B2B Lead Enrichment Suite

Why use this Actor?

A Google Maps search gives you a business name and a star rating -- not a usable sales lead. Getting from there to a contact-ready record normally means manually visiting each business's website to find an email, checking their tech stack by hand, and judging which ones are worth prioritizing.

This Actor automates that: it runs the search, visits each business's website, extracts emails and phone numbers, detects the technologies the site runs on, and computes a lead score so you can sort by priority instead of reading every row.

What you get

📍 Business data Name, address, rating, review count, and Google Maps link per result.	📧 Contact extraction Emails and phone numbers pulled from the business's own website when available.
🧰 Tech stack detection Technologies detected on the business website (e.g. Cloudflare, Angular, Magento).	🎯 Lead score A 0-100 score per lead based on whether decision-maker enrichment and emails are present.

How it works

Search queries
   |
Google Maps Email Extractor Pro (called internally)
   |
Business listings + website emails/phones/tech stack
   |
Decision-maker enrichment (currently disabled -- see below)
   |
Lead scoring + deduplication
   |
Dataset rows

This Actor is a thin orchestration layer: the actual Google Maps search, website visit, and extraction work is done by calling google-maps-email-extractor-pro directly through the Apify SDK (Actor.call(), resolved by actor id). A cost guard estimates the run's cost before any paid calls are made and aborts if it would exceed maxCostPerRun.

A note on LinkedIn enrichment

An earlier version of this Actor attempted to enrich leads with LinkedIn decision-maker profiles. That enrichment is currently disabled -- during testing, the LinkedIn-search Actor it depended on returned the identical placeholder result ("Satya Nadella, CEO at Microsoft") for every distinct query, meaning it wasn't actually searching. Shipping that would have attached a fabricated executive name to every lead, which is worse than shipping no enrichment at all. linkedin_profiles is currently always empty and has_decision_maker is always false until a real LinkedIn-search source is verified to return query-relevant results.

Use cases

• Build a targeted local-business prospect list by category and city
• Prioritize outreach using the lead score instead of contacting every result
• Identify which prospects already use a specific technology (for tools that integrate with it)
• Feed a CRM or outreach tool with pre-verified contact emails instead of guessed addresses

Input

Field	Type	Required	Default	Description
queries	array of strings	Yes	["restaurants in New York"]	Business search queries, e.g. "plumbers in Chicago".
maxResults	integer	Yes	25	Maximum businesses per query (1-1000).
webhookUrl	string	No	--	Optional URL notified on run completion.

Input example

{
  "queries": ["coffee shops in Seattle", "marketing agencies in Austin"],
  "maxResults": 25
}

Output

One dataset row per business found. Fields come from the underlying Google Maps extraction plus this Actor's own scoring:

Field	Type	Description
name	string	Business name.
address	string	Street address.
rating / reviewCount	string	Google rating and review count.
googleMapsUrl	string	Direct Google Maps link.
website	string	Business website, if found.
emails / phones	array	Contact details extracted from the website.
techStack	array	Technologies detected on the business website.
confidenceScore	number	0-1 confidence in the extracted data.
linkedin_profiles	array	Currently always empty -- see note above.
has_decision_maker	boolean	Currently always false -- see note above.
lead_score	number	0-100; higher when contact/decision-maker data is present.
source	string	"b2b_lead_enrichment_suite_v2".

Sample output

Real result from a live run:

{
  "query": "coffee shops in Seattle",
  "name": "Piedmont Café",
  "address": "1215 Seneca St Ste 100, Seattle, WA 98101",
  "rating": "4.8",
  "reviewCount": "290",
  "website": "https://piedmontseattle.com/",
  "emails": ["eben@eyebytes.com"],
  "phones": ["(206) 659-9899"],
  "techStack": ["Angular", "Google Analytics", "Bootstrap", "Magento"],
  "confidenceScore": 1,
  "linkedin_profiles": [],
  "has_decision_maker": false,
  "lead_score": 30,
  "source": "b2b_lead_enrichment_suite_v2"
}

Pricing

Pay-per-event: a small one-time actor-start charge, plus $0.003 per verified business lead returned.

Notes and limitations

• LinkedIn decision-maker enrichment is disabled (see above) until a real, verified data source is available -- lead_score currently reflects only whether an email was found, not decision-maker presence.
• Contact extraction depends on the business having a public website with visible contact information; not every business will have emails or a full tech stack detected.
• A cost guard aborts the run before any paid calls if the estimated cost exceeds maxCostPerRun (default $5).

Frequently asked questions

Does this include LinkedIn contacts? Not currently -- see the LinkedIn enrichment note above. linkedin_profiles will be empty on every result until this is re-enabled with a verified data source.

What happens if a business has no website? It's still returned with Google Maps data (name, address, rating), just without emails/phones/techStack.

Are failed queries charged? Only successfully returned leads trigger the per-result charge; the cost guard also prevents the run from starting if the estimated cost exceeds your budget.

Start building your lead list

Add your search queries and city, set a result cap, and run the Actor. Sort the resulting dataset by lead_score to prioritize outreach.

Related Actors

Calls Google Maps Email Extractor Pro internally for the underlying business search and contact extraction. Part of the same lead-gen catalog: ATS Hiring-Intent Lead Finder, Website Contact & Company Extractor.