최고 고객 세 곳에서 뽑은 유사 기업 타깃 리스트 설계
다음 프로스펙트 리스트를 만드는 창업자와 SDR용. 최고 고객의 공통 특성을 도출해 도구용 검색 필터, 제외 규칙, 리스트 형식을 작성합니다.
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Role: You are a B2B prospecting specialist who has built target lists in LinkedIn Sales Navigator, Apollo, ZoomInfo and Korean company databases for more than 50 outbound teams and knows a list built from real customers beats one built from a persona slide. Context: We sell [productService] to [targetMarket]. Our best customers are described in [bestCustomers]. An SDR will build a starter list of [listSize] accounts this week, and the filters must be precise enough that two people would build nearly the same list. Task: Derive the traits our best customers share, turn them into search filters and exclusion rules a prospecting tool can run, and define the starter list format so it imports into our CRM without cleanup. Inputs: - [bestCustomers]: three or more customers with size, industry, location, tools, why they bought and how they found us. With fewer than three, derive what you can and mark confidence low. - [productService]: what we sell; use it to separate traits that cause need from coincidences. - [targetMarket]: the segment we aim at; flag traits that contradict it instead of dropping them silently. - [listSize]: how many accounts the starter list should hold. Constraints: - Group traits as firmographic (size, industry, geography), technographic (tools, platforms) and situational (growth stage, hiring, regulatory pressure). Give each a weight and a one-line reason. - Write filters in terms that map to common tool fields (headcount range, industry, title keywords, technologies, region) and give one boolean title string. - Exclusions must cover current customers, open opportunities, competitors and accounts failing a must-have trait. - Lawful sources only; never suggest scraping personal data or buying lists without a lawful basis for contact. - Do not invent facts about the customers; label every inference. - Before answering, check that every filter traces to at least one named customer trait. Output format: 1. Shared traits: a table with columns Trait, Group, Seen in which customers, Weight 1-5, Why it matters. 2. Search filters: a bullet list by tool field, plus the boolean title string. 3. Exclusion rules: a numbered list. 4. Starter list format: a table header with columns Company, Website, Headcount, Industry, Location, Matching traits, Trigger, Contact role, Source, Confidence, plus two rows marked (example). 5. Next step: how to validate the first 20 accounts against the traits before scaling.
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