With the death of third-party cookies slated for 2024, customer data platforms (CDPs) have seen a rise in popularity. Exhibiting a market value of $1.16 billion in 2021, customer data platforms are expected to grow to $6.94 billion by 2029, at a CAGR of 25.4%.
Although third-party data has its place, companies use the more valuable first-party data that CDPs collect to help them foster better relationships with customers by providing a more personalized interaction with their business.
In this article, we'll explain what a customer data platform is, how it works, the benefits it provides and more.
Key Benefits of CDPs
Customer data platforms (CDPS) offer the following benefits:
- Improved customer experience: CDP data sources allow companies to use individual customer interactions to better understand their customers and target specific customers. Marketing teams can use this information to create more personalized marketing campaigns, which can also improve customer loyalty by up to 25%.
- More organized customer data management: CDPs organize and visualize customer profiles into a single customer view (SCV), allowing companies to manage customer data from a single database more easily and with less technical skill than might be required with normal data warehouses. This can help companies save time and additional costs, as well as better manage how they share data with internal or external systems.
- More insightful customer analytics: CDPs collect first-party data in real time which allows for more accurate and up-to-date customer insights. Any additional information that a customer might provide is automatically updated on their customer profile.
- Improved data protection and privacy: A CDP allows a company to be GDPR (General Data Protection Regulation) and CCPA (California Consumer Privacy Act) compliant, because it provides the company with a history of how and where customer data was collected and used, as well as making this information available to customers upon request. Customer preferences can also be maintained across a company's marketing platforms so that no errors are made during campaign management, such as if a customer asks to have their contact information deleted, only to receive future newsletters.
- Better data-driven marketing decisions: The SCV that a CDP provides can help companies improve their business intelligence and marketing efforts, because different departments can work together from a single database and see how customers are being interacted with. This can help improve customer engagement rates and provide a more-personalized customer experience.
CDP vs DMP vs CRM: Understanding the Difference
Customer data platforms (CDPs), data management platforms (DMPs) and customer relationship management (CRM) software can help implement the latest contextual advertising and programmatic advertising trends, although there are some differences that companies need to be aware of.
Differences Between CDPs and DMPs
Compared to a CDP that collects mostly first-party data, a data management platform (DMP) collects mostly third-party data. Each data platform collects some second-party data.
The data from a CDP is more personal (names, contact details, addresses, etc.), whereas DMPs focus more on anonymous data such as IP addresses, cookies or device information.
Because DMPs collect anonymized data, companies can't be 100% certain that the data was collected in a legal or ethical way. CDPs, on the other hand, normally have very strong data security standards, which means website visitors can also choose to share their data or have it deleted.
CDPs also retain their data for a longer period of time—to create "known" unified customer profiles—compared to DMPs that use their data for a shorter time to generate better targeted advertisements (often using bidstream data) or to build lookalike audience profiles (such as "women over 30 that enjoy gardening").
Differences Between CDPs and CRMs
As mentioned, CDPs can collect both online and offline data. This is different to customer relationship management (CRM) tools that mostly collect data from online sources. CRMs can incorporate offline data, however, these need to be entered manually.
Data that CDPs collect can be from known or anonymous sources, whereas CRMs only collect data from customers, or potential customers, that purposefully interact with the company.
As such, CRMs can only manage individually-entered data, compared to CDPs that are built to collect information from multiple data points through a large variety of different sources.
CDPs also focus on creating a full view of a company's customers and their behaviors with the company to improve their overall experiences. They can also use the data interchangeably with CRMs or DMPs to target any type of marketing.
Alternatively, CRMs analyze and manage sales-based information such as the customer's journey through a sales funnel, business transactions or predictive sales forecasts.
CDPs vs Data Warehouses and Data Lakes
Data lakes and data warehouses are both centralized data repositories that store all the corporate data of a company.
Data lakes store the raw, unstructured form of data that matches the forms of its original data sources—such as customer, transaction, product, store and human resource data—whereas data warehouses store the structured and processed form of this data.
A data warehouse—also referred to as an enterprise data warehouse (EDW)—is normally used by a company's managers or business-end users to report and analyze information based on the company's needs and performance indicators.
Alternatively, a data lake is used by IT professionals and scientists to run enterprise-wide machine learning and analytics to gain new business insights.
A CDP is different because, although it's also a centralized data repository, it integrates with EDWs and data lakes and uses only the customer data that they store. As such, it works with data on a smaller scale, making this information available to marketers and sales teams without needing constant help from the IT department.
Data lakes and EDWs don't need to match or merge their data—this would make it more difficult to analyze—which means they don't provide the cross-channel identity resolution technology that a CDP does to create a single customer view (SGV).
Data lakes and EDWs also don't update as frequently as CDPs do, because it would slow down the company's internal systems. This is another reason why a company's marketing team would use a CDP over the other repositories—they can extract and use up-to-date data much faster than having to wait for feedback from the IT department.
Data lakes, EDWs and CDPs have somewhat of a symbiotic relationship when it comes to data sharing. EDWs and data lakes often send more insightful customer profile and transactional data to CDPs, which in turn will send their customer activation data back to the data lakes and EDWs.
This allows companies to have more precise and accurate data when performing enterprise-wide analysis.
Final Thoughts
When it comes to choosing between CDPs, CRMs or DMPs, companies shouldn't ask "Which one..?" but rather look at using all three to help them improve their marketing efforts and provide a more personalized customer experience.
Bigger enterprises should also incorporate data lakes and EDWs for data storage and analytics, alongside a CDP that can use this information to create a single customer view and serve as a data repository between multiple channels. This will allow marketers to create advanced data-driven marketing campaigns across different touchpoints.
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FAQs
What Is the Difference Between a CRM and CDP?
A CRM is a software system that tracks all sales-based customer communications and information through sales, financial, customer support and marketing automation systems to help businesses improve their customer relationships and sales.
This is different from a CDP that uses customer data, gathered from multiple channels, to create a holistic 360 degree view of the customer to help the company better understand its customers.
What Are the Four Types of Customer Data?
- Identity data: Customer name, surname, age, gender and contact details
- Descriptive data: Types of vehicles or pets the customer owns, recreational activities/subscriptions, current work industry and family size
- Quantitative or behavioral data: Customer behavior, service queries, website visits, email opens and purchase data
Qualitative data: Online product ratings, opinions and purchase motivations
