Lead Radar 24/7 - Instant Buyer Discovery
Inside busy Facebook communities, prospective buyers regularly submit inquiries seeking vendors or recommendations: “Who has a 2-bedroom rental available?”, “Looking for a wholesale supplier”, “Need consultation on business insurance”.
These prospects are swarmed by competitors within minutes. If you are not alert the moment they post, you miss out on high-converting leads.
Lead Radar 24/7 transforms your browser into an automated radar that monitors community streams and notifies you the second a prospective customer speaks up.
🎯 Configuring Target Keyword Filters
Keywords are organized into two key categories:
1. Inbound Intent Keywords (Include)
Phrases signifying clear purchasing intent or product demand:
- Real Estate:
"looking to buy","need rental","budget under $500k","seeking 2BR" - E-Commerce & Supplies:
"wholesale prices","bulk order","looking for distributor" - Professional Services:
"recommend an agency","need quote","looking for developer"
2. Negative Exclusion Keywords (Exclude)
Filter out competing seller posts so your alerts remain clean:
- Exclude:
"for sale","selling now","discount available","hiring team"
[!TIP] Wrap exact phrases in quotation marks
""for strict string matching without false positives.
🔔 Real-Time Notification Channels
When Lead Radar flags a post satisfying your keyword rules:
- Audio Tone Alerts: Triggers a distinct audible alert even when your browser tab is minimized.
- Chrome Desktop Push Notifications: Pops an alert in the bottom corner of your display displaying the member name, target group, and a one-click “View Post” action.
- Telegram Bot Webhooks: Forwards the post snippet and direct link straight into your personal Telegram or sales team group chat for rapid outreach.
⚡ Lightweight Engine & Memory Footprint
Lead Radar is architected with extreme efficiency so it never bogs down your day-to-day machine:
- Polls minimal lightweight text feeds.
- Avoids fetching hefty media binaries or auto-playing videos.
- Background worker execution typically consumes less than 35MB of RAM.