Customer Data Platform (CDP) RFP Template

Request for Proposal: Customer Data Platform (CDP)

Table of Contents

1. Introduction and Background
2. Technical Requirements
3. Functional Requirements
4. AI-Powered Features
5. Integration and Scalability
6. User Experience and Interface
7. Security and Compliance
8. Implementation and Support
9. Pricing and Licensing
10. Vendor Information
11. Evaluation Criteria
12. RFP Response Format and Submission Guidelines
13. Timeline

1. Introduction and Background

• Organization description
• Current data management challenges
• Reasons for seeking CDP solution
• Primary goals for CDP implementation

2. Technical Requirements

Data Integration and Collection

• Ability to ingest data from various sources with support for structured and unstructured formats
• Real-time processing capabilities to ensure timely updates

Data Storage and Management

• Indefinite storage of customer data while adhering to privacy regulations
• Centralized database architecture for easy access to customer information

Identity Resolution

• Cross-channel identity matching to create a holistic view of customers

Security and Compliance

• Strong encryption protocols for data protection
• Compliance with industry regulations (GDPR, CCPA) including role-based access controls

Scalability and Performance

• Ability to scale with increasing data volumes without performance degradation
• High availability to ensure uptime of the platform

Integration Capabilities

• Robust APIs for seamless integration with existing martech stacks
• Pre-built connectors for popular third-party applications

Analytics and Reporting

• Features for analyzing customer behavior and campaign performance
• Customizable dashboards for displaying relevant metrics

AI and Machine Learning Capabilities

• Implementation of predictive analytics to forecast customer behavior
• Automated insights generation based on data analysis

User Experience

• Intuitive user interface that allows marketers to navigate the platform easily
• Availability of training resources to help users maximize platform capabilities

Data Quality Management

• Tools for identifying duplicates, inconsistencies, and errors in datasets
• Automated processes for maintaining data accuracy over time

3. Functional Requirements

3.1 Data Collection and Integration

Tip: Focus on comprehensive data ingestion capabilities that can handle diverse data sources and formats. The solution should demonstrate proven ability to collect, normalize, and process data in real-time while maintaining data quality and governance standards.

3.2 Unified Customer Profiles

Tip: The unified customer profile capability is the cornerstone of any CDP. Ensure the solution can maintain persistent, regularly updated customer profiles that combine data from all sources while resolving identity conflicts effectively.

3.3 Data Persistence and Storage

Tip: Evaluate the solution’s data storage capabilities not just in terms of volume, but also in terms of data retention policies, access speed, and compliance with privacy regulations.

3.4 Segmentation and Audience Management

Tip: Look for flexible segmentation capabilities that can handle both simple and complex audience definitions, with the ability to update segments in real-time as customer data changes.

3.5 Data Activation and Distribution

Tip: Consider how effectively the CDP can distribute audience data to your marketing execution systems. The key is not just connectivity, but also the speed and reliability of data synchronization.

3.6 Analytics and Insights

Tip: Evaluate both out-of-the-box analytics capabilities and the flexibility to perform custom analyses. Consider how actionable the insights are and how easily they can be shared across teams.

3.7 Privacy and Compliance Management

Tip: Ensure the solution provides comprehensive privacy controls that can adapt to evolving regulations while maintaining efficient data governance. The system should demonstrate robust consent management that can handle complex privacy scenarios across different jurisdictions.

3.8 Real-time Processing

Tip: Real-time processing capabilities should be evaluated not just for speed, but also for reliability and consistency at scale. Consider both the latency of data processing and the system’s ability to trigger immediate actions based on that processed data.

4. AI-Powered Features

4.1 Generative AI Interfaces

Tip: Focus on the practical applications of AI interfaces and how they will improve user productivity and data accessibility while maintaining accuracy and security.

4.2 AI-Driven Personalization

Tip: Evaluate how the AI personalization features can scale across channels while maintaining consistency and relevance in customer experiences.

4.3 Predictive Analytics and Churn Prevention

Tip: Look for proven accuracy in predictive models and the ability to take automated actions based on predictions while maintaining transparency in the decision-making process.

4.4 Automated Segmentation

Tip: Consider both the sophistication of the automated segmentation algorithms and their ability to adapt to changing customer behaviors and business needs.

4.5 AI-Powered Content Creation

Tip: Evaluate the balance between automation and human control in content creation, ensuring the AI suggestions align with brand voice and compliance requirements.

4.6 Sentiment Analysis

Tip: Look for comprehensive sentiment analysis that can handle multiple languages and contexts while providing actionable insights for customer experience improvement.

4.7 Anomaly Detection

Tip: Focus on the system’s ability to identify meaningful anomalies while minimizing false positives and providing clear context for investigation.

4.8 Customer Lifetime Value Optimization

Tip: Evaluate both the accuracy of CLV predictions and the actionability of the optimization recommendations provided by the AI system.

5. Integration and Scalability

• List of required integrations with existing marketing and business systems
• API and integration capabilities
• Scalability to handle growing data volumes and business expansion

6. User Experience and Interface

• Ease of use for marketing and non-technical users
• Customizable dashboards and reporting interfaces
• Mobile accessibility

7. Security and Compliance

• Data encryption and security measures
• Compliance with industry standards and regulations
• Regular security audits and updates

8. Implementation and Support

• Implementation process and timeline
• Training and onboarding support
• Ongoing customer support and service level agreements

9. Pricing and Licensing

• Pricing model (subscription-based, usage-based)
• Additional costs for implementation, training, or support
• Scalability of pricing as data volume or user base grows

10. Vendor Information

• Company background and financial stability
• Client references and case studies
• Product roadmap and future development plans

11. Evaluation Criteria

• List of key criteria for evaluating CDP vendors
• Scoring or weighting system specifications

12. RFP Response Format and Submission Guidelines

• Preferred format for vendor responses
• Submission deadline
• Contact information for questions and clarifications

13. Timeline

• RFP Release Date: [Date]
• Questions Deadline: [Date]
• Proposal Due Date: [Date]
• Vendor Presentations: [Date Range]
• Vendor Selection: [Date]
• Project Kickoff: [Date]