishing news articles from shop pages on the same domain).

2) Parse the response for categories and supporting fields

Use the categories array and confidence scores to decide whether to include, exclude, or queue for review. Store logos and company data for display and enrichment. Consider related domains as expansion candidates (or for de-duplication) in your index.

3) Apply business rules tied to cricket operations

• Ad tech: Approve placements only if the categories align with sports/cricket contexts at or above your confidence threshold, and avoid unrelated or sensitive contexts.
• Content filtering: Allow cricket education and training content on school networks, block off-topic or mature categories, and log exceptions for admin review.
• CRM enrichment: Auto-assign cricket retailers to a dedicated sales segment, enrich records with logo_url and company size, and alert BDRs for follow-up.

Example: Classifying cricket URLs with cURL and interpreting fields

Sample cURL request

Below is a straightforward request that classifies a target URL. Replace YOUR_API_KEY and the target with your cricket URL (e.g., a live score page or a team domain). This example demonstrates a typical flow for sending a single URL to the categorization endpoint.

curl -X POST "https://www.klazify.com/api/categorize" \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/x-www-form-urlencoded" \
--data-urlencode "url=https://www.espncricinfo.com/"

After this call, parse the JSON for categories, confidence, logo_url, and company objects. Use confidence thresholds to tune your filtering logic for cricket inventory, and store logo_url for UI or CRM enrichment.

Realistic JSON response example

Below is an example of the JSON structure you’ll receive. Use it as a template to understand where to extract fields (e.g., domain.categories[*], objects.company, similar_domains). This same schema applies when classifying cricket URLs or domains.

{
"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 read this when classifying cricket URLs:

• domain.categories: This is your primary decision field. Each category includes a confidence score. Map these to your cricket-specific rules (e.g., approve content in your sports categories; route other content for review).
• domain.logo_url: Ideal for showing official logos in dashboards when you monitor cricket inventory sources, or for enriching CRM records tied to cricket retailers/clubs.
• objects.company: Provides company name, location, and size metadata. When classifying cricket businesses (retailers, academies, leagues), this enriches B2B pipelines.
• domain_registration_data: Useful as a supplementary signal; for newly discovered cricket domains, you might weigh very young domains differently in risk models.
• similar_domains: Seed discovery and crawling for related cricket properties, or deduplicate overlapping sites across partners.

JavaScript example: ingest cricket URLs and parse core fields

Below is a simple JavaScript snippet illustrating how to call the endpoint and parse categorization and company fields for cricket content workflows. Adjust the URL variable to your target cricket property (e.g., a league’s fixture page or a cricket news landing page).

async function classifyCricketUrl(targetUrl) {
const res = await fetch("https://www.klazify.com/api/categorize", {
method: "POST",
headers: {
"Authorization": "Bearer YOUR_API_KEY",
"Content-Type": "application/x-www-form-urlencoded"
},
body: new URLSearchParams({ url: targetUrl })
});

if (!res.ok) {
throw new Error("Classification request failed: " + res.status);
}

const data = await res.json();

// Core extraction for cricket workflows
const categories = data?.domain?.categories || [];
const logoUrl = data?.domain?.logo_url || null;
const company = data?.objects?.company || null;
const similar = data?.similar_domains || [];

return { categories, logoUrl, company, similar, raw: data };
}

// Example usage:
classifyCricketUrl("https://www.espncricinfo.com/")
.then(result => {
console.log("Categories:", result.categories);
console.log("Logo:", result.logoUrl);
console.log("Company:", result.company);
console.log("Similar:", result.similar);
})
.catch(console.error);

In your pipeline, you’ll typically store the raw JSON for auditability while also normalizing a few top-level fields: the highest-confidence category, a boolean approved flag, and enrichment attributes like company name and logo URL.

Operational best practices for cricket URL classification at scale

Batching requests and queuing

For large crawls—e.g., auditing thousands of cricket content pages—batch your requests with a queue or worker pool. Throttle concurrency to match your throughput plan and retry transient failures with exponential backoff. Persist request payloads and responses for replay in case of downstream pipeline issues.

Caching per domain and per URL

Cricket homepages and team overview pages don’t change every hour. Cache results for a reasonable TTL (per domain and per URL). For rapidly changing pages like live scorecards, use a shorter TTL during match windows and a longer one off-season. Always include a “last-seen” and “last-updated” timestamp in your storage layer.

Handling unknown or new cricket domains

When a new cricket blog or club site appears, run full classification but apply conservative rules until enough data accumulates (e.g., require minimum confidence or a manual QA step). Store domain registration data as a secondary risk signal. Over time, your system can auto-promote stable, high-quality cricket content to trusted lists.

