Search for companies matching your ICP criteria, such as location, industry, revenue and more.
"num_of_followers"
: ["1-50", "51-100", "101-1000", "1001-5000", "5001+"]
"headcounts"
: ["1-10", "11-50", "51-200", "201-500", "501-1000", "1001-5000", "5001-10000", "10 000+"]
website-aggregator
) will not be shown
'bit.ly', 'goo.gl', 'linktr.ee', 'buff.ly', 'sites.google.com', 'meta.com', 'facebook.com', 'instagram.com', 'linkedin.com', 'youtube.com', 'meetup.com', 'wixsite.com', 'wordpress.com', 'twitter.com', 'microage.ca', 'google.com', 'business.site', 'vimeo.com', 'medium.com', 'behance.net', 'github.io', 'calendly.com', 'upwork.com'
ValidationError
(free request), with Hint what location you need to edit.
industry_name
column as input.
ValidationError
(free request), with Hint what industry you need to edit.
limit_by = 5
, offset_by = 200
, and 3 of these companies do not have websites. Then you will see only 2 companies (despite the fact limit_by = 5).
[“academy”, “technician”]
will be passed to SN as “(academy) OR (technician)”.
[“world”]
will be passed to SN as “world”
(without parentheses)
[“(education AND management)”, “(project AND office)”]
without special characters (!@#$%^\\\\*(){}[]/\|)
["1-10", "11-50", "51-200", "201-500", "501-1000", "1001-5000", "5001-10000", "10 000+"]
time_cached=null
.
headcounts
, locations
, industries
, keywords
strict
[“company_locations”]
will perform post-filtering on a strict occurrence of company_locations
.exclude_ids
exclude_domains
Use 'Token <api-key>' as the value
200 / 200 (Companies not found)
The response is of type object
.