CDP System Design

What is CDP System:

CDP stands for Customer Data Platform, which is a system designed to collect, unify, and manage customer data from various sources to create a unified and holistic view of the customer.

A CDP system is typically used by businesses to gather customer data from a range of sources, including websites, mobile apps, social media, email campaigns, and other touchpoints. The data is then processed and unified to create a single customer profile that includes demographic information, behavioral data, and other relevant data points.

CDP systems are designed to enable businesses to gain deeper insights into their customers’ behavior, preferences, and needs, and to use this information to create personalized experiences and optimize customer interactions. By analyzing customer data, businesses can identify trends and patterns, segment their customer base, and create targeted marketing campaigns.

A CDP system typically includes data collection tools, data storage and management capabilities, and analytics and reporting functionality. Some CDP systems also offer integrations with other marketing and customer engagement tools, enabling businesses to activate their customer data across their entire tech stack.

Overall, a CDP system is a critical tool for businesses looking to improve their customer experience and make data-driven decisions. By providing a centralized platform for collecting, unifying, and managing customer data, CDP systems enable businesses to create personalized experiences, optimize their operations, and drive growth.

Why CDP System:

A Customer Data Platform (CDP) is a tool that allows businesses to collect, organize, and analyze customer data from various sources such as social media, mobile apps, websites, CRM systems, and more. Here are a few reasons why businesses need a CDP system:

• A better understanding of customers: With a CDP system, businesses can gain a unified and comprehensive view of their customers by consolidating customer data from various sources. This allows them to understand customer behavior, preferences, and interests, which can help them tailor their products and services accordingly.
• Personalized Marketing: CDPs enable businesses to create personalized marketing campaigns based on customer data insights, which helps to increase customer engagement and retention. Personalization can also improve customer satisfaction and loyalty, as customers feel valued and understood by the brand.
• Data Security: A CDP system helps ensure data security and privacy by centralizing customer data management, and reducing the risk of data breaches and unauthorized access. It also enables businesses to comply with data protection regulations and maintain customer trust.
• Operational Efficiency: A CDP system streamlines data management processes, reducing manual effort and errors associated with data collection and analysis. This improves operational efficiency and enables businesses to make data-driven decisions faster.

Overall, a CDP system can help businesses to create a better customer experience, increase customer loyalty, and improve their bottom line.

High-Level Architecture Diagram:

Architecture Description:

Event Consumer Service:

• The service method you described involves two main steps: checking the details of the input event and retrieving the configuration of an event identifier.
• In the first step, the method would receive input events from an event or HTTP handler. The input event could include various types of information, such as customer details, product specifications, or order information. The method would then check the data to ensure that it is complete, accurate, and valid. This may involve verifying that all required fields are present as configured in the database, checking that the data is in the correct format, and validating any user input against predefined rules or constraints.
• Once the input data has been validated, the second step of the method would involve retrieving the configuration of a specific ID. This could involve querying a database, a web service, or another system to retrieve information related to the ID. The configuration information could include details such as the type of product or service associated with the ID, pricing information, shipping details, or any other relevant information.
• The service method could then return the retrieved configuration data to the caller, allowing them to use the information for further processing or to make decisions based on the data.

Event Configuration Service:

• The service method you described involves retrieving configuration data from a database if the data is not present in the Redis cache. Here’s how the method might work:
• The method would first check the Redis cache to see if the configuration data is already present. If the data is found in the cache, the method can simply return the cached data to the caller, bypassing the need to query the database.
• If the configuration data is not found in the Redis cache, the method would need to retrieve the data from the database. This could involve querying a specific table or collection in the database to retrieve the configuration information related to the requested key.
• Finally, the method would return the retrieved configuration data to the caller, allowing them to use the information for further processing or to make decisions based on the data.

Event Processing Service:

The service method you described involves calling different methods to process data. Here’s how the method might work:

• The method would receive input data from the parent method. The input data could be in various formats such as JSON.
• Once the input data has been received, the service method would determine the appropriate processing methods to apply to the data. This could involve checking the data format, the data type, or other attributes of the data to determine the appropriate methods to use.
• Each processing method would perform a specific task on the data and return the modified data to the service method. For example, one method may validate the data and return a list of validation errors, while another method may transform the data into a different format or structure.
• Once all the processing methods have been called and the data has been modified accordingly, the service method calls the distributor service to transmit the data to a third-party service.

Data Processing Service:

Data processing service process the event data and generate generic data which has all required attribute values.

Within the Processing service, we have a “data collection service” which is used to collect data using APIs from the GQL client server. The GQL configuration details are part of the event configuration and that is triggered only when there are events with an attribute source as GQL.

Once the data is collected from GQL and also data as part of the event object the processing service will return the processed data for further use.

Client Service: [ Engagement | Analytics | Other]

Client service clients are the methods with integration implementation details, which involve API invocation implementation with authentication.

Service clients are triggered asynchronously to keep the time for data transmission as minimum as possible.