Enterprise Must-See! Top 5 Best CDP Recommendations and Selection Guide for 2025

Enterprise Must-See! Top 5 Best CDP Recommendations and Selection Guide for 2025

Adobe Experience Platform & Realtime CDP, CDP

21 May 2025

 

Table of Contents

  1. Introduction: Why 2025 Is the Best Time to Adopt a CDP
  2. What is a CDP? How Does It Differ from CRM and DMP?
  3. 5 Key Factors to Consider Before Choosing a CDP
  4. Top 5 Best CDP Platforms in 2025
  5. Third-Party Insights: Who Are the Leaders in the CDP Market?
  6. Typical Use Cases for CDPs Across Industries
  7. Success Stories: How CDPs Create Business Value
  8. Expert Advice: CDP Selection Process and Strategy for Enterprises
  9. Conclusion: Leverage CDP for Customer-Centric Digital Marketing
  10. References

 

1. Introduction: Why 2025 Is the Best Time to Adopt a CDP

In today’s fast-growing digital economy, one of the biggest challenges enterprises face is accurately identifying, understanding, and responding to customer needs in real time amidst massive volumes of data. As consumer behavior becomes increasingly fragmented, brands must integrate customer data across multiple channels — including websites, apps, social media, and physical stores — to build a complete customer view (Customer 360) and enable truly personalized marketing.

While traditional CRM and DMP systems offer value in specific areas, they can no longer meet modern demands for cross-channel, cross-device real-time integration. This is precisely why the Customer Data Platform (CDP) has become a core component of modern marketing technology (MarTech) stacks.

A CDP not only helps businesses unify first-party data but also enables real-time analysis and actionable personalization — such as email pushes, content recommendations, and retargeting ads — effectively boosting conversion rates and customer lifetime value (CLV). Especially in an era of increasingly strict privacy regulations and the gradual phase-out of third-party cookies, the CDP has become a foundational infrastructure for brands to maintain data sovereignty and enhance their data utilization capabilities.

Now is the golden opportunity for enterprises to adopt a CDP and build a customer-centric data strategy.

 

2. What is a CDP? How Does It Differ from CRM and DMP?

A CDP (Customer Data Platform) is a marketer-focused data management system that integrates customer data from multiple sources, builds unified customer profiles, and applies them in real time for personalized marketing and automated campaigns — making it a key system for data-driven marketing strategies.

2.1 Core Features of a CDP:

  • Integrates first-party data from websites, apps, POS systems, emails, and customer service
  • Consolidates customer identities across devices and channels
  • Updates customer profiles in real time and connects automatically with marketing or advertising platforms
  • Provides a visual interface for marketers to quickly define segments and launch campaigns

2.2 Differences Between CDP, CRM, and DMP:

Category CDP (Customer Data Platform) CRM (Customer Relationship Management) DMP (Data Management Platform)
1. Data Source Mainly first-party, supports second- and third-party First-party (sales and service interactions) Third-party data (anonymous visitors, cookies)
2. Identity Recognition High – unifies identity across devices and platforms Moderate – limited to known customers Low – cannot identify individuals
3. Target Users Marketers, analysts, product managers Sales and customer service teams Ad agencies, media buying teams
4. Real-Time Capabilities & Usage High – real-time activation and campaign sync Moderate – mainly for relationship tracking and analysis Low – batch processing focused
5. Use Cases Segmentation, personalization, automation Customer management, sales tracking Audience building, cookie retargeting

2.3 Why Enterprises Need a CDP Now More Than Ever:

  • First-party data is becoming the most valuable asset for enterprises
  • Regulations like GDPR and CCPA demand stricter personal data management
  • The phase-out of third-party cookies forces companies to shift toward first-party strategies
  • Customers expect instant, personalized brand interactions, which require comprehensive data support
  • Marketing and IT teams need a shared platform to reduce data silos

 

3. 5 Key Factors to Consider Before Choosing a CDP

With numerous CDP solutions available on the market, each offering different features and positioning, enterprises should carefully evaluate the following five factors based on their business needs, technical architecture, and future plans before selecting a CDP:

1. Data Integration Capabilities

1. Data Integration Capabilities

  • Whether it supports data input from multiple sources, including websites, apps, CRM, POS, and customer service systems
  • Whether it can integrate structured data (e.g., transaction records) and unstructured data (e.g., click behavior)
  • Whether it has the capability to process streaming data in real time

