Lead-Radar is a web-based platform that converts Google Maps search results into structured business prospecting data. It targets users who need to identify companies by keyword and geographic area, retrieve their public contact details, and add email addresses for outreach.
The process begins with a search combining a keyword and location, supported by an automatic geographic mesh that expands coverage. Extraction pulls business name, address, phone number, website, Google rating, and review count from publicly available information. An email sniper feature then scans each associated website to locate contact addresses, charging only when an email is successfully located. Users can also request an AI-generated prospect profile for each lead that lists the business activity, target clientele, key selling points, and a personalized commercial approach.
Results may be exported in CSV format at no extra cost. The service runs on a credit system in which each keyword search, each successful email enrichment, and each AI prospect profile consumes one credit. It is delivered entirely as a web application with no additional software required.
Pricing consists of monthly subscriptions and one-time credit packs. The Starter plan costs 49.90 euros per month for 100 credits, the Pro plan costs 99.90 euros per month for 220 credits, and an Enterprise option is available on request for custom volumes. Standalone packs range from 10 credits at 9.90 euros to 100 credits at 59.90 euros. A free trial provides five credits without requiring a credit card. The platform is created by Les Sens de la Com'.
Lead-Radar is a Lead generation & prospecting project. It focuses on automating the process of finding and enriching business leads from Google Maps for sales prospecting. It is built as a B2B product for sales professionals and marketers. Pricing is paid, from $54. It runs on the web and the command line.
Lead-Radar first shipped in 2024. Key capabilities include lead extraction, Google Maps integration, and email enrichment.
Summary written by a language model from the project’s public pages.
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