Verizon 10DLC Compliance Guide

Verizon 10DLC Framework

Behavioral analysis algorithms and trust score-based campaign throughput allocation

Verizon requires 10DLC registration via TCR with mandatory EIN/Tax ID verification for all business senders. The carrier deploys sophisticated behavioral analysis algorithms that monitor message volume patterns, keyword stuffing, anomalous sending behavior, and subscriber complaint rates. Campaign throughput limits are dynamically allocated based on trust score tier combined with use case category, with immediate suspension triggered by TCPA legal demands.

EIN Verification Required

Tax ID validation through IRS records and state business registration databases. DUNS accepted as alternative.

Pattern Detection Algorithms

Real-time monitoring for volume spikes, keyword stuffing, URL patterns, and anomalous sender behavior.

TCPA Legal Response

Immediate suspension upon receipt of cease-and-desist letters or litigation notices from subscribers.

Verizon's Unique Enforcement Approach

Dynamic Trust Score Adjustment: Ongoing compliance issues automatically reduce TCR trust score, lowering throughput limits and triggering manual campaign reviews

Subscriber Complaint Sensitivity: Elevated spam reporting rates result in immediate throughput reduction and compliance investigation without warning

Legal Demand Priority: TCPA cease-and-desist letters or litigation notices trigger immediate suspension pending legal review (typically 5-10 business days)

Industry Vertical Risk Scoring: Debt collection, credit repair, and financial services campaigns face enhanced scrutiny with FDCPA/Reg E compliance verification

Critical Success Factors for Verizon Approval

EIN Verification Accuracy: Tax ID must exactly match IRS records; typos or formatting errors trigger rejection
Trust Score Optimization: Aim for 75+ trust score to avoid manual review and maximize throughput (4,500 msg/min)
Volume Pattern Management: Avoid sudden traffic spikes >3x daily average; gradual ramp-up prevents algorithmic flags
Industry-Specific Compliance: Debt collection requires FDCPA time restrictions (8am-9pm local time); financial services need Reg E compliance

EIN/Tax ID Verification Process

Mandatory business identity validation through IRS and state records

Verizon EIN Verification Requirements

Verizon validates EIN/Tax ID against IRS records and state Secretary of State business registration databases. Verification typically processes within 3-5 business days for established businesses; newly formed entities may require 7-10 days for government database updates to propagate.

Required Information

9-digit EIN in format XX-XXXXXXX
Legal business name (exact match to IRS filing)
Business address matching state registration
Entity type (LLC, Corp, Partnership, Sole Prop)
State of incorporation/formation

Common Rejection Reasons

EIN formatting errors (missing dash, extra digits)
Business name mismatch (DBA vs legal name)
Newly issued EIN not yet in IRS database
Inactive or revoked business registration
Using personal SSN instead of business EIN

DUNS Number as Alternative Verification

Verizon accepts DUNS (Data Universal Numbering System) numbers from Dun & Bradstreet as alternative business verification method. DUNS verification typically provides faster approval and improved trust score compared to EIN-only verification.

DUNS Benefits

• Faster verification (24-48 hours)
• +10-15 trust score boost
• Demonstrates business legitimacy
• International recognition

How to Obtain

• Free registration at dnb.com
• 30-day processing time
• Requires business EIN
• One-time setup

When to Use

• New businesses (<1 year old)
• Trust score optimization needed
• Previous EIN verification issues
• International operations

Behavioral Analysis Algorithms

Real-time pattern detection for spam identification and compliance monitoring

Verizon's Pattern Detection Framework

Verizon deploys machine learning algorithms that analyze sender behavior patterns across multiple dimensions to identify spam, fraud, and policy violations before subscriber complaints accumulate. The system monitors message volume trends, content patterns, engagement rates, and complaint signals to generate dynamic compliance scores.

Volume Pattern Analysis

• Spike Detection: Traffic increases >3x daily average trigger automated review
• Timing Patterns: Off-hours messaging (11pm-7am) flagged as potential spam
• Burst Behavior: Rapid-fire messaging exceeding throughput limits throttled immediately
• Consistency Metrics: Erratic volume patterns suggest list-based spam campaigns

Content Pattern Analysis

• Keyword Stuffing: Excessive promotional language or repeated keywords flagged
• URL Patterns: Link shorteners, suspicious domains, or URL obfuscation detected
• Template Variation: Identical message content sent to large recipient lists
• Prohibited Terms: Cannabis, crypto scams, payday loans, get-rich-quick schemes

Engagement Metrics

• Opt-Out Rates: >5% STOP responses indicate consent quality issues
• Response Rates: Low engagement (<1% replies) suggests purchased lists
• Delivery Failures: High bounce rates (>10%) indicate stale data
• Click Patterns: Unusually high or low click-through rates analyzed

Complaint Monitoring

• Spam Reports: >0.1% spam rate triggers compliance investigation
• Carrier Complaints: Direct subscriber calls to Verizon customer service
• Legal Demands: TCPA cease-and-desist or litigation notices
• Regulatory Inquiries: FCC or state attorney general investigations

Best Practices to Avoid Algorithmic Flags

Volume Ramp-Up: Increase daily message volume gradually (20-30% per week) to avoid spike detection
Natural Timing: Send during business hours (9am-6pm local time); avoid late-night or early-morning messaging
Content Variation: Rotate message templates and personalize content to reduce identical-message flags

Quality Consent: Aim for opt-out rates <2%; higher rates indicate consent quality issues
List Hygiene: Maintain delivery success rates >90%; remove bounced numbers promptly
Engagement Focus: Target engaged subscribers; low response rates suggest purchased lists