lead-extractorExtract structured real-estate lead records from parsed message objects. Use when users ask to find leads in WhatsApp exports, extract name-phone-budget, or...
Install via ClawdBot CLI:
clawdbot install vishalgojha/lead-extractorIdentify lead signals in parsed messages and emit strict lead objects.
message-parser -> lead-extractor -> india-location-normalizer
references/parsed-message-input.schema.json.references/extraction-rules-re-india-v1.md.dataset_mode from Supervisor context:broker_groupbroker_group, buyer_inquiry, mixedrecord_type:inventory_listing for broker inventory/availability posts (default in broker groups)buyer_requirement for explicit "required/chahiye looking for" demand postsnoise_or_systemlead_id, name, phone, record_typedataset_mode, property_type, budget, deal_type, asset_class, price_basis, area_sqft, area_basis, location_hint, raw_text, source, created_at+91 98205 82462 and 98200 78845.3.5 Lakh rent (monthly), 60K psf (per-sqft), 4.25 Cr (total)references/output-leads.schema.json.Generated Mar 1, 2026
A real estate brokerage firm uses the Lead Extractor to process WhatsApp group chats where brokers post property listings and buyers inquire about properties. The skill automatically extracts structured lead records, identifying broker inventory posts as 'inventory_listing' and buyer inquiries as 'buyer_requirement', enabling the firm to quickly capture and prioritize potential deals from daily communication.
A property listing portal integrates the Lead Extractor to analyze user-submitted messages or chat exports, extracting key details like budget, property type, and location hints. This enriches lead profiles for targeted marketing and improves matchmaking between buyers and sellers by converting unstructured text into actionable data points.
An investment firm uses the Lead Extractor to monitor WhatsApp groups for real estate trends, extracting lead data on property prices, area, and demand patterns. This helps analysts identify market opportunities, such as high-demand areas or budget ranges, without manual review of chat logs.
A real estate developer employs the Lead Extractor to process customer inquiries from WhatsApp support chats, automatically extracting contact details and property requirements. This streamlines lead qualification, allowing the support team to focus on high-potential leads and reduce response times.
Offer the Lead Extractor as a cloud-based API service with tiered pricing based on usage volume, such as number of messages processed per month. This model targets real estate agencies and tech startups, providing recurring revenue through monthly or annual subscriptions for automated lead extraction.
Sell customized integrations of the Lead Extractor into existing CRM or property management systems for large real estate firms. This involves one-time setup fees and ongoing support contracts, generating revenue from implementation services and maintenance agreements tailored to specific business workflows.
Package extracted lead data into anonymized datasets or insights reports for market research companies or investors. Revenue comes from selling aggregated data on real estate trends, such as budget distributions or location preferences, derived from processed chat messages.
💬 Integration Tip
Ensure input messages are pre-parsed using the recommended message-parser skill to validate schema compliance before extraction, and chain with india-location-normalizer for accurate location data in Indian contexts.
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