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Qualify Leads with Salesforce, Explorium Data & Claude AI Analysis of API Usage

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Created by: explorium || explorium

explorium

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Last update 17 hours ago

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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 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.

Credentials Required

To use this workflow, set up the following credentials in your n8n environment:

Salesforce

  • Type: OAuth2 or Username/Password
  • Used for: Pulling lead reports and creating follow-up tasks
  • Alternative CRM options: HubSpot, Zoho, Pipedrive
  • Get credentials at Salesforce Setup

Databricks (or Analytics Platform)

  • Type: HTTP Request with Bearer Token
  • Header: Authorization
  • Value: Bearer YOUR_DATABRICKS_TOKEN
  • Used for: Querying product usage and API endpoint data
  • Alternative options: Datadog, Mixpanel, Amplitude, custom data warehouse

Explorium API

  • Type: Generic Header Auth
  • Header: Authorization
  • Value: Bearer YOUR_API_KEY
  • Used for: Business matching and firmographic enrichment
  • Get your API key at Explorium Dashboard

Explorium MCP

  • Type: HTTP Header Auth
  • Used for: Real-time company intelligence and supplemental research
  • Connect to: https://mcp.explorium.ai/mcp

Anthropic API

  • Type: API Key
  • Used for: AI-powered lead qualification and analysis
  • Get your API key at Anthropic Console

Go to Settings → Credentials, create these credentials, and assign them in the respective nodes before running the workflow.

Workflow Overview

Node 1: When clicking 'Execute workflow'

Manual trigger that initiates the lead qualification process.

  • Type: Manual Trigger
  • Purpose: On-demand execution for testing or manual runs

Alternative Trigger Options:

  • Schedule Trigger: Run automatically (hourly, daily, weekly)
  • Webhook: Trigger on CRM updates or new lead events
  • CRM Trigger: Real-time activation when leads are created

Node 2: GET SF Report

Pulls lead data from a pre-configured Salesforce report.

  • Method: GET
  • Endpoint: Salesforce Analytics Reports API
  • Authentication: Salesforce OAuth2

Returns: Raw Salesforce report data including:

  • Lead contact information
  • Company names
  • Lead source and status
  • Created dates
  • Custom fields

CRM Alternatives: This node can be replaced with HubSpot, Zoho, or any CRM's reporting API.

Node 3: Extract Records

Parses the Salesforce report structure and extracts individual lead records.

Extraction Logic:

  • Navigates report's factMap['T!T'].rows structure
  • Maps data cells to named fields

Node 4: Extract Tenant Names

Prepares 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'

Node 5: Query Databricks

Queries your analytics platform to retrieve API usage data for each lead.

  • Method: POST
  • Endpoint: /api/2.0/sql/statements
  • Authentication: Bearer token in headers
  • Warehouse ID: Your Databricks cluster ID

Platform Alternatives:

  • Datadog: Query logs via Logs API
  • Mixpanel: Event segmentation API
  • Amplitude: Behavioral cohorts API
  • Custom Warehouse: PostgreSQL, Snowflake, BigQuery queries

Node 6: Split Out

Splits the Databricks result array into individual items for processing.

  • Field: result.data_array
  • Purpose: Transform single response with multiple rows into separate items

Node 7: Rename Keys

Normalizes column names from database query to readable field names.

Mapping:

  • 0 → TenantNames
  • 1 → endpoints
  • 2 → endpointsNum

Node 8: Extract Business Names

Prepares company names for Explorium enrichment.

Node 9: Loop Over Items

Iterates through each company for individual enrichment.

Node 10: Explorium API: Match Businesses

Matches company names to Explorium's business entity database.

  • Method: POST
  • Endpoint: /v1/businesses/match
  • Authentication: Header Auth (Bearer token)

Returns:

  • business_id: Unique Explorium identifier
  • matched_businesses: Array of potential matches
  • Match confidence scores

Node 11: Explorium API: Firmographics

Enriches matched businesses with comprehensive company data.

  • Method: POST
  • Endpoint: /v1/businesses/firmographics/bulk_enrich
  • Authentication: Header Auth (Bearer token)

Returns:

  • Company name, website, description
  • Industry categories (NAICS, SIC, LinkedIn)
  • Size: employee count range, revenue range
  • Location: headquarters address, city, region, country
  • Company age and founding information
  • Social profiles: LinkedIn, Twitter
  • Logo and branding assets

Node 12: Merge

Combines API usage data with firmographic enrichment data.

Node 13: Organize Data as Items

Structures merged data into clean, standardized lead objects.

Data Organization:

  • Maps API usage by tenant name
  • Maps enrichment data by company name
  • Combines with original lead information
  • Creates complete lead profile for analysis

Node 14: Loop Over Items1

Iterates through each qualified lead for AI analysis.

