Give it a city + an industry. Get back a ready-to-work B2B prospect list — company name, website, email, phone, address, industry, and LinkedIn — as one flat row per lead, in a single run.

Most "leads" tools hand you either raw map listings (name + address, no way to reach anyone) or a domain-only list you then have to feed into a second actor to find emails, and maybe a third for phones. This actor runs that whole waterfall for you in one pass:

Google Maps search  →  visit each business website  →  harvest email + phone + socials  →  MX-verify  →  flat lead row

No chaining actors. No stitching datasets together. One input, one output, ready for your CRM or sequencer.

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What you get — one flat row per lead

Field	Description
company_name	Business name from Google Maps
website	Business website URL
email	Best harvested email (MX-verified when verification is on)
phone	Phone number (from Maps and/or the website)
address	Full street address
city / state / country	Address split into parts for filtering & dedupe
industry	Primary category (e.g. "Marketing agency", "Dentist", "Plumber")
maps_rating / maps_review_count	Google Maps social proof — qualify before you reach out
linkedin_url	Company LinkedIn profile, when linked from the site
all_emails	Every distinct email found (not just the primary)
email_status	valid · role · risky · invalid · found · none
email_source	Where the email came from (website_contact / website)
social_links	Other social profiles found (Twitter/X, Facebook, Instagram, …)
parse_confidence	0–1 quality signal per row
scraped_at	UTC timestamp

By default the actor returns only reachable leads — every row carries at least an email or a phone. Name-only listings you can't actually contact are dropped (and never charged). Flip requireContact off if you also want the no-contact places.

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Why one run instead of three

The cheapest way to get to a usable prospect list today is to chain: a Maps scraper → an email finder → a contact extractor, exporting and re-importing a dataset between each. That's three runs, three bills, and a brittle pipeline.

This actor bakes the proven contact-enrichment logic from our email-finder and website-contact-extractor directly into the Maps crawl. For each place that has a website, it fetches the homepage plus the highest-yield contact pages (contact / about / imprint / team), de-obfuscates the common name [at] domain [dot] com tricks, pulls emails, phones and social profiles, and — when verifyEmails is on — MX-verifies each address so you know the domain actually accepts mail before you send.

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Input

{
  "queries": [
    "marketing agencies in Austin TX",
    "dentists in San Francisco CA",
    "plumbers near Denver CO 80202"
  ],
  "maxResults": 50,          // places per query (1–300, auto-paginated)
  "requireContact": true,    // only return leads with an email or phone
  "verifyEmails": true,      // MX-verify each harvested email
  "language": "en",
  "country": "us",
  "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"] }
}

Tips

• One query ≈ one "industry in a city". For full coverage of a large metro, split into narrower queries (per neighborhood or sub-category) — Google itself caps a single area at ~120–300 places.
• Residential proxy is required: Google Maps blocks datacenter IPs. The GOOGLE_SERP proxy group does not support Maps — leave the default RESIDENTIAL.

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Output example

{
  "company_name": "Acme Marketing Co",
  "website": "https://acme.com",
  "email": "hello@acme.com",
  "phone": "+1 512-555-0100",
  "address": "500 Congress Ave, Austin, TX 78701, USA",
  "city": "Austin",
  "state": "TX",
  "country": "US",
  "industry": "Marketing agency",
  "maps_rating": 4.7,
  "maps_review_count": 88,
  "linkedin_url": "https://linkedin.com/company/acme",
  "all_emails": ["hello@acme.com", "info@acme.com"],
  "email_status": "valid",
  "email_source": "website_contact",
  "parse_confidence": 1.0,
  "scraped_at": "2026-06-14T12:00:00Z"
}

---

Pricing

Pay per enriched lead. You're charged only for billable leads — rows with a company name and at least one reachable contact (email or phone). Map listings that yield no contact are dropped at no charge, so you're not paying for rows you can't use.

Example: a run that returns 100 enriched leads costs 100 × the per-lead price. Empty shells dropped along the way are free.

Platform compute (proxy, runtime) is billed to your own Apify account at Apify's standard rates, as with every Store actor.