Mapping to your own taxonomy

Klazify yields categories in a hierarchical system mapped to IAB. If your internal taxonomy is sports-specific (e.g., “Cricket/Professional,” “Cricket/Grassroots,” “Cricket/Equipment,” “Cricket/Analysis”), maintain a mapping table from IAB categories to your business tags. Apply a tie-break rule for multiple categories: prefer the highest-confidence path; if multiple exceed a threshold, mark the item as multi-topic for more nuanced controls.

Deep dive: interpreting the response for cricket workflows

Focus on categories, confidence, and action thresholds

Use confidence to set thresholds per use case:

• Strict ad placements: Accept only if top category confidence exceeds your threshold; otherwise, queue for QA.
• Discovery crawls: Log all categories but only whitelist domains after a second pass confirms stability.
• CRM enrichment: Use categories to assign cricket-oriented lead owners or segments without blocking flows.

Companies, tags, and technologies

Company fields are helpful when your targets are cricket businesses. Tags can suggest a business model (e-commerce, B2C), while technologies give additional hints about size or maturity. Combine this with domain age to triage new cricket shops or academies for review by your sales or compliance teams.

Similar domains and coverage expansion

Once you successfully classify a high-quality cricket property, use similar_domains to discover peers. That’s powerful for coverage expansion in ad inventory, specialized directories, or sports analytics platforms. Deduplicate by canonical domain and store relational mappings for your team’s search and browse experiences.

Examples: repeated JSON schema to guide parsing and QA

Below are additional copies of the same JSON example structure. Include them in your documentation or QA checklists so engineers, data ops, and product managers can quickly reference field names and nesting while building classifiers, ETL jobs, or dashboards.

{
"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"
]
}

{
"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"
]
}

{
"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: integrating the categorize endpoint into your pipeline

Dataflow for cricket classification

Design the flow like a typical ingestion and enrichment pipeline:

• Collector: Feeds new cricket URLs (from crawlers, partner feeds, or application events) into a durable queue.
• Classifier worker: Pulls URLs, calls the categorize endpoint, applies validation, and saves normalized outputs to a datastore (e.g., a relational DB with JSONB or a document store).
• Rule engine: Consumes normalized data, applies business logic for approvals, blocks, enrichment updates, and dashboard flags.
• Indexing: Builds search and analytics views (e.g., by category, domain, or country) to support internal users and automated reports.

Response mapping and normalization

Normalize the following fields into your schema for consistent downstream usage:

• primary_category_name: highest-confidence category name from domain.categories.
• primary_category_confidence: the associated confidence value.
• approved_for_cricket_ads: boolean determined by your rules (e.g., category match + confidence threshold).
• logo_url: from domain.logo_url.
• company_name, company_url, employees_range, revenue: from objects.company.
• domain_age_date, domain_expiration_date: from domain_registration_data.
• similar_domains: array for expansion or dedupe logic.

Documentation reference

For implementation details, request patterns, and field behaviors, keep the official docs handy as you design your integrations and QA routines: Check out the full Klazify API documentation

Field-by-field comparison: what to use and when

Field	Purpose in cricket workflows	Common actions
domain.categories	Determine topical relevance and suitability	Approve/deny placements, assign review queues, segment inventory
domain.logo_url	Consistent identity in dashboards and CRMs	Store and display logos in UI and account records
objects.company	Business-level enrichment for cricket entities	Route leads, score accounts, augment analytics
domain_registration_data	Additional trust or recency signal	Flag brand-new domains for extra QA
similar_domains	Discover peers and expand coverage	Seed crawlers, deduplicate, form publisher clusters

Python example: classify and store results for cricket pipelines

This sample demonstrates parsing the response and preparing normalized fields for downstream databases or message buses. Replace the URL with any cricket page (team roster, match preview, academy site, equipment shop).

import requests

def classify_and_normalize(url):
headers = {
"Authorization": "Bearer YOUR_API_KEY",
"Content-Type": "application/x-www-form-urlencoded"
}
resp = requests.post(
"https://www.klazify.com/api/categorize",
headers=headers,
data={"url": url},
timeout=30
)
resp.raise_for_status()
data = resp.json()

categories = data.get("domain", {}).get("categories", [])
primary = None
if categories:
primary = max(categories, key=lambda c: c.get("confidence", 0.0))

normalized = {
"url": url,
"primary_category_name": (primary or {}).get("name"),
"primary_category_confidence": (primary or {}).get("confidence"),
"logo_url": data.get("domain", {}).get("logo_url"),
"company": data.get("objects", {}).get("company", {}),
"domain_registration_data": data.get("domain_registration_data", {}),
"similar_domains": data.get("similar_domains", [])
}
return normalized

# Example usage
if __name__ == "__main__":
result = classify_and_normalize("https://www.espncricinfo.com/")
print(result)

Store normalized outputs in your domain table alongside the raw payload for audits. This keeps your dashboards fast while preserving the full context for troubleshooting.

