Observed Signal · Jul 20, 2026 · Product Launch · Source: https://martechseries.com/feed/ · Impact: 2/5 · Sentiment: Neutral
Leadsscraper.io Launches Google Maps Data Scraper
Leadsscraper.io has launched a Google Maps Data Scraper to help sales, marketing, and research teams collect structured, publicly available business information from Google Maps. The tool extracts fields such as company names, addresses, phone numbers, websites, ratings, reviews, categories, hours, and geographic coordinates, and allows exports into common formats for CRM systems, spreadsheets, and analytics. Users can search by category, keyword, city, postal code, or geographic area. Leadsscraper.io positions the product as part of a broader suite of lead-generation tools for building targeted local lead lists and conducting market and competitor research.
A small vendor product launch that provides useful local business data and export capabilities for lead generation; relevant to sales and local marketing but not industry-shifting.
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Key Takeaways & Evidence Grounding
- Leadsscraper.io launched a Google Maps Data Scraper to collect publicly available business information from Google Maps.
- The scraper extracts company names, addresses, phone numbers, websites, ratings, reviews, categories, business hours, geographic coordinates, and other profile details.
- Users can search by business category, keyword, city, postal code, or geographic area and export data into formats for CRM systems, spreadsheets, and marketing platforms.
- Leadsscraper.io offers the Google Maps Data Scraper alongside other lead generation tools aimed at sales, marketing, recruitment, and business intelligence.
Connected Companies & Entities
3 Entities mapped“The Google Maps Data Scraper extracts valuable business information... from Google Maps....”
“MarTech Series (MTS) is a business publication dedicated to helping marketers get more from marketing technology through in-depth journalism...”
“As part of the iTech Series network, it acts as a "Brand to Demand" partner....”
Ontology Mapping & Concepts
Related Market Signals & Shifts
Recent verified developments and strategic activity across this market segment.
Outscraper Adoption Grows for Google Maps Scraper
Outscraper reported increased adoption of its Google Maps Scraper as more agencies, sales teams, marketers, recruiters and researchers use automated tools to collect publicly available business listings for business intelligence. The cloud-based scraper extracts Google Maps data fields such as company names, phone numbers, websites, addresses, business categories, ratings and reviews. Use cases cited include lead generation, market analysis, local SEO research and multi-location prospecting. Outscraper has expanded integrations and export capabilities so collected data can be pushed into CRM systems, outreach tools, spreadsheets and reporting platforms to support scalable, automated location-based data workflows.
AI-Powered Google Maps Scraper for Lead Generation
A developer post describes GMapsScraper AI (gmapsscraper.io), a SaaS tool that uses a headless browser plus AI to extract and structure local business data from Google Maps for lead generation. The author details the tech stack (Next.js 14 frontend, Cloudflare Workers, Supabase, and a Go-based scraper on Google Cloud Run), engineering challenges (rate limits, data accuracy, speed) and their solutions (rotating proxies, randomized delays, browser fingerprint rotation, AI-based normalization, parallel scraping with a job queue). Reported results include 200+ leads per search, average responses under 30 seconds, and support for 18 languages. The product offers CSV export for CRM import and a free trial with no credit card required.
Developer Releases AI Web Data Extractor API
A developer published an AI Web Data Extractor API that combines fast HTTP scraping (Axios + Cheerio) with a Puppeteer browser fallback to extract structured data from arbitrary URLs. Implemented in Node.js, the extractor can return product data (title, price, image), emails, and article metadata, and uses a heuristic to auto-fallback to browser rendering when static scraping yields weak results. The API is available via RapidAPI and the author provides code snippets (fetchStatic, fetchBrowser, extractProduct) plus an example POST request/JSON response. The post lists real use cases (SaaS, price tracking, lead generation), implementation challenges (anti-bot measures, messy price formats), and planned additions such as proxy rotation, CAPTCHA bypass, and LLM-based parsing and page classification.
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