Lead Enrichment Agent for Recruiting
An AI agent that handles lead enrichment for sales teams in recruiting & staffing businesses. Triggered by new spreadsheet row, it extracts structured data, classifies and categorises, updates the CRM record, running fully autonomously.
Raw leads with only a name and email are hard to prioritise. This agent enriches each lead with company data, job titles, social profiles, and firmographic details from public sources and your CRM — so your sales team works with full context from the first touch.
Ideal For
- Sales managers
- Account executives
- SDRs
- Teams in recruiting & staffing
Data Sources
- Spreadsheet (Google Sheets, Excel)
- CRM (Salesforce, HubSpot, etc.)
Trigger
Workflow starts when: New spreadsheet row
Collect Data
Retrieve data from: Spreadsheet (Google Sheets, Excel), CRM (Salesforce, HubSpot, etc.)
Extract structured data
Perform: extract structured data on the collected data
Classify / Categorize
Perform: classify / categorize on the collected data
Update CRM record
Perform: update crm record on the collected data
Log activity
Perform: log activity on the collected data
Complete & Log
Log activity, update records, and close the workflow
If: New lead added with email only
Then: Look up company domain, job title, and LinkedIn profile
If: Company data found matches ICP criteria
Then: Tag as high priority and route to senior SDR
If: Enrichment returns no results for company
Then: Flag for manual research and add to secondary queue
If: Duplicate lead detected in CRM
Then: Merge records and notify lead owner of the update
Never expose API keys or credentials in outputs
Only perform actions within defined workflow scope
- If enrichment APIs hit rate limits, queue remaining leads and retry in the next batch window
- If the returned company data conflicts with existing CRM records, flag for human review instead of overwriting
- Tasks processed per day
- Error/failure rate
- Enrichment match rate (% of leads successfully enriched)
- Data accuracy score vs. manual verification
- Time saved per lead vs. manual research
System Prompt
You are a Sales AI assistant specialized in lead enrichment. ## Your Role You help sales teams by automating lead enrichment tasks. Your communication style is concise. ## Capabilities You can: extract structured data, classify / categorize, update crm record, log activity. ## Guidelines - Always be accurate and verify data before acting - Flag uncertain cases for human review - Maintain professional tone - Never make promises or commitments on behalf of the organization - Respect data privacy and confidentiality - Log all significant actions for audit purposes ## Constraints - Only access data sources explicitly provided - Do not perform actions outside your defined scope - Escalate edge cases rather than guessing
Starter User Prompt
Process this spreadsheet row: [INSERT DATA HERE] Perform lead enrichment according to your guidelines. Provide: 1. Classification/analysis 2. Recommended action 3. Draft output (if applicable) 4. Any flags or concerns
Handoff Prompt
This task requires human attention. Here is what I have processed: ## Summary [Brief description of what was done] ## Analysis [Key findings and classification] ## Recommended Action [What should happen next] ## My Concerns [Any flags, uncertainties, or edge cases] Please review and respond when available. Please review and advise how to proceed.
# Lead Enrichment Agent - Standard Operating Procedure ## Purpose This SOP defines how the Lead Enrichment Agent operates within the organization. ## Trigger New spreadsheet row ## Data Sources - Spreadsheet (Google Sheets, Excel) - CRM (Salesforce, HubSpot, etc.) ## Process Steps 1. Extract structured data 2. Classify / Categorize 3. Update CRM record 4. Log activity ## Human Oversight None – fully autonomous ## Escalation Path 1. Agent flags issue 2. Notification sent to assigned reviewer 3. If no response in 4 hours, escalate to backup 4. Log all escalations ## Review Schedule Monthly review of agent performance and rules
- 1Define access credentials for all data sources
- 2Set up automation platform (n8n/Zapier)
- 3Configure AI API access (OpenAI/Claude)
- 4Create trigger workflow
- 5Connect input data sources
- 6Implement extract structured data step
- 7Implement classify / categorize step
- 8Implement update crm record step
- 9Implement log activity step
- 10Test with sample data
- 11Configure error handling and alerts
- 12Set up logging and monitoring
- 13Document and train team
- 14Deploy to production
- 15Schedule first review
n8n Workflow
## n8n Workflow Outline ### Trigger Node - Type: New spreadsheet row - Configuration: Set up webhook/schedule/email trigger ### Input Nodes - Spreadsheet (Google Sheets, Excel): HTTP Request or native integration node - CRM (Salesforce, HubSpot, etc.): HTTP Request or native integration node ### Processing Nodes 1. OpenAI Node: Extract structured data 2. OpenAI Node: Classify / Categorize 3. Function/HTTP Node: Update CRM record 4. Function/HTTP Node: Log activity ### Output Nodes - Update destination systems - Send notifications - Log activity
Zapier Zap
## Zapier Workflow Outline ### Trigger (Zap starts when...) - New spreadsheet row ### Data Lookup Steps - Search/Lookup in Spreadsheet (Google Sheets, Excel) - Search/Lookup in CRM (Salesforce, HubSpot, etc.) ### Action Steps 1. ChatGPT by Zapier: Extract structured data 2. ChatGPT by Zapier: Classify / Categorize 3. App Action: Update CRM record 4. App Action: Log activity ### Final Actions - Update records - Send completion notification
Example Use Cases
- •Enrich new leads with company data, job titles, and LinkedIn profiles automatically
- •Tag high-priority leads that match ICP criteria and route to senior SDRs
- •Detect and merge duplicate lead records in the CRM
Tools Needed
Frequently Asked Questions
What does the Lead Enrichment Agent do?
An AI agent that handles lead enrichment for sales teams in recruiting & staffing businesses. Triggered by new spreadsheet row, it extracts structured data, classifies and categorises, updates the CRM record, running fully autonomously.
Where does the enrichment data come from?
The agent pulls from public sources — company websites, LinkedIn profiles, business registries — as well as any third-party data providers you connect (e.g., Clearbit, Apollo).
How is this different from lead qualification?
Lead qualification scores leads against buying criteria. Enrichment adds missing data fields (company size, job title, industry) so that qualification and personalised outreach can be more accurate.
What happens when enrichment data is incomplete?
If the agent can't find reliable data for a field, it leaves it blank and flags the lead for manual research rather than guessing.
What level of technical skill is needed?
Basic familiarity with workflow automation tools (Zapier/n8n) is helpful. No coding is required for most implementations, though API integration experience helps for advanced setups.
Best For
- •Your SDRs spend 10+ minutes researching each new lead manually
- •Lead volume exceeds what the team can research before first outreach
- •Incomplete CRM records are hurting personalisation and conversion
Not Ideal For
- •Lead volume is fewer than 10 per week
- •Your leads already arrive with comprehensive data from the source
- •Manual research is a deliberate part of your sales process for relationship reasons
Review Before Launch
- All integrations tested with real credentials
- Error handling and retry logic configured
- Notification channels set up for alerts
- Team trained on reviewing exceptions
- KPI dashboard configured
- Rollback plan documented
Ready to implement your Lead Enrichment Agent? Use this blueprint to guide your setup in n8n, Zapier, or your preferred automation platform.
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