Data Cooperatives in Direct Mail

Purpose: Explain how data cooperatives work and Path2Response’s position in the competitive landscape.

What is a Data Cooperative?

A data cooperative (co-op) is a group of companies that pool their customer transaction data to gain access to a larger universe of prospects. Members contribute their customer data and, in return, gain access to modeled audiences from the entire cooperative database.

Core Principle: Give data to get data. The more you contribute, the more value you can extract.

┌─────────────────────────────────────────────────────────────────────────┐
│                         DATA COOPERATIVE                                 │
├─────────────────────────────────────────────────────────────────────────┤
│                                                                          │
│   Member A ──▶ ┌─────────────────────────────────────┐ ──▶ Audiences    │
│   (Catalog)    │                                     │     for Member A  │
│                │      POOLED TRANSACTION DATA        │                   │
│   Member B ──▶ │                                     │ ──▶ Audiences    │
│   (Nonprofit)  │   • Billions of transactions        │     for Member B  │
│                │   • Modeling & scoring              │                   │
│   Member C ──▶ │   • Response prediction             │ ──▶ Audiences    │
│   (Retailer)   │                                     │     for Member C  │
│                └─────────────────────────────────────┘                   │
│                                                                          │
└─────────────────────────────────────────────────────────────────────────┘

How Co-ops Differ from List Rental

Co-op Membership Model

What Members Contribute

• Transaction data: Customer purchases, donations, orders
• Frequency: Weekly or more frequent updates
• Data elements: Name, address, transaction date, amount, product category

What Members Receive

• Access to universe: Prospects from other members’ customers
• Modeling: Propensity and affinity scores
• Suppression: Identify existing customers across sources
• Optimization: Score and rank rented lists against co-op data

Participation Requirements

• Minimum data contribution thresholds
• Data quality standards
• Ongoing update cadence
• Usage agreements and privacy compliance

Co-op Value Proposition

For Prospecting

Co-ops identify individuals who:

• Have purchased from similar companies (synergistic titles)
• Show recent transaction activity (recency)
• Demonstrate purchasing patterns matching your best customers (affinity)
• Have predicted likelihood to respond (propensity)

For List Optimization

When renting traditional lists, co-ops can:

• Score names against co-op data to predict response
• Suppress low-performers before mailing
• Identify multi-buyers appearing on multiple lists
• Lift performance by 15-70% through optimization

The Math

Traditional List Rental:
  100,000 names × 1.5% response = 1,500 responders

Co-op Optimized:
  100,000 names scored → 60,000 high-propensity names mailed
  60,000 names × 2.5% response = 1,500 responders

  Result: Same responders, 40% less mail cost

Competitive Landscape

Major Data Cooperatives

Epsilon/Abacus

• History: Epsilon (founded 1969) acquired Abacus Alliance
• Scale: Enormous - part of Publicis Groupe global marketing network
• Products: Abacus ONE (next-gen modeling), full marketing services
• Approach: Integrated with broader Epsilon marketing technology stack
• Positioning: Enterprise-scale, full-service

Wiland

• History: Launched as consumer intelligence co-op in 2004
• Scale: 160 billion+ transactions from thousands of sources
• Approach: Heavy ML/AI investment; does NOT sell consumer data directly
• Privacy: No SSN, credit card, or bank account numbers stored
• Positioning: Analytics-first, privacy-conscious

Path2Response Differentiation

• Digital integration: Site visitor identification + co-op transaction data
• Speed: Custom audiences delivered within hours
• Scale: Billions of transactions, 5B+ unique daily site visits
• Products: Path2Acquisition (prospecting), Path2Ignite (PDDM), Digital Audiences
• Focus: Performance-driven results (“Performance, Performance, Performance”)

Co-op Economics

Typical Fee Structures

• Membership fees: Annual or ongoing participation fees
• Usage fees: Per-campaign or per-thousand pricing
• Optimization fees: Additional charge for scoring rented lists (~$45/M)
• Minimum commitments: Volume or spend minimums

Value Drivers

1. Data breadth: More members = larger universe
2. Data depth: More transaction history = better models
3. Recency: Fresher data = better predictions
4. Modeling sophistication: Better algorithms = better selection

Why Multiple Co-ops Exist

Each co-op has:

• Different member mix: Different catalogs, nonprofits, retailers
• Different modeling approaches: Unique “secret sauce”
• Different data structures: Variables and attributes vary
• Different strengths by vertical: Some stronger in nonprofit, others in catalog

Result: The same individual may be scored differently by different co-ops. Sophisticated mailers test multiple co-ops to find best performers for their specific audience.

The Digital Evolution

Traditional co-ops focused on postal prospecting. The industry is evolving to support:

Path2Response’s digital strategy:

• Digital Audiences product (300+ segments)
• LiveRamp and Trade Desk partnerships
• Path2Ignite for programmatic direct mail
• Site visitor identification capabilities

Related Documentation

• Direct Mail Fundamentals - Industry overview
• List Rental & Exchange - Traditional list economics
• Competitive Landscape - Detailed competitor analysis
• Products & Services - Path2Response product portfolio
• Path2Acquisition Flow - How Path2Response’s solution works