2. Identity Resolution & Unified Customer View (Customer 360)

2. Identity Resolution & Unified Customer View (Customer 360)

  • Whether it can associate user behavior across different devices and channels to a single customer profile
  • Whether it supports identity recognition logic and merging rules (e.g., Email, phone number, member ID)
  • Whether it can establish a consistent customer view across platforms

3. Real-Time Capabilities and Personalization Application

3. Real-Time Capabilities and Personalization Application

  • Whether data updates are real-time and can drive real-time marketing actions
  • Whether it supports real-time segmentation, dynamic push notifications, and content personalization
  • Whether it can integrate with marketing automation platforms, ad投放 tools, or internal systems

4. Compliance and Data Security

4. Compliance and Data Security

  • Whether it complies with major global data privacy regulations such as GDPR and CCPA
  • Whether it includes features such as access control, data encryption, and audit logs
  • Whether it supports data subject rights management, such as user data access and deletion requests

5. Scalability and Technical Support Capabilities

5. Scalability and Technical Support Capabilities

  • Whether it offers flexible APIs or SDKs for integration with existing systems
  • Whether it can be used with the CDP vendor's ecosystem tools (e.g., Adobe, Salesforce)
  • Whether it provides local or global technical support, training, and consulting services

 

4. Overview of Top 5 Recommended CDP Platforms for 2025

Among the numerous CDP products, we have selected the top 5 platforms for 2025 that are most worthy of enterprise attention and adoption, covering different business scales and application needs. Below are brief introductions to each platform and suggested use cases:

4.1 Adobe Real-Time CDP

Adobe Real-Time CDP

Product Positioning:
Adobe Real-Time CDP is one of the core modules of Adobe Experience Platform, designed for enterprises to provide a comprehensive CDP solution that can integrate multi-source data in real time and drive cross-channel personalized marketing. It leverages Adobe's deep expertise in content management, analytics, and marketing automation to help brands achieve true "data as a service".

Main Features:

  • Real-Time Profile Architecture: Integrates data from websites, apps, CRM, customer service, and third-party advertising platforms into a single, real-time updated customer profile
  • Powerful Identity Resolution: Supports both deterministic and probabilistic identity merging, effectively handling anonymous and known data across devices and channels
  • Native Integration with Adobe Experience Cloud Ecosystem: Includes tools such as Adobe Analytics, Target, Campaign, and Journey Optimizer to enable end-to-end data application
  • Supports B2B and B2C Dual-Model Architecture: Through a dual-layer design of Account Profile and Individual Profile, enables personalized and segmented marketing for B2B businesses
  • Compliance and Governance: Built-in data classification, tagging, access control, and support for privacy regulations (e.g., GDPR, CCPA), suitable for highly sensitive industries such as finance and healthcare
  • Built-In AI and Adobe Sensei: Supports audience prediction, automatic segmentation, and behavior modeling to accelerate custom application deployment

Target Users:
Adobe Real-Time CDP is suitable for mid-to-large enterprises, brands, and multinational organizations, especially those already using Adobe Marketing Cloud or Adobe Experience Manager. This platform is ideal for enterprises looking to improve first-party data integration efficiency, enhance real-time personalization, and implement consistent cross-channel marketing within their existing MarTech infrastructure.

4.2 Salesforce Data Cloud (formerly Customer 360 Audiences)

Salesforce Data Cloud

Product Positioning:
Salesforce Data Cloud is an enterprise-grade CDP designed specifically for the Salesforce ecosystem, dedicated to integrating customer data from various Salesforce cloud platforms (Sales Cloud, Service Cloud, Marketing Cloud, etc.) into a unified view to build an actionable Customer 360 in real time.

