Linkedin Jobs Scraping + Decision Maker Research
Shared 11/30/2025
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"jsonBody": "{\n \"publishedAt\": \"r604800\",\n \"saveOnlyUniqueItems\": false,\n \"startUrls\": [\n {\n \"url\": \"https://www.linkedin.com/jobs/search/?currentJobId=4266807332&f_E=4&f_SB2=4&f_TPR=r604800&geoId=102748797&keywords=superintendent%20construction&origin=JOB_SEARCH_PAGE_JOB_FILTER&refresh=true&sortBy=R&spellCorrectionEnabled=true\"\n }\n ]\n}",
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"content": "## Linkedin Jobs Scraper\n [Apify Scraper Link](https://apify.com/cheap_scraper/linkedin-job-scraper)"
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"content": "## Decision Maker Finder\n[Apollo API Documentation](https://docs.apollo.io/)"
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"jsCode": "const people = $json.people; // from Apollo People Search\nconst jobLocation = $('Get Jobs from Notion').first().json.property_location || \"\";\n\n// Normalize job location (e.g. \"Atlanta, GA\" -> city & state)\nconst [jobCityRaw, jobStateRaw] = jobLocation.split(\",\").map(x => (x || \"\").trim().toLowerCase());\nconst jobCity = jobCityRaw || \"\";\nconst jobState = jobStateRaw ? jobStateRaw.replace(/\\./g, \"\") : \"\"; // remove period from \"GA.\"\n\n// Define weights for Lucid’s target roles\nconst titleScore = {\n 'director': 5,\n 'manager': 4,\n 'partner': 4,\n 'lead': 3,\n 'specialist': 2,\n 'associate': 1\n};\n\nconst keywords = [\n 'recruiting',\n 'talent',\n 'acquisition',\n 'hr',\n 'human resources',\n 'people',\n 'operations',\n 'project',\n 'staffing'\n];\n\nconst scored = people.map(p => {\n const title = (p.title || \"\").toLowerCase();\n const seniority = (p.seniority || \"\").toLowerCase();\n const city = (p.city || \"\").toLowerCase();\n const state = (p.state || \"\").toLowerCase();\n \n let score = 0;\n\n // Title keyword match\n if (keywords.some(k => title.includes(k))) score += 5;\n\n // Add seniority weighting\n Object.keys(titleScore).forEach(level => {\n if (title.includes(level) || seniority.includes(level)) {\n score += titleScore[level];\n }\n });\n\n // Bonus for “Director”, “Manager”, “Partner” tier\n if (['director', 'manager', 'partner', 'lead'].some(l => title.includes(l))) {\n score += 2;\n }\n\n // 🟢 Location relevance scoring\n if (jobCity && city.includes(jobCity)) score += 4; // Same city\n else if (jobState && state.includes(jobState)) score += 2; // Same state\n\n return { ...p, relevanceScore: score };\n});\n\n// Sort descending by score and limit\nconst topPeople = scored.sort((a, b) => b.relevanceScore - a.relevanceScore).slice(0, 5);\n\nreturn topPeople.map(p => ({\n json: {\n name: p.name,\n title: p.title,\n seniority: p.seniority,\n linkedin: p.linkedin_url,\n city: p.city,\n state: p.state,\n relevanceScore: p.relevanceScore\n }\n}));\n"
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"text": "=You are an elite Senior Psychographic Researcher and Strategic Communication Analyst for Lucid Group, a staffing and recruitment agency specializing in construction, engineering, and professional services.\n\nYour expertise combines organizational psychology, psycholinguistics, and sales communication strategy.\nYou analyze professional signals (education, work experience, skills, job titles, industry, writing tone, leadership style, career progression, and public achievements) to infer deep insights into a person’s psychological profile, values, and communication preferences.\n\nYou translate those insights into tactical cold email hooks and message angles that resonate with the person’s mindset, priorities, and worldview.\n\nYOUR OBJECTIVE\n\nGiven public information scraped from a prospect’s LinkedIn profile, produce:\n\nA psychological and communication profile of the person.\n\nPredicted motivators and personality drivers (what matters most to them).\n\nPreferred communication style — how they think, how they talk, and what persuades them.\n\nCold outreach hooks & angles for Lucid Group that would best engage this person — referencing the way they view success, risk, leadership, and results in their work.\n\nOUTPUT FORMAT\n\nReturn a markdown response.\n\nGUIDING PRINCIPLES\n\nNever hallucinate data. Base insights strictly on what can be inferred from the provided text and professional signals.\n\nTreat professional history as a window into cognitive style. For example:\n\nEngineers → precision, stability, logic.\n\nProject Managers → control, communication, trust, reliability.\n\nExecutives → achievement, strategy, influence, legacy.\n\nTailor all conclusions and outreach angles to Lucid Group’s mission: helping construction companies staff skilled, reliable talent faster and with less operational risk.\n\nKeep the tone grounded, human, and practical — avoid generic personality adjectives.\n\nEvery insight should answer: “How would this person want to be approached, spoken to, and convinced?”\n\n\nHere is the information about the person:\n\nFull Name: {{ $json.fullName }}\nAbout Section: {{ $json.about }}\nLinkedIn Headline: {{ $json.headline }}\nCurrent Job Title: {{ $json.jobTitle }}\nTop Skills by Endorsement: {{ $json.topSkillsByEndorsements }}\nCurrent Job Location: {{ $json.experiences[0].caption }}\nMost Recent Job Title: {{ $json.experiences[1].title }}\nMost Recent Employer: {{ $json.experiences[1].subtitle }}\nMost Recent Job Duration: {{ $json.experiences[1].caption }}\n\nCollege they attended: {{ $json.educations[0].title }}\nCollege Major: {{ $json.educations[0].subtitle }}\nReview that the person left for colleague: {{ $json.recommendations[1].section_components[0].subComponents[0].fixedListComponent[0].text }}",
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}