CDP
Category: Marketing
What is Customer Data Platform (CDP)?
Customer Data Platform (CDP) is a software platform that collects and manages customer data from multiple sources, creating a complete picture of each customer. CDP allows businesses to create personalized marketing experiences, analyze customer behavior and make more informed business decisions.
Unlike traditional data management systems, CDP is designed specifically for marketing teams and can be used by non-technical users to create customer segments and activate data in real time.
Key components of CDP
Data collection
Integration with multiple customer data sources:
- Website and mobile apps
- CRM systems
- E-commerce platforms
- Social networks
- Offline channels
- Email marketing
Data unification
Creating a unified customer profile:
- Identity resolution
- Connecting anonymous and known users
- Removing duplicate records
- Enriching data
- Creating a 360° profile
Segmentation
Creating dynamic customer segments:
- Demographic segments
- Behavioral segments
- Segments by purchase history
- Prognostic segments
- Real-time segmentation
Activation
Exporting data to marketing systems:
- Email platforms
- Advertising networks
- CRM systems
- Personalization systems
- Call centers
Analysis and reports
Visualization and analysis of customer data:
- Customer journey mapping
- Attribute analysis
- Behavioral trends
- Personalized tables
- Prognostic modeling
Security and compliance
Management of access and compliance with regulations:
- GDPR compliance
- CCPA compliance
- Management of consent
- Data encryption
- Access control
Architecture of CDP system - How does a CDP platform work
- Data sources Website, mobile apps, CRM, POS
- Data collection API, SDK, imports
- Unification Identity resolution, profiling
- Segmentation Creating audiences
- Activation Export to marketing systems
Data Flow in CDP system
Data from different sources is collected, unified into a unified customer profile and activated to marketing channels for personalized experiences.
Types of data that CDP collects
Demographic data
Basic information about customers:
- Name and contact
- Age and gender
- Location
- Language
Behavioral data
Actions and interactions:
- Website visits
- Clicks and navigation
- Purchases and cart
- Social interactions
Transactional data
Purchases and financial data:
- Purchase history
- Purchase value
- Purchase frequency
- Purchased products
Psychographic data
Interests and preferences:
- Interests and hobbies
- Lifestyle
- Values and beliefs
- Marketing preferences
Advantages of using CDP
- Single customer view: 360° profile of each customer from all channels
- Personalized marketing experiences: Messages and offers tailored to individual needs
- Improved ROI of marketing: More effective targeting and higher conversions
- Reduced costs: Eliminating duplicate systems and processes
- Real-time interactions: Immediate reactions to customer actions
- Improved customer retention: Better understanding and service of customers
- Compliance with regulations: Centralized management of consent and privacy
- Data-driven solutions: Making decisions based on real data
Example of a customer profile in CDP
Unified customer profile in CDP system
- Maria Ivanova - VIP Customer LTV: €2,450 | Segment: Loyal
- Demography 32 years, Sofia
- Last purchase 5 days ago
- Total orders 18 orders
- Average value €136
- Last interactions 📧 Open email for new collection (yesterday) | 🌐 Visit page with shoes (today) | 📱 Add product to cart (2 hours ago)
- Preferences 🛍️ Shoes and accessories | 💄 High-end cosmetics | 🎁 React to personalized offers
Use Cases and applications
- Personalized email marketing: Sending relevant messages based on behavior and preferences
- Dynamic pricing: Offering personalized prices and discounts
- Remarketing campaigns: Targeting ads to users who showed interest
- Improving customer journey: Identifying drop-off points and optimizing
- Cross-selling: Offering additional products based on purchase history
- Retention prevention: Identifying customers at risk and activating retention strategies
- Channel optimization: Understanding which channels are most effective for different segments
- Prognostic models: Predicting future behavior and purchases
Comparison: CDP vs other systems
| System | Main goal | Advantages | Restrictions |
|---|---|---|---|
| CDP | Unification and activation of customer data | Real-time, marketing-focused, easy to use | Limited analytical depth |
| CRM | Management of customer relationships | Good sales-focused, structured data | Limited behavioral data, not real-time |
| DMP | Management of anonymous audiences for advertising | Good for advertising campaigns, large scale | Limited data lifespan, anonymous users |
| Data Warehouse | Storage and analysis of business data | Powerful analytics, historical data | Complex for marketing teams, not real-time |
Implementation stages of CDP
- 1
Defining goals and requirements
What business problems do we want to solve? What use cases are priority? What data is needed?
- 2
Choosing a CDP platform
Evaluation of different providers according to functionality, integrations, price and scalability.
- 3
Integration of data sources
Connecting website, mobile apps, CRM, e-commerce and other systems.
- 4
Creating segments and audiences
Defining customer segments according to business goals.
- 6
Activation of data
Connecting with marketing systems and testing the first campaigns.
Popular CDP platforms
| Platform | Focus | Price model | Suitable for |
|---|---|---|---|
| Segment | Data infrastructure and activation | Based on events | Technical teams, enterprises |
| mParticle | Mobile data and privacy | Based on MAU | Mobile apps, GDPR-sensitive |
| Tealium | Tag management and data | Based on traffic | Enterprise, complex integrations |
| Bloomreach | E-commerce and personalization | Based on data volume | Online retailers |
| Lytics | Marketing activation | Based on profiles | Marketing teams, medium businesses |
Future trends in CDP
- AI and machine learning: Automatic segmentation and prognostic modeling
- Increased focus on privacy: Privacy-first design and management of consent
- Integration with real-time systems: Real-time interactions in all channels
- CDP as a service (CDPaaS): Cloud-based solutions with lower barrier to entry
- Data enrichment: Adding external data for more complete profiles
- Integration with operational systems: Connecting not only with marketing, but also with operational systems
- Combined platforms: CDP + marketing automation in one platform
Key success indicators (KPIs)
| KPI | Description | Target value |
|---|---|---|
| Customer Lifetime Value (LTV) | Total value of the customer during their lifetime | Increase by 15-25% High |
| Conversion rate | Percentage of visitors who perform the desired action | Increase by 10-20% High |
| Marketing ROI | Return on marketing investment | Increase by 20-30% High |
| Customer Retention Rate | Percentage of customers who continue to buy | Increase by 10-15% Average |
| Activation time | Time from event to marketing reaction | Under 5 minutes Average |