get https://api.explorium.ai/v1/businesses/autocomplete
Endpoint: GET /businesses/autocomplete
GET /businesses/autocomplete
Description
The Fetch Business Autocomplete endpoint provides real-time suggestions for business-related fields, helping users quickly find relevant categories, locations, and industries based on partial text input. This is useful for creating dynamic search fields and enhancing user experience in filtering interfaces.
Coverage
Attribute | Coverage Details |
---|---|
Supported Fields | Country, Region, Google Category, NAICS Category, LinkedIn Category, etc. |
Geographic Scope | Supports 150+ countries |
Response Time | Optimized for real-time autocomplete functionality |
How It Works
- Input: Specify a field type (
country
,region_country
, etc.) and provide a partial query string. - Processing: The system searches through indexed datasets to return the most relevant suggestions.
- Output: A structured response containing suggested values for the given input.
Query Parameters
Parameter | Type | Description |
---|---|---|
field | String | The field for which autocomplete is requested (e.g., country , industry ). |
query | String | Partial text input to generate suggestions. |
Example Request (cURL)
curl -X GET \
"https://api.explorium.ai/v1/businesses/autocomplete?field=country&query=unit" \
-H "API_KEY: your_api_key_here"
📌 Supported Autocomplete Fields & Example Inputs
Filter | Description | Example Input |
---|---|---|
country | Autocomplete for country names | "Uni" → United States, United Kingdom |
country_code | Autocomplete for country codes (ISO 2-letter) | "US" → United States |
region_country_code | Autocomplete for region-based country codes | "EU" → European Union countries |
google_category | Google’s business category classification | "E-com" → E-commerce |
naics_category | Industry classification based on NAICS codes | "541512" → Computer Systems Design Services |
linkedin_category | Industry classification from LinkedIn data | "Retail" → Retail Industry |
company_tech_stack_tech | Technologies used by a company | "Cloud" → Cloud Computing, Cloud Security |
job_title | Autocomplete for job titles | "Soft" → Software Engineer, Software Developer |
company_size | Autocomplete for company sizes (by number of employees) | "500" → Companies with ~500 employees |
company_revenue | Revenue-based classification (K, M, B, T for thousands, millions, billions, trillions) | "100M" → $100 Million+ |
company_age | Company age in years | "10" → Companies older than 10 years |
job_department | Autocomplete for job departments | "Eng" → Engineering, Product Engineering |
job_level | Job seniority levels | "Senior" → Senior Manager, Senior Engineer |
Example Response
[
{
"query": "unit",
"label": "United States",
"value": "us"
},
{
"query": "unit",
"label": "United Kingdom",
"value": "gb"
},
{
"query": "unit",
"label": "United Arab Emirates",
"value": "ae"
},
{
"query": "unit",
"label": "Tanzania, United Republic Of",
"value": "tz"
},
{
"query": "unit",
"label": "United States Minor Outlying Islands",
"value": "um"
}
]
Best Practices
- Use precise queries to get the most relevant autocomplete results.
- Optimize search fields by implementing real-time feedback mechanisms.
- Restrict field selection to avoid unnecessary queries and improve API efficiency.
- Combine with filtering APIs to refine user selections dynamically.
📌 Explore the sections above for additional query examples and integration guidelines.
Body Params - Try Me Example
field: country
query: unit