Main Features:

  • Full Integration within the Salesforce Ecosystem: Automatically integrates sales records, customer service conversations, and marketing interactions without additional development
  • Built-In Einstein AI Models: Enables predictive analysis directly, such as purchase intent, churn risk, and product recommendations
  • Marketing Automation Integration: Seamlessly connects with modules like Journey Builder and Email Studio to enable customized marketing campaigns
  • Real-Time Data Sync and Identity Recognition: Quickly builds actionable customer profiles and supports real-time updates across touchpoints
  • Open Architecture: Supports third-party integrations (e.g., Salesforce, Snowflake, Meta, Google) and custom connections
  • Cross-Organization Data Governance and Standardization: Allows the creation of a Blueprint model for multinational companies and enterprise groups to share common data models
  • High Flexibility in Practical Applications: Suitable for various use cases including website content personalization, marketing automation push, e-commerce conversion improvement, and churn prediction

Target Users:
Especially suitable for enterprises that are already widely using Salesforce CRM, productivity tools, and marketing cloud platforms. If your goal is to further integrate cross-departmental data and activate real-time personalization, Salesforce Data Cloud is a natural extension. Its advantage lies in reducing integration costs and complexity, allowing businesses to realize CDP value quickly.

4.3 Segment by Twilio

Segment by Twilio

Product Positioning:
Segment is a modular CDP platform acquired by Twilio, designed with a developer-friendly and highly flexible architecture. It enables enterprises to quickly integrate and deploy solutions, making it especially suitable for tech-driven companies that require custom workflows and integration logic.

Main Features:

  • Plug-and-Play Integration: Supports over 100 common data sources (e.g., Google Analytics, Shopify, Stripe) and destinations (e.g., Snowflake, BigQuery, Braze)
  • Event Tracking and Identity Resolution: Allows custom event naming and attribute standards, supporting the merging of anonymous identities into known customers
  • Rich API and Lightweight Architecture: Enables fast integration with internal systems and supports multi-environment deployment (cloud, on-premise, hybrid)

Target Users:
Recommended for growth-stage SaaS companies, startups, and product-driven tech teams that typically have in-house development capabilities and seek greater data ownership and flexibility. Segment’s advantage lies in quick time-to-market and high composability.

4.4 Tealium AudienceStream

Tealium AudienceStream

Product Positioning:
Tealium AudienceStream is a real-time customer data platform specialized in handling real-time interaction data at the website and device level. Built around an "event-driven" approach and "behavioral tag management," it helps enterprises enable real-time personalization and experience optimization.

Main Features:

  • Seamless Integration with Tealium iQ: Builds a complete data collection and tag management workflow, reducing deployment time
  • Real-Time Segmentation and Triggering: Enables real-time trigger logic based on visitor behavior, device status, or location — such as ad exclusion, pop-up display, and email triggers
  • Cross-Device Identification and Merging: Accurately links website visitors, app users, and customer member data to strengthen the unified customer view

Target Users:
Especially recommended for retail, travel, and e-commerce platforms that heavily rely on real-time interactions via websites and apps, to effectively improve real-time marketing efficiency and data operation flexibility. Its technical strength lies in front-end data collection and automated triggering.

4.5 Treasure Data CDP

Treasure Data CDP

Product Positioning:
Treasure Data is a CDP known for its strong data integration and analytics capabilities, widely used in manufacturing, retail, and consumer goods industries. It emphasizes the ability to handle large volumes of heterogeneous data and build custom BI models.

Main Features:

  • Supports Big Data and Complex ETL Processes: Provides powerful data transformation logic to handle non-standardized data from sources such as CRM, IoT, POS, ERP
  • Custom Reporting and Analysis Logic: Supports SQL queries, table joins, and built-in model design, can connect with visualization tools like Power BI, Tableau
  • High Flexibility Integration: Supports hybrid cloud, private cloud, and API integration, ensuring smooth connection with existing systems

Target Users:
Highly suitable for manufacturing, retail groups, and large data operation units, especially those with internal data science teams looking to enhance internal data integration and analysis autonomy. Treasure Data is a CDP option that leans towards data engineering and internal BI analysis.

Platform Comparison Overview:

Platform Name Feature Overview Suitable Enterprise Size Ecosystem Integration Real-Time Capability Development Flexibility
Adobe Real-Time CDP Comprehensive real-time integration + native marketing linkage Mid-to-large enterprises ★★★★★ ★★★★★ ★★☆☆☆
Salesforce Data Cloud CRM data extension + AI analysis Salesforce users primarily ★★★★★ ★★★★☆ ★★☆☆☆
Segment by Twilio High API flexibility + quick deployment Growth-stage tech companies ★★★★☆ ★★★★☆ ★★★★★
Tealium AudienceStream Behavior tag-oriented + fast segmentation Retail and e-commerce businesses ★★★☆☆ ★★★★☆ ★★★☆☆
Treasure Data CDP Big data processing + strong internal integration Manufacturing, retail, large enterprises ★★★★☆ ★★★☆☆ ★★★★☆

