Why Clay Users Need Unstuck Engine Integration
Clay excels at data enrichment and workflow automation, but lacks several critical capabilities that B2B teams need for effective lead qualification and prioritization:
The Clay Column Limitation Problem
Clay's action column limits (32 columns on paid plans, 40 on Enterprise) become a critical bottleneck when building sophisticated lead qualification systems. The challenge isn't storing data - it's the complex logic required for multi-dimensional scoring.
Multiple ICP scoring requires extensive formula logic:
Each ICP model needs 8-12 action columns for weighted scoring calculations
Multiple ICP models can require 25+ individual parameters to evaluate
Each parameter needs filtering, scoring, and weighting logic
Additional columns needed for persona matching algorithms
More columns for intent signal processing and decay models
With live intent signals, the math doesn't work:
3 ICP models × 10 scoring parameters = 30 action columns
5 columns for persona matching logic
8 columns for intent signal processing
5 columns for final weighted calculations
= 48+ action columns needed (exceeds even Enterprise limits)
Unstuck Engine solves this by moving all complex scoring logic to its AI engine, returning simple, pre-calculated scores via a single webhook. This frees up your action columns for workflow automation instead of manual scoring mathematics.
Missing Native ICP & Persona Capabilities
Unlike dedicated sales intelligence platforms, Clay doesn't natively support:
Multiple ICP models simultaneously - Most B2B companies need to score leads against different market segments or product lines
Dynamic persona matching - Automatic identification of decision makers, influencers, and champions within target accounts
Weighted scoring systems - Sophisticated algorithms that balance firmographic, technographic, and behavioral data
Intent Signal Aggregation Gap
While Clay can receive intent data from various sources, it cannot:
Automatically aggregate multiple signals into unified engagement scores
Apply decay models to time-sensitive intent signals
Cross-reference behavioral data with ICP/persona fit in real-time
Provide engagement staging (A-E levels) for prioritized outreach
Unstuck Engine fills these gaps by providing real-time intent signal aggregation from 20+ sources with automatic ICP and persona scoring, delivered as clean, actionable data to Clay.
Part 1: Receiving Enriched Data from Unstuck Engine in Clay
Quick Setup
In Clay: Create a webhook and copy the provided URL
In Unstuck Engine: Follow the Outbound Webhooks setup guide to configure your Clay webhook URL
Back in Clay: Map the incoming data fields to your table columns
Key Data Fields to Map
Consolidated Scoring (Replaces 15-20 Clay columns):
icp_score&icp_reason→ Single ICP qualification scorepersonas_codes&personas_score→ Multi-persona match in one fieldicp_version→ Track which ICP model was used
Aggregated Intent Intelligence:
action_intent→ Consolidated intent level (1st/2nd/3rd party)signal_action→ Behavioral trigger typetimestamp→ Real-time signal timing
Essential Contact Data:
person_name_full,person_email_company,person_jobtitlecompany_name,company_employee_count,company_industry
For complete field descriptions, see the Outbound Webhooks documentation.
Part 2: Sending Signals from Clay to Unstuck Engine
Quick Setup
In Clay, add HTTP API enrichment and create a new connection named "Unstuck Engine"
Configure POST method with your unique Unstuck Engine inbound webhook URL
Set up the JSON payload structure
API Configuration
Method: POST
Endpoint: Your unique Unstuck Engine inbound webhook URL (get this from the Inbound Webhooks setup guide)
Request Body:
{ "intent": "{{clay_intent_column}}", "linkedInProfileUrl": "{{clay_linkedin_url_column}}", "source": "{{clay_source_column}}", "additional_info": "{{clay_custom_info_column}}" }Common Use Cases
CRM Import for ICP Scoring:
{ "intent": "1", "linkedInProfileUrl": "{{clay_crm_linkedIn_url}}", "source": "{{clay_crm_sync}}", "additional_info": "{{clay_crm_lead_source}}" }Event Attendee Qualification:
{ "intent": "1", "linkedInProfileUrl": "{{clay_event_linkedIn_url}}", "source": "{{clay_events}}", "additional_info": "{{clay_event_name_role}}" }For complete payload structure and intent level definitions, refer to the Inbound Webhooks documentation.
Integration Benefits
Column Efficiency Gains
Before: 40+ columns needed for comprehensive lead scoring
After: Single webhook payload delivers all qualification data
Result: 35+ columns freed for additional workflow logic and data enrichment
Advanced Capabilities Unlocked
Multi-ICP scoring: Evaluate leads against different market segments simultaneously
Dynamic persona matching: Automatic identification of buyer roles and influence levels
Intent aggregation: 20+ signal sources combined into actionable engagement stages
Real-time updates: Scoring refreshes as prospect behavior changes
Best Practices
Workflow Optimization
Segment by ICP score: Create separate Clay workflows for different qualification tiers
Leverage engagement staging: Use A-E levels for appropriate campaign types
Monitor score velocity: Track prospects with improving qualification over time
Automation Tips
Enable auto-update for real-time data sync
Use conditional logic based on ICP scores to trigger different workflows
Set up alerts for high-scoring prospects (A-B engagement levels)
This integration transforms Clay from a data enrichment tool into a sophisticated B2B qualification engine, combining Clay's workflow capabilities with Unstuck Engine's AI-powered ICP scoring and intent aggregation.