Operation Manual: Advanced Domain Acquisition and Data Cleaning for Medical B2B Lead Generation

1. Scope and Prerequisites

This manual details the procedure for acquiring high-value expired domains, specifically targeting the medical and B2B sectors, and processing them for lead generation campaigns. The process leverages the SpiderPool platform and focuses on domains with a .com TLD, high Domain Authority (DA)/Page Authority (PA), and high Backlink (BL) profiles, often associated with entities like Kangya or similar China-based medical companies.

Prerequisites:

• Access to the SpiderPool domain auction/expired domains platform.
• A domain analysis tool (e.g., Ahrefs, Moz, Semrush).
• A secure server environment for data processing (e.g., Linux VPS).
• Python 3.8+ installed with libraries: pandas, requests, beautifulsoup4.
• Clear objectives for the target audience (e.g., medical equipment distributors, pharmaceutical companies).

2. Preparation

Before starting the acquisition process, define your target criteria and set up your environment.

1. Define Target Parameters:
   • Industry Keywords: "medical", "hospital", "biotech", "pharma", "kangya", "b2b", "supplier".
   • Domain Metrics: Target DA > 30, Referring Domains > 100.
   • TLD: Strictly .com.
   • Geo-Targeting: Focus on historical registration patterns indicating China-based company operations.
2. SpiderPool Account Configuration:
   • Log in to your SpiderPool account.
   • Navigate to the "Expired Domains" or "Auction" section.
   • Configure alert filters with the parameters defined above.
3. Setup Analysis Script: Create a directory and a Python script for initial data cleaning.

   
   # filename: domain_scanner.py
   import pandas as pd
   import sys
   
   def load_domain_list(filepath):
       """Loads a CSV file containing scraped domain data from SpiderPool."""
       try:
           df = pd.read_csv(filepath)
           print(f"Loaded {len(df)} domains.")
           return df
       except FileNotFoundError:
           print("File not found. Please export data from SpiderPool first.")
           sys.exit(1)
   
   if __name__ == "__main__":
       # This script will be expanded in the steps below.
       pass
           

3. Operational Procedure

1. Step 1: Sourcing and Shortlisting Domains

   Access the filtered list on SpiderPool. Export the list of potential domains (e.g., `spiderpool_export.csv`). The list should contain fields: Domain Name, Expiry Date, DA, PA, Backlink Count, Anchor Text.

   Screenshot Description: The SpiderPool interface showing a table of expired domains with columns for "Domain," "Authority Score," "Backlinks," and "Auction End Time." Several rows are highlighted where the domain name contains "med" or "health" and the DA is above 35.

2. Step 2: Initial Data Cleaning and Validation

   Run the initial cleaning script to remove obvious low-value entries.

   
   # Add to domain_scanner.py
   def clean_initial_data(df):
       """Performs initial filtering on the raw domain list."""
       # Filter for .com only
       df = df[df['Domain'].str.endswith('.com')]
       # Filter for high DA (example threshold)
       df = df[df['DA'] >= 30]
       # Drop rows with critical missing data
       df = df.dropna(subset=['Backlink Count'])
       # Remove domains with spammy keywords
       spam_keywords = ['casino', 'porn', 'adult', 'click-here']
       pattern = '|'.join(spam_keywords)
       df = df[~df['Domain'].str.contains(pattern, case=False)]
       print(f"After initial cleaning: {len(df)} domains remain.")
       return df
   
   # In main:
   df = load_domain_list('spiderpool_export.csv')
   cleaned_df = clean_initial_data(df)
   cleaned_df.to_csv('cleaned_domain_list.csv', index=False)
           

   Expected Result: A new CSV file, `cleaned_domain_list.csv`, containing a refined list of .com domains meeting basic quality thresholds.

3. Step 3: Deep Backlink Profile Analysis (Clean-History)

   This critical step involves analyzing the backlink history to ensure a "clean" profile, free from toxic or irrelevant links, which is paramount for medical sector credibility.

   • Import `cleaned_domain_list.csv` into your SEO tool (e.g., Ahrefs).
   • For each shortlisted domain, examine the "Backlink Profile" report.
   • Manually audit or use tool filters to:
     • Identify and flag links from irrelevant industries.
     • Check for links from penalized or low-quality sites.
     • Verify the prevalence of relevant anchor text (e.g., "medical device supplier," "clinical equipment").
     • Confirm a history associated with B2B or medical content.
   • Create a final shortlist of 5-10 domains with pristine, contextually relevant backlink profiles.

   Expected Result: A final, vetted shortlist of high-DP (Domain Power), high-BL, medically-relevant .com domains ready for acquisition.

4. Step 4: Acquisition and Configuration

   Place bids or purchase the selected domains through SpiderPool's auction system. Upon successful acquisition:

   1. Point the domain nameservers to your hosting provider.
   2. Set up 301 redirects from old, valuable pages (identified in backlink audit) to new, relevant content on your target site.
   3. Configure SSL certificates.
   4. Update domain registration information (WHOIS) as required.
5. Step 5: Integration into Lead Generation Workflow

   Develop targeted landing pages on the acquired domains or redirect traffic to your main B2B medical platform. Content should align with the domain's historical authority (e.g., a domain formerly about "hospital sterilization equipment" should now feature content on modern medical sterilization solutions).

4. Common Issues and Troubleshooting

Problem	Possible Cause	Solution
Exported list from SpiderPool contains non-.com or low-DA domains.	Filters were not applied correctly or saved before export.	Re-apply filters on the SpiderPool platform. Ensure "TLD=.com" and "Min DA=30" are set. Re-export the list.
Backlink profile shows sudden spam links from the past 6 months.	The domain may have been used for a "PBN" (Private Blog Network) or spam after expiration.	Reject this domain from your shortlist. The history is not clean. Focus on domains with a consistent, relevant link profile up to expiration.
Acquired domain does not pass traffic or regain ranking.	Search engine sandbox effect, incorrect redirect setup, or loss of critical backlinks.	1. Verify 301 redirects are implemented correctly. 2. Ensure the new content is high-quality and relevant. 3. Allow 4-8 weeks for search engines to re-index and recognize the change in authority.
Python script throws a "FileNotFoundError".	The CSV file is not in the same directory as the script or the filename is misspelled.	Check the file path. Use absolute path if necessary (e.g., /home/user/data/spiderpool_export.csv).
Difficulty finding domains specific to China-based medical companies.	Generic filters may not capture regional nuances.	In SpiderPool, use advanced search operators for keywords in Chinese pinyin (e.g., *kangya*, *yiliao*) and filter by past registration country code.