 

5. Third-Party Evaluation Perspectives: Who Are the Leaders in the CDP Market?

When evaluating CDP platforms, referencing reports from reputable third-party research institutions (such as Forrester and Gartner) can help enterprises better understand each platform’s performance and positioning. Here are key insights from two recent reports:

5.1 Forrester Wave™: Customer Data Platforms for B2C, Q3 2024

5.1 Forrester Wave™:Customer Data Platforms for B2C, Q3 2024

Forrester evaluates based on “Current Offering” and “Strategy”. According to this chart:

  • Leaders Quadrant:
    • Adobe, Salesforce, ActionIQ received high scores in both categories, showing strengths in functionality maturity and strategic planning.
    • Treasure Data is close to the Leader quadrant, demonstrating solid product capabilities.
  • Strong Performers:
    • Includes Tealium, mParticle, Zeta Global, suitable for specific scenarios and mid-sized enterprises.
  • Challengers and Contenders:
    • Twilio (Segment), Amperity, Microsoft need improvements in product strategy or are still establishing their overall market positioning.

Recommendation:
For enterprises needing to drive personalization and omnichannel integration in B2C scenarios, Forrester recommends Adobe and Salesforce as mature choices.

5.2 Gartner Magic Quadrant for Customer Data Platforms, Feb 2025

5.2 Gartner Magic Quadrant for Customer Data Platforms, Feb 2025

Gartner focuses on “Ability to Execute” and “Completeness of Vision”:

  • Leaders Quadrant:
    • Salesforce is the only platform in the Leaders quadrant, excelling especially in CRM and real-time data integration.
  • Visionaries:
    • Adobe and Tealium are highly rated for innovation and future scalability, considered innovative leaders.
  • Challengers and Niche Players:
    • Treasure Data and Oracle are rated as Challengers, offering practical features but needing stronger execution; Twilio (Segment), mParticle, BlueConic are niche players, suitable for specific applications and SMB markets.

Recommendation:
For enterprises valuing long-term vision, cross-platform flexibility, and future scalability, Gartner suggests focusing on Adobe and Tealium; if already using Salesforce, Data Cloud is the natural choice.

5.3 Comprehensive Observations and Selection Recommendations:

Platform Name Forrester Rating Gartner Rating Suitable Targets and Characteristics
Adobe Leader Visionary Strong multi-channel integration, AI support, suitable for content-driven enterprises
Salesforce Leader Leader Excellent CRM integration, real-time data flow, ideal for existing customers
Treasure Data Strong Performer Challenger Robust big data processing and internal BI integration capabilities
Tealium Strong Performer Visionary Strengths in behavior tracking and real-time push notifications
Segment Contender Niche Player Quick deployment, developer-friendly, suitable for growth-stage teams

 

6. Typical Application Scenarios (Use Cases) for Different Industries Implementing CDP

While Customer Data Platforms (CDPs) have similar architectures, their application priorities and integration methods vary significantly across different industries. Below are common CDP use cases and expected benefits for five major sectors, aiding enterprises in considering implementation strategies and investment directions.

 

1. Retail and E-Commerce | Enhancing Personalized Recommendations and Customer Retention

Use Cases:

  • Integrate online shopping behavior, in-store transactions, membership data, and app interaction data
  • Create a Unified Customer Profile for behavioral segmentation and recommendation modeling
  • Enable personalized ad targeting, cart abandonment reminders, and dynamic pricing strategies

Benefits:
  • Increase conversion rates and average order value
  • Improve repeat purchase rates and customer lifetime value (CLV)
  • Reduce experience gaps caused by data fragmentation

2. Banking | Strengthening Customer Insights and Digital Transformation

Use Cases:

  • Integrate multi-source data from digital banking (online banking, mobile app), branch transactions, credit card spending, customer service interactions, and product inquiry records
  • Create a comprehensive 360° customer profile covering financial product portfolios, interaction behaviors, risk preferences, and lifecycle stages
  • Predictively recommend suitable products (e.g., loans, credit cards, wealth management, investments) based on customer attributes and behavior
  • Trigger real-time marketing actions using interaction data (e.g., push a personalized interest rate offer via the app after a user browses fixed deposit options online)

