✨Leads Finder — Effortless Data Extraction A cost-effective alternative to ZoomInfo, Lusha & Apollo. Get verified B2B emails, LinkedIn profiles, and rich firmographics at scale. --- ## 🚀 What this actor does Leads Finder generates targeted B2B contact lists using advanced filters (job title, Location/City, industry, tech stack, revenue, funding, etc.) and returns verified emails, mobile numbers (paying plans only), LinkedIn URLs, and detailed company data — ready for CRM or outreach. Free plan note: Users on the free Apify plan can fetch up to 100 leads/run. Support: codecrafter70@gmail.com --- ## 🧭 Quick start (UI) 1. Open the actor, set 📁 File name / Run label (optional). 2. Choose your filters (e.g., 👔 Job Title = "Marketing Manager", 🌍 Location = "United States", 🏭 Industry = "SaaS"). 3. Set #️⃣ Number of leads to fetch (default 50,000; leave empty to fetch all that match). 4. Click Run. When finished, download results from the Dataset tab or use the Overview table. > Location vs City: Use Location for a region/country/state. To target a single city, leave Location empty and use City only. (Same logic for the Exclude fields.) --- ## 🧩 Input schema (fields you can use) > Fields accept arrays unless noted. ### General * fetch_count (integer, default 50000) — Max leads to fetch. Leave empty to fetch all matches. * file_name (string) — Custom run label / export name. ### People targeting * contact_job_title / contact_not_job_title — Include/Exclude titles ("realtor", "software developer", "teacher", …). * seniority_level — Founder, Owner, C-Level, Director, VP, Head, Manager, Senior, Entry, Trainee. * functional_level — C-Level, Finance, Product, Engineering, Design, HR, IT, Legal, Marketing, Operations, Sales, Support. ### Location (Include) * contact_location — Region/Country/State (e.g., EMEA, United States, California, US). * contact_city — One or more cities (use this instead of Location when you want city-level targeting only). ### Location (Exclude) * contact_not_location — Region/Country/State to exclude. * contact_not_city — One or more cities to exclude. ### Email quality * email_status — validated, not_validated, unknown (prefill: validated) ### Company targeting * company_domain — Limit to specific domains (e.g., google.com, https://apple.com). * size — 0–1, 2–10, 11–20, 21–50, 51–100, 101–200, 201–500, 501–1000, 1001–2000, 2001–5000, 10000+ * company_industry / company_not_industry — Include/Exclude industries. * company_keywords / company_not_keywords — Include/Exclude free-text keywords. * min_revenue, max_revenue — Revenue bands (100K → 10B). * funding — Seed, Angel, Series A…F, Venture, Debt, Convertible, PE, Other. --- ## 📤 Output schema (what you get) Results are written to the run's Dataset and rendered in the Overview table with these columns: Person * first_name, last_name, full_name, job_title, headline, functional_level, seniority_level * email (verified when available) * mobile_number (available for paying Apify plan users only) * personal_email * linkedin (profile link) * city, state, country Company * company_name, company_domain, company_website (link), company_linkedin (link), company_linkedin_uid * company_size, industry, company_description * company_annual_revenue, company_annual_revenue_clean * company_total_funding, company_total_funding_clean * company_founded_year, company_phone * company_street_address, company_city, company_state, company_country, company_postal_code, company_full_address * company_market_cap (if public) Context * keywords, company_technologies --- ## 🔎 Examples ### Example 1 — US SaaS marketing leaders * contact_job_title: ["Head of Marketing","VP Marketing","CMO"] * functional_level: ["marketing"] * contact_location: ["united states"] * company_industry: ["computer software","internet","information technology & services","marketing & advertising","saas"] * email_status: ["validated"] * fetch_count: 5000 ### Example 2 — UK CTOs * contact_job_title: ["CTO","Head of Engineering","VP Engineering"] * contact_location: ["united kingdom"] * email_status: ["validated","unknown"] ### Example 3 — Amsterdam city-only (no broader Location) * contact_city: ["amsterdam"] * contact_location: (leave empty) --- ## ✅ Best practices * Location vs City: Choose one. Use Location for region/country/state or leave it empty and use City for city-only targeting. Same rule for Exclude. * Start broad, then narrow. Begin with Location + title, then add industry/revenue/funding. * Use include & exclude. Quickly remove irrelevant sectors with company_not_industry / company_not_keywords. * Prefer validated emails. Keep email_status = ["validated"] for outreach-ready lists; add unknown to increase volume. * Deduplicate downstream. If you merge runs, dedupe by email → linkedin → (full_name,company_domain). * Stay compliant. Use for B2B prospecting; follow GDPR/CCPA/PECR and local rules. --- ## 🧪 Output view (in the Apify UI) The Overview tab shows a sortable table with links for company_website, linkedin, and company_linkedin. Export any time to CSV/JSON/XLSX from the Dataset. --- ## 🧰 API usage Run via API with the same input JSON as the UI. 1. POST a run with your input JSON. 2. Poll for completion. 3. Fetch dataset items (JSON/CSV). (See Apify docs for runs, datasets endpoints.) --- ## 💵 Pricing & limits * From $1.5 / 1,000 leads (cheaper than typical ZoomInfo/Lusha/Apollo seat pricing). * On the free Apify plan, the platform caps at 100 leads/run. * Mobile numbers are only enriched and included for users on paying Apify plans. --- ## 🧯 Troubleshooting * Few or zero results? Loosen filters (remove company_not_*, broaden Location, allow unknown email status). Try title synonyms ("Demand Gen" vs "Growth Marketing"). * Too many results? Add industry, revenue, funding, or switch from region to country/state/city. * Geography mismatches? Don't mix broad regions with countries/states/cities; use either Location or City for the same target. --- ## ✨ Changelog (high level) * v1.1 — Simplified location filters: replaced Region/Country/State trio with Location (Region/Country/State) + City; mirrored for Exclude. * v1.0 — Initial release with People/Company/Tech/Revenue/Funding filters, validated email preference, and LinkedIn enrichment.