Block 1 - GET SF Report
- Type / Role
- n8n-nodes-base.httpRequest - httpRequest
- Config choices
- Version 4.2
This workflow is provided as-is. Please review and test before using in production.
Inbound Agent AI Powered Lead Qualification with Product Usage Intelligence This n8n workflow automatically qualifies and scores inbound leads by combining their product usage patterns with deep co...
n8n-nodes-base.httprequest, n8n-nodes-base.code, n8n-nodes-base.splitout, n8n-nodes-base.renamekeys, n8n-nodes-base.manualtrigger, n8n-nodes-base.salesforce, @exploriumai/n8n-nodes-explorium-ai.exploriumapinode, @n8n/n8n-nodes-langchain.lmchatanthropic
This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by explorium.
Original n8n.io sourceThis n8n workflow automatically qualifies and scores inbound leads by combining their product usage patterns with deep company intelligence. The workflow pulls new leads from your CRM, analyzes which API endpoints they've been testing, enriches them with firmographic data, and generates comprehensive qualification reports with personalized talking points—giving your sales team everything they need to prioritize and convert high-quality leads.
To use this workflow, set up the following credentials in your n8n environment:
AuthorizationBearer YOUR_DATABRICKS_TOKENAuthorizationBearer YOUR_API_KEYhttps://mcp.explorium.ai/mcpGo to Settings → Credentials, create these credentials, and assign them in the respective nodes before running the workflow.
Manual trigger that initiates the lead qualification process.
Alternative Trigger Options:
Pulls lead data from a pre-configured Salesforce report.
Returns: Raw Salesforce report data including:
CRM Alternatives: This node can be replaced with HubSpot, Zoho, or any CRM's reporting API.
Parses the Salesforce report structure and extracts individual lead records.
Extraction Logic:
factMap['T!T'].rows structurePrepares tenant identifiers for usage data queries.
Purpose: Formats tenant names as SQL-compatible strings for the Databricks query
Output: Comma-separated, quoted list: 'tenant1', 'tenant2', 'tenant3'
Queries your analytics platform to retrieve API usage data for each lead.
/api/2.0/sql/statementsPlatform Alternatives:
Splits the Databricks result array into individual items for processing.
result.data_arrayNormalizes column names from database query to readable field names.
Mapping:
0 → TenantNames1 → endpoints2 → endpointsNumPrepares company names for Explorium enrichment.
Iterates through each company for individual enrichment.
Matches company names to Explorium's business entity database.
/v1/businesses/matchReturns:
business_id: Unique Explorium identifiermatched_businesses: Array of potential matchesEnriches matched businesses with comprehensive company data.
/v1/businesses/firmographics/bulk_enrichReturns:
Combines API usage data with firmographic enrichment data.
Structures merged data into clean, standardized lead objects.
Data Organization:
Iterates through each qualified lead for AI analysis.
Fetches the associated Salesforce account for context.
Purpose: Link lead qualification back to Salesforce account for task creation
Analyzes each lead to generate comprehensive qualification reports.
Input Data:
Analysis Process:
Output: Structured qualification report with:
Formats the AI qualification report for Salesforce task creation.
Creates follow-up tasks in Salesforce with qualification intelligence.
Alternative Output Options:
This workflow eliminates manual lead research and qualification, automatically analyzing product engagement patterns alongside company fit to help sales teams prioritize and personalize their outreach to the highest-value inbound leads.
Replace the manual trigger with:
The Databricks query can be adapted for:
Works with multiple CRMs:
Add more Explorium endpoints:
Route qualification reports to:
Swap AI providers:
This workflow acts as an intelligent lead qualification system that combines behavioral signals (what they're testing) with firmographic fit (who they are) to give sales teams actionable intelligence for every inbound lead.
This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.
Showing the first 24 of 31 workflow blocks. Download the JSON for the full node graph.
| Workflow | Qualify leads with Salesforce, Explorium data & Claude AI analysis of API usage |
|---|---|
| Complexity | advanced |
| Nodes | 31 |
| Categories | Lead Generation, AI Summarization |
| Author | explorium |
| Published | 06 Nov 2025 |
Use the JSON export at /data/workflows/10560/10560.json as the source template for this automation.
Open n8n, import the downloaded JSON, and review each node before activating the workflow.
Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.
Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.
Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.
Inbound Agent AI Powered Lead Qualification with Product Usage Intelligence This n8n workflow automatically qualifies and scores inbound leads by combining their product usage patterns with deep co...
Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.
Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Lead Generation, AI Summarization use case.