Real-world cricket use cases and how to implement them

Brand-safe cricket ad targeting

When buying impressions across sports inventory, your DSP or internal bidder can call Klazify to confirm the context of each page. Use categories and confidence to greenlight pages clearly related to cricket news, player interviews, or match analysis. Maintain exception lists for off-topic content on otherwise trusted cricket domains.

Content filtering for education and public Wi-Fi

Cricket content is typically appropriate for general audiences. Use categories to whitelist sports and training content, while keeping unrelated or sensitive contexts blocked. As new cricket sites appear, classify and add them into the whitelist if they meet your criteria, increasing safe access without manual curation.

CRM enrichment for cricket retailers and academies

When a new B2B signup arrives from a cricket equipment store or coaching academy, enrich the record using company name, country, employee range, and logo. This enables faster routing to the right sales team and better account scoring. Use similar_domains to find related outlets for prospecting lists.

Additional JSON schema reference copies for engineering teams

For engineering review and QA processes, including schema validation and field name verification, keep additional copies of the example structure available in your internal docs. The example below mirrors the same fields and nesting you will parse 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"
]
}

Benefits of accurate cricket content classification

• Better ad ROI and reduced risk: Only run ads next to relevant cricket content, protecting brand safety and improving engagement.
• Less manual review: Automate allowlists and exception handling with confidence-driven rules, freeing ops teams to focus on edge cases.
• Higher-quality enrichment: Add trusted metadata—logo, company details, related domains—to your records for better sales and analytics outcomes.
• Scalable content governance: Consistent rules applied to global cricket content, across languages and regions, improve governance and compliance posture.

Images: how to visualize cricket inventory health and coverage

Use the following visual concepts to track your cricket classification quality and breadth. Replace the src values with your own assets.

Future trends in cricket content classification

As cricket schedules expand across formats and leagues, classification systems must keep pace with rapid content creation and multilingual coverage. Expect increased emphasis on page-level context and semantic understanding, which Klazify already prioritizes. Teams will also demand richer domain signals—like similar domains and company tags—to power discovery and analytics beyond simple category matches.

With cricket’s global footprint, another trend is adaptive thresholds by region and seasonality. Systems that automatically tighten or relax confidence requirements during intense traffic spikes (like ICC tournaments) will improve both accuracy and throughput. Klazify’s real-time analysis pairs well with these evolving operational patterns.

Putting it all together for cricket URL classification APIs

To successfully classify cricket URLs at scale, wire a clean ingestion path into Klazify’s categorize endpoint, normalize the response with category and confidence, enrich records with logos and company fields, and persist similar_domains for discovery. Build rule layers that convert categories into actions—approve placements, whitelist content, or flag edge cases—and maintain caches that reflect cricket’s seasonality and update cadence.

The result is a resilient pipeline that knows cricket content when it sees it and turns that understanding into better ad placement, safer inventory, richer CRM data, and stronger analytics.

FAQ: Cricket URL classification with Klazify

How do I decide which cricket pages are safe for ads?

Use the highest-confidence category from domain.categories and compare it against your approved cricket categories. Set a confidence threshold appropriate for your risk tolerance and route borderline cases to manual QA.

Can I classify individual cricket articles instead of entire domains?

Yes. The categorize endpoint supports page-level classification, which is important for cricket sites that mix match reports, opinion pieces, e-commerce, and community posts.

What should I cache, and for how long?

Cache domain and URL results. Use longer TTLs for static pages (team history, about pages) and shorter TTLs for highly dynamic content (live scores, match reports during tournaments). Track last-updated timestamps to guide refresh policies.

How do I enrich CRM records for cricket businesses?

Extract company fields (name, location, employeesRange, revenue) and the logo_url from the response. Store them alongside your lead or account records to improve routing, scoring, and UI quality.

How can I discover more cricket sites similar to one I already trust?

Leverage similar_domains from the response as candidates for crawling and evaluation. Classify each candidate and apply your standard acceptance rules before whitelisting.

What if a new cricket site doesn’t map cleanly to my internal taxonomy?

Maintain a mapping from Klazify categories to your internal cricket tags. For ambiguous cases, store multiple tags with confidence scores and let your rule engine decide whether to approve now or queue for further review.

Where can I find the official field references and endpoint details?

Use the official documentation for request and response specifics, along with best practices for production integrations: Check out the full Klazify API documentation

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