Sales Lead Discovery and Procurement Customer Mining

The Problem It Solves

Sales and procurement teams face a critical challenge: how to efficiently and accurately identify potential clients from vast amounts of public bidding information that align with their products or services, and obtain actionable leads for follow-up? Manual searching and filtering of bidding announcements is inefficient and risks missing key details or contact information.

How It Works

This skill addresses this issue through an automated data pipeline. It is not merely an information query tool but a lead mining system that integrates multiple data sources and analytical logic. Its workflow is tightly focused on the bidding sales scenario, primarily involving these steps:

1. Data Acquisition & Initial Filtering: The skill first translates a user's described product capabilities (e.g., 'industrial sensors') into a set of structured procurement keywords (e.g., 'sensor procurement', 'online monitoring equipment'). It then calls the core bidding search API (e.g., searchProjectApi) to retrieve tenders, awards, competitive consultations, and other announcements within specified time, region, and budget ranges.
2. Structured Detail Retrieval & Company Profiling: For high-match projects in the results, the skill further calls a structured detail API (e.g., getZTBStructreDetail) to obtain granular information like specific procurement requirements, budgets, deadlines, and agencies. Simultaneously, for identified purchasing entities (Party A), it invokes company profile summary (companyProfileSummary) and company contact (companyProfileContacts) APIs to gather public background information and contact leads.
3. Transparent Scoring & Lead Segmentation: This is the skill's core analytical capability. Instead of just listing facts, it quantitatively evaluates each lead based on a default 100-point scoring rule (e.g., need fit 35 pts, procurement stage 20 pts, timeliness 15 pts). The scoring is based entirely on verified, fact-based API outputs—missing data fields receive 0 points—ensuring the analysis is transparent and explainable. Based on scores, the system automatically categorizes leads into 'Priority Follow-up', 'Monitor', and 'Low Match' tiers.

Applicability and Key Considerations

Please note that the skill's output is an assistive analysis, not a final sales decision. Key points to acknowledge:
- Data Timeliness & Accuracy: Results are based on public information; the project status (e.g., whether the deadline has passed or it's been canceled) may have changed. The validity of contact phone numbers requires manual verification. Contacts from different sources (project details vs. company profiles) must be annotated separately.
- Scores are Analysis, Not Facts: Lead scores are the skill's analytical judgment based on rules applied to facts. They do not equate to the certainty of a project. Critical information like procurement budget and progress must be verified through official channels.
- Operational Constraints: The skill adheres to strict API call conventions, querying no more than 50 items per page and only adding detailed queries for high-match projects to avoid unnecessary resource consumption. It does not generate or fabricate any simulated leads not returned by the APIs.
- Keys and Security: Normal operation requires a valid API key, which must be securely configured and will never be disclosed in the output.

In summary, this skill transforms scattered bidding information into a structured, scored list of sales leads with actionable recommendations, providing a powerful data-driven starting point for a team's customer discovery efforts.