lead rejection analysis

When leads are being rejected at higher rates than expected, this guide helps you diagnose the cause and implement solutions. Learn to use Events effectively, identify patterns, and communicate clearly with sources about requirements.

📍 You Are Here

You're investigating why leads are failing your acceptance criteria. This guide shows you how to find patterns in rejections, fix common issues, and improve your acceptance rates without compromising quality.

🎯 What You'll Learn

How to analyze rejection patterns using Events
Common rejection causes and fixes
Communicating requirements to sources
Balancing quality with acceptance rates

🔍 Step 1: Gathering Rejection Data

Using the Events System

Events provide complete visibility into why each lead was rejected:

Navigate to Events
- Open your flow
- Click the Events tab
- Filter by outcome: "Failure"
Identify Patterns
- Look at "Reason" column for rejection messages
- Note which sources have highest rejection rates
- Check timestamps for time-based patterns
Drill Into Specific Events
- Click any failed event
- Review the complete data received
- See exactly which rule failed

💡 Pro tip: Export Events data for deeper analysis in spreadsheets.

Common Rejection Reasons

Here's what to look for in your Events:

"Email address is required"

Source not sending email field
Field named differently than expected
Empty values being sent

"Invalid phone number format"

Type parsing found invalid format
Missing area code
International numbers not supported

"Outside service area"

State/zip not in accepted list
Geographic restrictions too narrow
Source sending wrong locations

"TrustedForm certificate invalid"

Certificate expired (>90 days old)
Certificate URL malformed
No certificate provided

📊 Step 2: Analyzing Patterns

By Source Analysis

Check if rejections are concentrated in specific sources:

Source A: 80% acceptance rate ✅
Source B: 45% acceptance rate ⚠️
Source C: 92% acceptance rate ✅

If one source has significantly lower acceptance, investigate:

Are their field mappings correct?
Do they understand your requirements?
Is their data quality different?

By Time Analysis

Look for time-based patterns:

Business hours vs after-hours

Different data quality at different times?
Automated vs manual submissions?

Day of week patterns

Monday rejections higher? (Weekend data buildup)
Friday quality issues? (End of week rush)

By Rejection Type

Group rejections by reason:

Field validation failures (40%)

Focus on field mapping fixes
Check type validation rules

Business logic failures (35%)

Review if criteria too strict
Consider source-specific rules

Compliance failures (25%)

Ensure sources understand requirements
Provide implementation guides

🛠️ Step 3: Common Fixes

Fix 1: Field Mapping Issues

Problem: Source sends phone_number, you expect phone

Solution: Add field mapping in source configuration:

Source Field: phone_number → Target Field: phone
Source Field: e_mail → Target Field: email
Source Field: fname → Target Field: first_name

See Field Mapping Guide for details.

Fix 2: Type Validation Too Strict

Problem: Valid data failing type parsing

Example: Phone 555.123.4567 rejected (dots not dashes)

Solution: Types handle various formats automatically, but check if:

Source sending unusual format
International data needs different type
Custom field needs different validation

Reference: Types Documentation

Fix 3: Acceptance Criteria Too Narrow

Problem: Good leads rejected by overly strict rules

Review your rules:

❌ Too strict: age is equal to 25
✅ Better: age is between 21 and 65

❌ Too strict: income is greater than 100000  
✅ Better: income is greater than 50000

See Acceptance Criteria Guide

Fix 4: Missing Required Fields

Problem: Source not sending all required fields

Solutions:

Make field optional if not critical
Set default value in mappings
Work with source to add field
Create source-specific criteria

📞 Step 4: Communicating with Sources

Creating a Requirements Document

Share clear requirements with your sources:

# Lead Submission Requirements

## Required Fields
- email (valid email format)
- phone (10-digit US phone)
- first_name (text)
- last_name (text)
- state (2-letter abbreviation)
- zip_code (5 digits)
- trustedform_url (valid TrustedForm certificate)

## Accepted Values
- States: CA, TX, FL, NY, PA
- Age: 21-65
- Certificate Age: Less than 90 minutes

## Submission Endpoint
POST https://app.leadconduit.com/flows/[ID]/sources/[NAME]
Header: X-API-Key: [their-key]

## Example Successful Submission
{
  "email": "john.doe@example.com",
  "phone": "555-123-4567",
  "first_name": "John",
  "last_name": "Doe",
  "state": "CA",
  "zip_code": "90210",
  "trustedform_url": "https://cert.trustedform.com/[token]"
}

Providing Rejection Feedback

Help sources understand why leads fail:

Daily Summary Email:

Yesterday's Performance:
- Submitted: 1,000 leads
- Accepted: 750 leads (75%)
- Rejected: 250 leads (25%)

Top Rejection Reasons:
1. "Invalid phone number format" - 100 leads
2. "Outside service area" - 75 leads  
3. "Missing email address" - 50 leads
4. "TrustedForm certificate expired" - 25 leads

Action Items:
- Ensure phones include area code
- Only send leads from: CA, TX, FL, NY, PA
- All leads must include email
- Submit within 90 minutes of capture

📈 Step 5: Optimization Strategies

Don't make all rules strict immediately:

Week 1: Basic validation only

Required fields present
Valid email/phone format

Week 2: Add quality filters

Geographic restrictions
Age requirements

Week 3: Full compliance

TrustedForm validation
Complete criteria set

A/B Testing Rules

Test rule changes on subset:

Create duplicate source
Apply new rules to test source
Compare acceptance rates
Roll out if improved

Source-Specific Optimization

Different sources may need different rules:

Premium Source Config:

Stricter quality requirements
Higher pricing for better data
Lower volume caps

Volume Source Config:

More permissive rules
Lower pricing
Higher volume caps

🎯 Quick Diagnosis Checklist

When investigating rejections:

Check Events for specific rejection reasons
Group rejections by source
Look for time-based patterns
Verify field mappings are correct
Review if acceptance criteria too strict
Check type validation on fields
Confirm sources understand requirements
Test with known good data

💡 Best Practices

Start Permissive: Begin with loose rules and tighten based on quality issues.

Clear Rejection Messages: "Phone area code 555 invalid" better than "Invalid phone".

Monitor Daily: Check rejection rates daily when making changes.

Document Changes: Track what rules you changed and why.

Communicate Proactively: Tell sources before changing requirements.

Events Reference - Deep dive into event data
Acceptance Criteria - Building better rules
Field Types - Understanding validation
Source Configuration - Source setup

📊 Data-Driven Decisions: Good rejection analysis turns frustrated sources into successful partners. Use Events data to make informed decisions about your acceptance criteria, and remember - the goal is quality leads, not just volume!

lead rejection analysis