What is a customer data platform?
A customer data platform (CDP) is software that integrates customer data from multiple sources. It create a unified view of all customer activity, interactions, and touchpoints with your products and services. Even before they make purchase decisions, digital-era customers interact with brands and companies through multiple channels—website visits, emails, third-party sites, online ads, and live chat. To build unified customer profiles, a CDP combines behavioral data (like clicks), transactional data (like purchases), and demographic data (like contact details). Your organization can use this information to understand customer preferences and create personalized marketing campaigns, content, and user experiences.
What are the benefits of a customer data platform?
Customer data platforms provide organizations with the tools they need to adapt to ever-changing consumer behavior. They can collect data from everywhere and use it anywhere for advanced analytics.
Here are some benefits of customer data platforms.
If you have multiple customer-facing applications, you might have data silos. This means individual departments have limited views of your customers.
For example, imagine that a customer browses for cushions in an online store of a brand but then goes into a physical store to purchase the cushions. The online system is unaware of what the customer purchases in person, even though the customer's purchase data is captured in the transactional system. The online store recommends the same products again and gets no interaction. Recommending a related product (like cushion covers instead of cushions) might have gotten better results.
By consolidating data into a single data management platform, businesses can maintain consistent, up-to-date, and accurate information about their customers. This information can span across all departments and touchpoints. Consistency lessens the potential for conflicting data and ensures all teams work from the same information base.
CDPs enhance automation capabilities within an organization. They remove data redundancies and errors and consolidate information from multiple data sources into a unified format. Data can flow more quickly into—and out of—other systems. This is helpful if you use marketing automation platforms, email service providers, and customer relationship management (CRM) software.
Your organization can build and connect a flexible technology stack; integrate with other marketing, sales, and service tools; and create a more streamlined operational flow. Businesses can scale their operations without sacrificing the quality of their customer insights.
Existing and emerging data privacy regulations require companies to provide consumers the right to access their personal information and to have it erased. It can be hard to meet these requirements when customer data is siloed across multiple data systems.
A unified customer database improves compliance by centralizing how you manage customer data. The data can be used, updated, or deleted as required by law. Centralized data governance enhances security across your customer data collection.
What are the use cases of a customer data platform?
Many organizations use the customer data platform as a smart data hub that democratizes customer data across the entire organization. Everyone in your organization can use first-party data owned by your organization and second-party data purchased or shared by a partner. You can also use third-party data purchased from a public provider to give context to future customer interactions.
We give some example use cases below.
Organizations can generate and own advanced analytics without reliance on third parties. They can uncover hidden patterns from historical data to predict future customer behaviors or preferences. This helps you build proactive marketing or service strategies.
For example, analytics may reveal that customers who purchase a specific product buy certain related products within a month of the original purchase. You can automatically send the second product reminders to these customers through email to meet their needs.
Enhanced marketing outcomes
Marketers often want to lessen the cost of customer acquisition and improve return on ad spend, customer lifetime value, and average order size. A CDP can help meet these goals.
With a centralized customer data management platform, you can segment your customer base more precisely on factors like demographics, purchase behavior, and engagement metrics. With this segmentation, you can design loyalty programs or retention strategies that genuinely resonate with your customers.
For example, you can optimize advertising spend by targeting ads to those most likely to convert. You can also retarget ads based on specific customer behavior or activate marketing campaigns that meet customers' needs.
Companies can offer personalized product recommendations or content by pulling data from every customer's single unified customer profile. This gives customers more tailored experiences.
For instance, ecommerce sites can use browsing history, purchase behavior, and customer preferences to suggest relevant products or promotions. Customer service teams can quickly access all relevant customer interactions and history for a faster and more personalized support experience.
How does a customer data platform work?
Customer data platforms work by collecting data from multiple sources to create a historical snapshot of every customer's journey with your organization. Customer data platform architecture typically has the following components.
The platform seamlessly collects information from various sources, such as CRM systems, ecommerce platforms, web analytics tools, and social media channels.
Data can be streamed in real time or ingested in batches depending on the platform's capabilities. Real-time data is continuously inputted and processed as it generates, while batch data may be uploaded in periodic, high-volume batches.
Once a platform ingests data, it's crucial to unify and make sense of it. To process the data, the platform cleans it of any anomalies, deduplicates redundant information, and merges related records
This step is facilitated by robust extract, transform, load (ETL) and extract, load, transform (ELT) processes. These convert the diverse data into a standardized format and build cohesive customer profiles. Different mechanisms are used so the system can identify customers without revealing confidential information to unauthorized parties.
The data is stored securely throughout the integration process. Customer data management solutions typically use advanced data warehouses or data lakes to store the information. A data warehouse may stage the data ready for marketing analysis. By comparison, a data lake may store it in raw format for downstream tools to analyze and use at a later stage.
Storage solutions are designed to be both scalable and efficient. They help ensure quick and secure data access.
Data segmentation is the process of dividing a vast pool of customer data into smaller, more manageable groups based on specific criteria.
At its simplest, data segmentation in a CDP involves categorizing customers based on predetermined criteria, like these:
- Demographic information—like age, gender, location, and occupation
- Behavioral data—like purchase history, website visits, and product interactions
- Psychographic information—like lifestyle, values, and interests
- Transactional data— like spending habits, frequency of purchases, and average order value
However, with recent technological development, you can use artificial intelligence and machine learning (AI/ML) for audience segmentation. Customer categories are predicted and adjusted based on real-time customer activity.
A CDP uses data consumption components, and you can use data collected by other components for business purposes. In other words, a CDP helps you execute on the insights you get from it. These insights could help you craft a new marketing campaign, adjust a sales strategy, or enhance customer experience on a digital platform.
Consumption technologies may be built into the CDP architecture, or you can integrate with external marketing automation systems.
How does a customer data platform compare to other marketing technologies?
A customer data platform works best in conjunction with other marketing technologies. We explain how some of these technologies interact next.
CDP vs. CRM
Customer relationship management (CRM) systems manage company interactions with current and potential customers. They primarily focus on sales, service, and relationship-building.
Traditionally, CRMs focused on manual segmentation and consumption with limited access to various data sources. Conventional CRMs are one input source for a CDP with a much broader scope. Recently, large CRM platforms have adopted a CDP approach, rapidly blurring the lines between CRM and CDP.
CDP vs. DMP
A data management platform (DMP) collects third-party data from external sources, such as cookies, online behaviors, and digital ads. It often anonymizes data to create audience segments. It stores data for a short term, typically 30–90 days, due to the transient nature of third-party cookies and the intent to capture recent behaviors.
DMPs are an advertising tools for showing ads more optimally to new customers with unknown demographic information. By comparison, CDPs are marketing tools for enhancing engagement with known customers. DMP data gives you deeper insight into your broader audience characteristics that can inform CDP segmentation.
How can AWS support your customer data platform requirements?
With Customer 360 solutions on Amazon Web Services (AWS), you can accelerate the deployment of a customer data platform.
Choose from AWS services, leading partner applications, and turnkey professional services offerings that help you create a unified view of your customers. For example, you can use:
- Amazon AppFlow to automate bidirectional customer data flows between software as a service (SaaS) applications and your CDP in just a few clicks
- AWS Data Exchange to find, access, and increase speed to value for third-party customer datasets in the cloud
- Amazon Personalize to quickly build and deploy curated recommendations and intelligent user segmentation at scale using machine learning
- Amazon Pinpoint to deliver customer communications across channels, segments, and campaigns at scale
Learn how to combine these services with other existing AWS offerings to create a customized customer data platform for your requirements.
Get started with customer data platforms on AWS by creating a free account today.
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