  • Batch Size: 1 (analyzes leads individually)
  • Purpose: Generate personalized qualification reports

Node 15: Get many accounts1

Fetches the associated Salesforce account for context.

  • Resource: Account
  • Operation: Get All
  • Filter: Match by company name
  • Limit: 1 record

Purpose: Link lead qualification back to Salesforce account for task creation

Node 16: AI Agent

Analyzes each lead to generate comprehensive qualification reports.

Input Data:

  • Lead contact information
  • API usage patterns (which endpoints tested)
  • Firmographic data (company profile)
  • Lead source and status

Analysis Process:

  • Evaluates lead quality based on usage, company fit, and signals
  • Identifies which Explorium APIs the lead explored
  • Assesses company size, industry, and potential value
  • Detects quality signals (legitimate company email, active usage) and red flags
  • Determines optimal sales approach and timing
  • Connected to Explorium MCP for supplemental company research if needed

Output: Structured qualification report with:

  • Lead Score: High Priority, Medium Priority, Low Priority, or Nurture
  • Quick Summary: Executive overview of lead potential
  • API Usage Analysis: Endpoints used, usage insights, potential use case
  • Company Profile: Overview, fit assessment, potential value
  • Quality Signals: Positive indicators and concerns
  • Recommended Actions: Next steps, timing, and approach
  • Talking Points: Personalized conversation starters based on actual API usage

Node 18: Clean Outputs

Formats the AI qualification report for Salesforce task creation.

Node 19: Update Salesforce Records

Creates follow-up tasks in Salesforce with qualification intelligence.

  • Resource: Task
  • Operation: Create
  • Authentication: Salesforce OAuth2

Alternative Output Options:

  • HubSpot: Create tasks or update deal stages
  • Outreach/SalesLoft: Add to sequences with custom messaging
  • Slack: Send qualification reports to sales channels
  • Email: Send reports to account owners
  • Google Sheets: Log qualified leads for tracking

Workflow Flow Summary

  1. Trigger: Manual execution or scheduled run
  2. Pull Leads: Fetch new/updated leads from Salesforce report
  3. Extract: Parse lead records and tenant identifiers
  4. Query Usage: Retrieve API endpoint usage data from analytics platform
  5. Prepare: Format data for enrichment
  6. Match: Identify companies in Explorium database
  7. Enrich: Pull comprehensive firmographic data
  8. Merge: Combine usage patterns with company intelligence
  9. Organize: Structure complete lead profiles
  10. Analyze: AI evaluates each lead with quality scoring
  11. Format: Structure qualification reports for CRM
  12. Create Tasks: Automatically populate Salesforce with actionable intelligence

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.

Customization Options

Flexible Triggers

Replace the manual trigger with:

  • Schedule: Run hourly/daily to continuously qualify new leads
  • Webhook: Real-time qualification when leads are created
  • CRM Trigger: Activate on specific lead status changes

Analytics Platform Integration

The Databricks query can be adapted for:

  • Datadog: Query application logs and events
  • Mixpanel: Analyze user behavior and feature adoption
  • Amplitude: Track product engagement metrics
  • Custom Databases: PostgreSQL, MySQL, Snowflake, BigQuery

CRM Flexibility

Works with multiple CRMs:

  • Salesforce: Full integration (pull reports, create tasks)
  • HubSpot: Contact properties and deal updates
  • Zoho: Lead enrichment and task creation
  • Pipedrive: Deal qualification and activity creation

Enrichment Depth

Add more Explorium endpoints:

  • Technographics: Tech stack and product usage
  • News & Events: Recent company announcements
  • Funding Data: Investment rounds and financial events
  • Hiring Signals: Job postings and growth indicators

Output Destinations

Route qualification reports to:

  • CRM Updates: Salesforce, HubSpot (update lead scores/fields)
  • Task Creation: Any CRM task/activity system
  • Team Notifications: Slack, Microsoft Teams, Email
  • Sales Tools: Outreach, SalesLoft, Salesloft sequences
  • Reporting: Google Sheets, Data Studio dashboards

AI Model Options

Swap AI providers:

  • Default: Anthropic Claude (Sonnet 4)
  • Alternatives: OpenAI GPT-4, Google Gemini

Setup Notes

  1. Salesforce Report Configuration: Create a report with required fields (name, email, company, tenant ID) and use its API endpoint
  2. Tenant Identification: Ensure your product usage data includes identifiers that link to CRM leads
  3. Usage Data Query: Customize the SQL query to match your database schema and table structure
  4. MCP Configuration: Explorium MCP requires Header Auth—configure credentials properly
  5. Lead Scoring Logic: Adjust AI system prompts to match your ideal customer profile and qualification criteria
  6. Task Assignment: Configure Salesforce task assignment rules or add logic to route to specific sales reps

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.

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