Benefits:
  • Enhance cross-selling opportunities and improve recommendation accuracy
  • Shorten the decision-making journey from product awareness to conversion, boosting digital application success rates
  • Segment and manage high-value and potential customers to optimize allocation of advisory and marketing resources
  • Increase customer retention and satisfaction while reducing churn

3. B2B and Manufacturing | Integrating Customer Journey and Lead Nurturing

Use Cases:

  • Integrate website behavior, product catalog downloads, event attendee lists, and CRM data
  • Analyze interest topics and engagement depth of potential enterprise customers
  • Automatically deliver technical whitepapers, customized product recommendations, and sales follow-up reminders

Benefits:
  • Shorten the sales cycle and improve lead conversion rates
  • Help sales teams identify high-potential, "high-intent" prospects
  • Establish a clear Account-Based Marketing (ABM) path with data-driven support

4. Insurance Industry | Enhancing Service Experience and Policy Renewal Rates

Use Cases:

  • Integrate insurance application data, claims history, app usage behavior, and customer service interaction records
  • Build individual risk assessment models and segment customers based on coverage needs
  • Push notifications for coverage gap alerts, product updates, and claims status tracking

Benefits:
  • Strengthen policyholder relationships and brand loyalty
  • Increase app engagement and policy renewal rates
  • Support data-driven sales and customer service strategies

5. Education and Public Institutions | Integrating Identity Management and Interaction Data Analysis

Use Cases:

  • Integrate student information systems (SIS), online learning platforms, event participation records, and survey data
  • Build student learning journey and engagement preference models
  • Push personalized course recommendations, event invitations, and administrative notifications

Benefits:
  • Increase student engagement and academic outcomes
  • Accurately analyze the effectiveness and response rates of campus promotion activities
  • Enable centralized data governance and visual reporting across multiple units and departments

 

7. Success Stories: How CDPs Create Value for Businesses

Enterprises that have implemented CDPs often see significant improvements in data integration, customer management, and marketing effectiveness. Below are several representative case studies spanning various industries, showcasing how CDPs play a crucial role in practice.

Case Study 1: Global Retail Brand Integrates Online and Offline Membership Data

Background:
The company operates e-commerce websites and physical stores worldwide. Over time, member data had been scattered across regional systems, making it difficult to perform unified analysis and marketing.

CDP Implementation Results:

  • Created a unified customer profile by integrating online behavior, app activity, and POS transaction records
  • Achieved personalized recommendations and localized promotions, increasing member repurchase rates by over 20%
  • Enabled marketing teams to quickly set up automated campaigns, such as cart abandonment reminders and birthday offers

Case Study 2: Bank Optimizes Digital Channels and Promotion Effectiveness

Background:
The financial institution aimed to improve the conversion rate for digital wealth product applications, but marketing activities and data analysis had long operated in silos.

CDP Implementation Results:

  • Integrated data from online banking, mobile app, email, and customer service center
  • Accurately identified high-potential customers and delivered relevant product information in real time
  • Both click-through rates and application completion rates for marketing campaigns increased by over 30%

Case Study 3: B2B Manufacturing Company Implements CDP for Lead Nurturing

Background:
The company aimed to integrate event attendee lists, website downloads, sales interactions, and CRM data to improve lead quality and conversion efficiency.

CDP Implementation Results:

  • Created visitor profiles for target accounts, tagging their interested product lines and engagement depth
  • Automatically delivered technical whitepapers and use cases for educational marketing (nurturing)
  • Successfully shortened the sales cycle from lead to opportunity and improved sales follow-up efficiency

Case Study 4: Insurance Company Enhances Customer Engagement and Renewal Rates

Background:
An insurance company aimed to improve policyholder engagement and product renewal conversion rates, while also addressing the issue of data fragmentation.

CDP Implementation Results:

  • Integrated insurance application data, claims records, customer service interactions, and mobile app engagement
  • Built customer risk profiles and lifecycle models to automatically send relevant coverage recommendations and product updates
  • Successfully increased app activity and annual policy renewal rates, while reducing churn risk

Case Study 5: University Unifies On-Campus and Off-Campus Interaction Records to Enhance Student Engagement

Background:
The university aimed to increase student engagement with extracurricular activities, career counseling services, and academic resources.

