Why you should use customer data platform connectors
Wave goodbye to data silos, say hello to smarter marketing.
5 minute read
Why you should use customer data platform connectors
CDP connectors help eliminate data silos, streamline workflows, and improve data connectivity across your martech stack. They empower marketers to make faster, smarter decisions by providing a unified view of the customer journey.
By leveraging pre-built data connectors and integration platforms, businesses can reduce the time-consuming burden of manual data transfers, improve campaign performance, and deliver exceptional customer experiences.
When paired with a robust data lake strategy, CDPs become even more powerful—enabling organizations to scale their data infrastructure, support AI-driven personalization, and future-proof their customer data strategy.
What is a CDP?
The Customer Data Platform Institute defines a CDP as “packaged software that creates a persistent, unified customer database that is accessible to other systems."
Simply put, a CDP collects and aggregates data from multiple data sources to create a single customer view that can be accessed across your organization. These sources can include email, social media, ecommerce platforms, SaaS tools, and systems like customer relationship management (CRM) and data management platforms (DMPs).
This data integration enables companies to build rich customer profiles by capturing various types of data, linking it to unique customer identifiers, and storing it in a centralized data warehouse. These profiles support advanced decision-making, attribution modeling, and real-time personalization across all customer touchpoints.
With unified data flow and schema consistency, organizations can activate marketing data, prevent churn, and track campaign performance using business intelligence (BI) tools and analytics platforms. These tools help visualize data sets and monitor key metrics that drive performance.
What are CDP connectors?
CDP connectors are pre-built data connectors that enable seamless integration between your CDP and other systems. These connectors are designed to reduce time-consuming manual processes and simplify data transfers between platforms.
Built on standardized frameworks, CDP connectors ensure consistent, scalable, and maintainable integration. Whether you're connecting to cloud-based tools, cloud storage solutions, or on-premise systems, these connectors help unify your data ecosystem across different systems and apps.
You can add custom connectors or modify existing ones to meet evolving business needs, without starting from scratch.
How do CDP connectors work?
CDP connectors function through APIs—protocols that allow systems to communicate and share data. These APIs facilitate integration with marketing platforms, ecommerce systems, and analytics tools, enabling real-time data flow and synchronization.
Can marketers combine both pre-packaged CDP connectors with customized APIs?
The answer is yes. Marketers can utilize the Stream API to capture and transmit real-time transactional and behavioral data, like page views or clicks from third-party solutions to their CDP. This data can then be used to build segments, activate audiences, and visualize insights in tools like Excel or custom dashboards.
For example, a retail brand might use a CDP connector to pull purchase history from its ecommerce platform, merge it with email engagement data, and then push that unified profile into a marketing automation tool for personalized outreach.
Types of CDP connectors
CDP connectors typically fall into three categories:
1. Data and analytics
These connectors extract, transform, and load (ETL) data into a centralized data warehouse or data lake, enabling advanced data analysis and reporting through BI tools. A data lake is particularly useful for storing raw, unstructured, or semi-structured data at scale, which can later be refined and analyzed as needed.
Unlike traditional data warehouses, which require structured data and predefined schemas, data lakes offer flexibility and scalability. This makes them ideal for CDPs that need to ingest diverse data types from multiple sources in real time.
2. Integrations
These streamline workflows by connecting marketing automation platforms, CRM systems, and ecommerce tools to the CDP. Integration connectors ensure that data flows bi-directionally, keeping all systems updated with the latest customer information.
3. Sales and marketing automation
These connectors enable real-time audience activation, campaign orchestration, and personalized messaging across channels. They allow marketers to trigger campaigns based on behavioral signals, such as cart abandonment or product views, and deliver timely, relevant messages.
Use cases for CDP connectors
CDP connectors unlock a wide range of use cases that drive business value:
- Syncing marketing data from various platforms into a unified data model.
- Automating data aggregation from CSV files, Excel sheets, or cloud-based sources.
- Enhancing attribution models with cross-channel data.
- Feeding machine learning models with real-time data for predictive decision-making.
- Personalizing customer experiences across web, email, mobile, and offline channels.
- Improving customer segmentation by combining demographic, and transactional data.
An everyday example of CDP connectors in action is a travel company using CDP connectors to merge booking data, website behavior, and loyalty program activity into a single profile. This enables the brand to send personalized offers based on travel history, preferred destinations, and seasonal trends.
CDPs and the role of the data lake
As organizations scale, the volume and variety of customer data grow exponentially. This is where the data lake becomes a strategic asset. A data lake acts as a centralized repository that stores raw data in its native format until it’s needed. It complements the CDP by serving as a long-term storage solution for historical data, which can be tapped for deep analytics, machine learning, and AI-driven insights.
For example, while a CDP might store active customer profiles for real-time personalization, the data lake can retain years of behavioral data, clickstream logs, and third-party enrichment data. This historical depth allows data scientists to build more accurate predictive models and uncover long-term trends.
Moreover, integrating a CDP with a data lake ensures that no data is lost or siloed. It creates a seamless pipeline from data ingestion to activation, enabling organizations to maintain data governance, ensure compliance, and support advanced analytics initiatives.
CDP connectors vs. custom APIs
While all CDP connectors are API-based, not all APIs are CDP connectors. Pre-built data connectors are designed for rapid deployment and minimal configuration, while custom APIs require more development effort, testing, and maintenance.
Custom connectors offer flexibility but can be more complex and costly. In contrast, pre-built connectors reduce integration time, lower risk, and ensure compatibility with popular integration platforms and analytics platforms.
When evaluating CDP solutions, it's also important to consider pricing models from each provider, as costs can vary significantly depending on the level of customization, volume of data, and number of connected systems.
Learn more about the lightning-fast capabilities of Sitecore CDP today—and discover how it can transform your customer engagement strategy.