Similar Profiles API: Build a Target List
By Kooperativa Engineering
A common prospecting problem: you have one great customer or one great prospect, and you want more people who look like them, but describing "look like them" as explicit search filters is harder than it sounds. Is the match on title, on industry, on seniority, on all three? A similar profiles endpoint solves this by doing that matching automatically, using the source profile itself as the query.
What "similar" is actually computed on
The response is explicit about which attributes drove the match, which matters because it tells you exactly what the result set is and is not controlling for:
{
"id": "f9413465-...",
"matched_on": {
"seniority": "c-level",
"industry": "Computer Software",
"country": "US"
},
"results": [
{
"id": "b9847f21-...",
"full_name": "Sundar Pichai",
"current_title": "CEO",
"current_company": "Google",
"seniority": "c-level"
}
],
"total": 1931,
"page": 1,
"per_page": 25,
"pages": 78
}The gap this endpoint does not close
matched_on here is seniority, industry, and country, not company size, not specific job function, not tenure. Two C-level executives in the same industry and country can run companies of very different sizes and be at very different stages of buying readiness. Similar profiles is a fast way to widen a target list from one example, not a substitute for a fully specified search once you know exactly which additional attributes actually matter for qualification.
A practical two-step pattern
Start from similar profiles to generate a wide candidate set quickly from a single known-good example, then run the resulting IDs through a fully filtered people search or bulk enrich to apply the harder qualifiers, company size, specific title keywords, exclusions, that the similarity match does not account for on its own.
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