CDP Implementation Results:

  • Integrated data from learning platforms, event registration systems, website visits, and email interactions
  • Delivered highly relevant event and resource recommendations based on students’ majors and interests
  • Both event sign-up rates and average website dwell time increased significantly, along with improved student satisfaction

 

8. Expert Advice: CDP Selection Process and Implementation Strategy for Enterprises

Implementing a CDP is not only a technology decision, but also a digital transformation initiative that spans departments and platforms. To reduce implementation risks and accelerate time-to-value, many enterprises choose to collaborate with experienced technology consultants or implementation partners. Below is a recommended selection and deployment process, along with suggested forms of external support for each stage:

Step 1: Define Business Objectives and Core Requirements

  • Clearly define the primary objectives for implementing a CDP (e.g., integrating customer data, enabling personalization, enhancing automation)
  • Evaluate needs and pain points across departments (marketing, IT, customer service, legal, etc.)
  • Engage external consultants to assist with requirement gathering, use case analysis, and documentation

Step 2: Establish a Cross-Functional Team

  • Form a decision-making team including representatives from marketing, IT, data analytics, and legal departments
  • Define data sources, access permissions, and the scope of integration
  • External consultants can act as neutral facilitators to help build cross-functional consensus and provide industry best practices

Step 3: Evaluate and Shortlist Platform Vendors

  • Refer to market research (e.g., Gartner, Forrester) to shortlist 2–3 CDP platform candidates
  • Compare vendors based on key criteria such as real-time capabilities, integration flexibility, UI/UX, and data governance
  • Engage consultants to help develop evaluation matrices and RFP documents to accelerate the selection process

Step 4: Conduct a Proof of Concept (POC)

  • Select 1–2 high-value use cases (e.g., cart abandonment tracking, customer behavior segmentation) for POC testing
  • External implementation teams can provide test environments, sample data, and integration support to accelerate the validation cycle
  • Both marketing and IT should participate in the acceptance process to verify system functionality and operational feasibility

Step 5: Develop an Implementation Plan and Budget Assessment

  • Develop a phased implementation plan (e.g., data integration, real-time segmentation, automated messaging)
  • External vendors can provide guidance on implementation timelines, technical architecture design, and risk assessment
  • Evaluate total cost of ownership, including licensing fees, technical implementation costs, training, and ongoing maintenance

Step 6: Launch Implementation and Establish Continuous Optimization Mechanisms

  • Continuously track key performance metrics (e.g., engagement rate, conversion rate, data quality) after full implementation
  • Set up data governance processes, access control policies, and compliance audit mechanisms
  • External consultants can help establish performance review frameworks and regularly provide optimization recommendations and new use case suggestions

 

9. Conclusion: Leveraging CDP to Achieve Customer-Centric Digital Marketing

In an era where first-party data has become a brand’s core asset, CDP is no longer an optional tool — it is the foundational infrastructure for enterprises to move toward data-driven and personalized marketing. By integrating fragmented customer data and ensuring consistent cross-channel engagement, businesses can not only improve conversion rates and customer lifetime value (CLV), but also strengthen their digital competitiveness and market agility.

However, successfully implementing a CDP is not something that can be achieved overnight. It is a medium- to long-term project that involves technology selection, internal process reengineering, data governance, and cross-functional collaboration. For most companies lacking in-house MarTech or data science expertise, we recommend:

  • Seeking assistance from consulting firms or technical implementation partners with CDP implementation experience right from the planning phase
  • Leveraging vendors’ POC (Proof of Concept), requirement gathering, and system integration capabilities to accelerate time-to-value
  • Adopting industry best practices through external consultants to avoid common pitfalls and rework

If companies can clearly define their objectives early on, steadily advance the implementation process, and combine efforts from professional consultants and internal teams, they will be able to unlock the full potential of CDP and truly realize a “customer-centric” digital marketing strategy.

If you are interested in CDP or would like our team to help you evaluate or implement one, please feel free to contact us at Leads Technologies Limited.

 

10. References

If you wish to further understand CDP platform functionalities, architecture, and industry trends, the following are recommended official resources and expert materials to support your evaluation and implementation decisions:

  1. Official Platforms and Product Pages
  1. Market Research & Industry Reports
  1. Further Reading and Practical Resources

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