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Use cases

• SDR / outbound — build a targeted list of "industry in city" prospects with verified emails, ready to drop into your sequencer.
• Local market research — map every competitor in a category and metro, with ratings and review counts to gauge market density.
• Recruiting / agency prospecting — find businesses in a vertical and reach the right inbox without buying a seat in an enrichment SaaS.
• CRM enrichment — feed a list of "category + city" searches and get flat rows you can import directly.

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Notes & legal

This actor collects publicly available business contact information (the same data a person sees on Google Maps and on the businesses' own public websites). You are responsible for using the output in compliance with applicable laws and regulations (including GDPR/CCPA and anti-spam rules such as CAN-SPAM) and with the terms of the platforms you operate on. Verify consent and legitimate interest before sending marketing communications. The actor does not access private, gated, or login-protected data.

Email verification is performed at the MX layer (does the domain accept mail?). It does not guarantee that a specific mailbox exists — a full SMTP probe is unreliable on cloud infrastructure where outbound port 25 is blocked. email_status is an honest signal, not a delivery guarantee.

More scrapers from our toolkit

Building a data pipeline? These actors pair well with this one — each runs on your own Apify account with the same pay-per-result pricing, no subscription:

• Company Lookup Scraper
• Email Finder
• Epa Data Scraper
• Firmy Cz Scraper
• Gelbeseiten Directory
• Google Maps Leads

Chain any of them together from the Integrations tab (the Run succeeded trigger) to build a multi-step workflow — one actor's output feeds the next.

Usage statistics

This Actor creates a small, content-free summary at the end of each run. It is used only to monitor reliability and improve this Actor. A copy is saved as USAGE_STATS in your own Apify key-value store, so you can see the exact record created for your run.

Set disableUsageStats to true in the input to opt out. Nothing is sent then; your USAGE_STATS record only says that statistics were disabled.

Only these fields are recorded:

• schema version, Actor name and build number;
• UTC start and finish hour (not a precise timestamp);
• run duration, number of results and time to the first result, each as a coarse range;
• whether the result was empty, the end status, and an error type from a fixed list;
• memory setting and counts of charged events;
• names of the input fields you set, never their values;
• the selected option for input fields that offer a fixed list of choices (for example a sort order).

We do not collect input text, search terms, URLs, domains, usernames, email addresses, names, proxy credentials, tokens, scraped records, output items, raw error messages, stack traces, or hashes of any of those values. Records are kept for no longer than 13 months, used only as aggregated operational statistics, and never sold or shared.

Additional fields (Phase 2)

This Actor also records your Apify user ID, whether Apify marks the account as paying, the size range of list inputs, the selected country when the input offers a fixed list of countries, and one category from a fixed Actor taxonomy. We use these fields only for aggregate reliability, repeat-use and cross-Actor analysis; reports suppress any cell with fewer than five distinct users.

The same disableUsageStats: true input flag turns these fields off too. The user ID is removed after 13 months; we do not export, sell, share, or attempt to re-identify this data.

Run-outcome signals (v2)

To learn whether a run did what it was asked to do, the record also holds a few more coarse ranges and yes/no flags. None of them contains content:

• the result limit you asked for (a range, when the input has one) and what share of it was delivered;
• results delivered per input item you listed (a range);
• output quality as ranges: how fully the result fields were filled, the share of rows that look like errors, the share of duplicate rows, and how many different fields appeared. These are counted in memory while results are saved; no result content is kept;
• how the run was started (console, API, schedule, webhook, another Actor);
• how it ended: stopped by you, timed out, reached the requested limit, stopped by the charge limit, and how many times the platform moved the run;
• if this Actor reports it: how many items to process worked or failed (ranges) and one failure reason from a fixed list;
• a short code made from the names of the input fields you set, never their values.

Repeat-run fingerprint (v2)

When your Apify user ID is recorded (see above), the record also holds an 8-character one-way code made from your input (proxy settings left out) and this Actor's name. It only lets us see that the same account ran the same input again soon after an unsatisfying run; we never see the input itself. It is stored only in the database, never published, and reports use it in aggregate with the same five-user minimum. It is the one exception to the statement above that no hashes are collected, and disableUsageStats: true turns it off.