Extract ICP leads from competitor engagement

Extract ICP-fit leads from competitor LinkedIn post engagers

Finding warm ICP-fit leads in one competitor's engaged audience when you have 1-2 days and a budget of 50+ Apify credits — not for weekly monitoring (too expensive) or precise targeting (keywords too loose).

• · Competitor LinkedIn company page URL(s)
• · Time window (days back, default 30)
• · Top N posts to extract from (default 1)
• · ICP keywords (job titles/roles, e.g., 'sales', 'SDR', 'revenue')
• · Exclude keywords (roles to filter out, e.g., 'software engineer')
• · Geographic focus (optional)

• · Deduped list of engagers (reactors + commenters) with ICP classification
• · Company enrichment data (industry, employee count, description, location) from Apollo
• · ICP score per lead: Likely ICP, Possible ICP, Unknown, Tech Vendor
• · Export-ready CSV/JSON with all data

• · Apify actor (harvestapi/linkedin-company-posts) with scrapeReactions: true, scrapeComments: true
• · Apollo.io API for company enrichment (optional, --skip-company-enrich flag)
• · Apify credits (varies by company page size)

• · Competitor must be a LinkedIn company page with public posts
• · Must have audience (reactions/comments) large enough to justify cost (~1 credit per post scraped)
• · User must supply ICP keywords + exclusions upfront

• · Can only scrape public posts (Apify limitation)
• · Engagement filters by time window reduce result set (short windows = small lead set)
• · Apollo enrichment adds cost and latency (~1 credit per unique company)
• · Headline keyword matching produces false positives (consultant + 'sales' might match 'VP Sales')
• · Company enrichment by industry keyword can miss niche ICPs

• · Two-step ranking: engagement score (commenters +3, reactors +2) + headline ICP keyword match (+2) + exclusion penalty (-5)
• · Config JSON structure with all filter mappings provided
• · Explicit database write policy: never export without user approval
• · CLI flags for cost control: --test (small limits), --yes (skip prompts), --skip-company-enrich (save credits), --top-n (override posts), --max-runs
• · Phase breakdown: Scrape, Rank, Enrich, Classify — with per-phase credit consumption tracked