Identifying local businesses that may be relevant for a sales conversation often requires more than searching Google Maps. Teams may need to review whether a business is active, assess its digital presence, identify potential opportunity signals, remove duplicate locations, and find the right decision-maker before outreach can begin.
This use case explores how a connected automation can turn a single local-market search into a structured lead-generation process. The workflow collects business listings, filters and scores them, creates a deduplicated company list, and prepares suitable companies for decision-maker research and contact enrichment.
The Problem
Local-service businesses appear across Google Maps, but identifying which ones are worth approaching can require significant manual review. Teams may need to determine whether a business is open, already digitally established, actively managing its online presence, or likely to benefit from a particular service.
Once a relevant company is identified, outreach cannot begin until a decision-maker has been found and their contact information has been verified. This can make local prospecting slow, inconsistent, and difficult to manage at scale.
The Solution
The Google Maps Local Lead Generator turns a single search keyword into a scored and deduplicated list of local business leads.
The workflow collects business-listing information, filters closed businesses, scores each business using defined opportunity criteria, saves qualified companies into a central list, and prepares them for decision-maker research through Apollo.
The decision-maker search and contact-enrichment stages are built into the workflow but are currently paused pending review.
How the Agent Works
- Capture a local-market search. A user enters a keyword such as a service category and location into a connected spreadsheet.
- Collect relevant business listings. The workflow searches Google Maps and retrieves available business information, including address, phone number, website, ratings, reviews, and listing status.
- Score local-business opportunity. Each business is assessed using factors such as website presence, phone availability, listing status, ratings, reviews, and digital opportunity signals.
- Remove duplicate company records. Multiple locations from the same business are consolidated into one company-level record using the business website domain.
- Prepare companies for outreach. High-priority companies can move into a decision-maker search and contact-enrichment process for future sales activity.
Technical Workflow
1. Search entrypoint
A Google Sheets trigger watches a “Search Entrypoint” tab. Adding a new row with a Keywords value, for example, “bathroom remodeling in Portland, OR”, is all it takes to start a run.
2. Google Maps scrape via Apify
The keyword is passed to an Apify “Google Maps Scraper” actor, pulling up to 50 businesses per search with full listing details, address, phone, website, rating, review count, claimed status, and open/closed status, while skipping contact and review scraping to keep each run lean and fast.
3. Filter closed businesses
A filter node immediately drops anything flagged permanently or temporarily closed before it ever enters scoring.
4. Lead scoring
A detailed scoring function rates each business out of roughly 105 points across four weighted categories: engagement potential, rating plus review volume; accessibility, having a phone and specifically not having a website; business health, rating and review-count thresholds; and digital opportunity, unclaimed listings, especially combined with no website.
A hard penalty eliminates closed businesses outright. Each lead comes out with a leadScore, a normalized 0–100 score, a tier, Hot / Warm / Cold, an “easy target” label, Prime Target / Strong Opportunity / Standard, and a plain-English explanation string built from the same underlying factors.
5. Save scored leads
Every scored lead is appended or updated in a “Lead 2” sheet tab, deduplicated on Google Place ID, carrying the full listing details plus the entire scoring breakdown.
6. Route and deduplicate to company level
Leads are routed by tier, Hot / Warm / Cold, then a code node collapses everything down to one row per unique website domain, parsed and normalized from each listing’s website URL.
This is done because multiple Google Maps listings can belong to the same business, while outbound only needs one contact per company rather than one per storefront.
7. Save unique companies
Each deduplicated company, name, domain, category, address, phone, rating, score, and tier, is appended or updated in an “Unique Companies” sheet tab, matched on domain.
This becomes the seed list for the decision-maker search phase.
8. Decision-maker search via Apollo, built, currently paused
For companies not yet processed, a code node builds an Apollo people-search URL filtering for senior titles, owner, founder, C-suite, partner, VP, head, and director, within C-suite or HR departments, scoped to the batch of company domains just collected.
The workflow is ready to call Apollo’s people-search endpoint and surface named decision-makers at each business.
9. Dedupe against existing contacts
Before writing anything new, a Merge node compares incoming Apollo results against the existing “Contacts” sheet, keyed on Apollo Person ID, and keeps only the non-matches, so re-running the search never creates duplicate contact records.
10. Log new contacts
Each new decision-maker, name, title, company, LinkedIn URL, domain, and location, is appended to the Contacts sheet with a “Pending” processing status, queued for enrichment.
11. Bulk contact enrichment, built, currently paused
Pending contacts are batched 10 at a time, packaged into an Apollo bulk-match payload, by person ID, name, LinkedIn URL, and domain, and sent to Apollo’s bulk-match endpoint with personal-email reveal enabled.
The response is split out and used to fill in employee count, verified email address, and email-verification status back on each contact row, flipping its status to “Done.”
Technology and Integrations
Built with: n8n, Apify Google Maps Scraper, Apollo.io, Google Sheets, webhooks, and connected outreach workflows.
Outcome
The Google Maps Local Lead Generator creates a more structured approach to local-business prospecting.
A single keyword entered into a spreadsheet can produce a scored, deduplicated view of local business opportunity. Businesses with a phone number, no website, and an unclaimed listing can be identified as stronger prospects for outreach.
The Apollo phase, which is built but currently paused pending review, can extend the workflow from company discovery to decision-maker research and verified contact enrichment without requiring the user to leave the spreadsheet.
Explore Custom AI Automation for Your Business
The Google Maps Local Lead Generator is one example of how AI automation can support local-market research, lead scoring, decision-maker discovery, and outreach workflows.
Divverse Labs designs and builds custom AI agents, automation workflows, internal tools, and connected systems for a wide range of business processes.
From sales, marketing, recruitment, customer support, and reporting to finance, operations, and internal team workflows, each solution is designed around the way your business works.
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