AI Local Lead Finder
Find high-intent B2B leads from public business signals.
Searches public sources such as Google business listings, Yelp, TripAdvisor, reviews, websites, and directories to identify businesses that match a target ICP and show potential pain signals.
What you need to build this
Connect these tools, give the AI this data, expect these outputs.
Connect
APIs & tools to set up
OAuth, API keys, or webhooks depending on the tool.
Gather
Data sources to pull from
Give to AI
Inputs per run
- ICP definition: industry, geography, employee size proxy, revenue signals
- Google Places / Yelp search parameters (category, radius, keyword)
- Review text and ratings from listing pages
- Website URL and basic page content if available
- Exclusion list of existing customers or CRM accounts
Expect
AI outputs
- Filtered prospect list with business name, address, phone, website
- Pain signal tags (low rating, no website, stale reviews, unanswered complaints)
- ICP fit score (1–100) with reasoning
- Suggested outreach angle per lead based on detected signals
- CSV or CRM-ready import file
Business problem
B2B sellers waste hours manually searching Google Maps, Yelp, and directories to build prospect lists — and still miss businesses with visible pain signals like unanswered negative reviews or outdated websites.
Expected outcome
A scored prospect list filtered by geography, industry, and ICP criteria — each lead tagged with pain signals, contact info, and a one-line reason they're worth pursuing.
Who it's for: B2B agencies, SaaS companies, and local service providers selling to other businesses who need net-new prospect lists without expensive data subscriptions.
Required data sources
- Public Business ListingsView access method →
- Customer ReviewsView access method →
- Business WebsitesView access method →
- Industry DirectoriesView access method →
- TripAdvisor ListingsView access method →
What data goes into the AI
- ICP definition: industry, geography, employee size proxy, revenue signals
- Google Places / Yelp search parameters (category, radius, keyword)
- Review text and ratings from listing pages
- Website URL and basic page content if available
- Exclusion list of existing customers or CRM accounts
What the AI should output
- Filtered prospect list with business name, address, phone, website
- Pain signal tags (low rating, no website, stale reviews, unanswered complaints)
- ICP fit score (1–100) with reasoning
- Suggested outreach angle per lead based on detected signals
- CSV or CRM-ready import file
APIs needed to automate this
- Google Places APIAuth & setup →
- Yelp Fusion APIAuth & setup →
- Outscraper APIAuth & setup →
- OpenAI APIAuth & setup →
System behavior
- Runs on schedule (weekly) or on-demand per territory — not real-time
- Read-only on public sources — never contacts businesses automatically
- Respects API rate limits with batching and backoff
- Excludes businesses already in CRM or on do-not-contact list
- Logs search parameters and result counts for reproducibility
No-code vs low-code vs custom
No-code
Lowest effort
Non-technical owners, quick validation, under 50 runs/day
3 options listed
Low-code
Medium effort
Operators comfortable with Zapier/n8n, need more control
3 options listed
Custom build
Highest effort
High volume, custom logic, or strict data privacy requirements
5 options listed
| No-code options | Low-code options | Custom build stack |
|---|---|---|
| Outscraper Google Maps export → ChatGPT scoring in a Google Sheet | n8n: Places API search → Yelp enrichment → OpenAI pain scoring → Sheets | Node.js service querying Google Places Text Search API |
| Apify Google Maps scraper → Zapier → HubSpot import with GPT summary | Google Sheets + Apps Script + Places API + Claude for ICP filtering | Yelp Fusion business match for cross-validation |
| Clay.com enrichment table with Places + Yelp + AI columns | Make.com: Outscraper webhook → OpenAI → HubSpot contact create | Outscraper/Apify for bulk listing + review extraction |
| — | — | OpenAI structured output for ICP scoring and pain tagging |
| — | — | HubSpot or Salesforce bulk import endpoint |
Start with no-code to validate the workflow. Move to low-code when you hit rate limits or need branching logic. Custom build when volume, privacy, or integration depth requires it.
Step-by-step implementation
- 1Define ICP: target industries, cities, business size proxies, and disqualifiers
- 2Set up Google Places API key and Yelp Fusion app with rate limit handling
- 3Build search queries per geography — e.g., 'commercial cleaning' in Austin TX
- 4Pull reviews and website URLs; flag pain signals with a scoring rubric
- 5Run AI pass to score fit and draft one-line outreach angles
- 6Deduplicate against CRM before import; review top 20% manually before outreach
Risks and limitations
- Scraping TripAdvisor or directories may violate platform terms — prefer official APIs where available
- Public listing data can be stale — verify phone and website before outreach
- Cold outreach to scraped leads must comply with CAN-SPAM and local regulations
- Over-broad ICP definitions produce low-quality lists that waste sales time
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