Table of Contents

The pros and cons of using a customer data platform as your data warehouse:

  1. The cost of a CDP can be lower than a data warehouse, depending on your data integration workflow.

  2. CDPs enable organizations to democratize insights, improving access for both technical and non-technical users.

  3. Users can benefit from the marketing-specific features of a CDP over a data warehouse.

  4. CDPs may not be as general-purpose and robust as a data warehouse.

  5. Data warehouses and variants like data lakes are better at handling unstructured data than CDPs.

  6. CDPs must offer the same data privacy and security features as data warehouses.

Does your Ecommerce business team understand the customer journey? By tracking the history of individual customer behavior and customer interactions across different channels, your organization can better understand what motivates your audience — and cater to them with the right marketing campaigns.

To help with the task of data collection about the customer experience, many companies use a dedicated customer data platform (CDP). This software helps build a customer 360 view of your audience, bringing together information from different sources in your IT ecosystem into a single customer database.

Some businesses are so heavily invested in customer data that they consider using their CDP as a general-purpose data warehouse. But is using a customer data platform as your data warehouse a good idea, or do you need to consider pitfalls and drawbacks? This article will cover everything you need to know about using a customer data platform as a data warehouse, plus the pros and cons of having a CDP as your data warehouse.

What is a Customer Data Platform (CDP)?

A customer data platform (CDP) is a software-based solution that functions primarily to unify different types of data on your audience’s demographics, behavior, and interactions with your business. With that, a CDP helps you create customer profiles of individual people, forming a single customer view for everyone in your organization.

CDPs take an omnichannel approach, collecting data points from multiple customer touchpoints in your business, from website visits and newsletter clicks to social media likes and shares. This behavioral data can then be combined with transactional data about customers’ purchases, helping you better understand what makes your audience tick.

The primary beneficiaries of CDP software are marketing team members, as well as executives and other key stakeholders. The information you glean and store in your CDP platform can then be taken up for business intelligence (BI) and analytics workflows, extracting hidden insights for smarter decision-making.

CDPs empower you to adopt fresh new marketing strategies and initiatives. For example, you might find that changes to your marketing automation sequence result in a higher conversion rate or improvements to your customer lifetime value (CLV) and other metrics. You might also discover novel approaches to audience segmentation, enabling you to deliver better, more personalized experiences to different groups of customers.

Just a few advantages of using a CDP include:

  • Single source of truth: A CDP should contain the most accurate, up-to-date customer data your organization has on hand. Storing this data in a CDP ensures that people in different departments — from managers to IT teams — are all on the same page using the same information.

  • Data integration: CDPs aggregate data from many data sources and data sets, both internal and external to your business. CDPs differ from a DMP (data management platform) both in the type of data they collect (customer-focused vs. general) and the data’s origin. Whereas CDPs usually focus on first-party data (i.e., customer information your company generates, manages, and owns), DMPs often focus on third-party data (i.e., information from external sources such as other companies or government institutions).

  • Identity resolution: Your business may have multiple ways of identifying the same person: name, phone number, email address, website cookies, etc. One of the most important functions of a CDP is to perform identity resolution: automatically storing all these identifiers under the same customer profile, fleshing it out and giving a more complete picture.

One final note: CDPs are not quite the same as CRMs (customer relationship management) software. Although both CDPs and CRMs are intended to store customer data, CDPs focus on building customer profiles. As such, CDPs can also store profiles of anonymous and unidentified users, a feature that CRMs typically lack. According to Forbes, a CDP is “like a CRM on steroids. It doesn’t so much help you engage the customer as it helps you engage them in an even more meaningful way.”

Getting your data into a CDP is much easier with the right ETL and data integration tool. Take a test drive with the 7-day pilot of Integrate.io's powerful yet user-friendly solution for data integration.

What is a Data Warehouse?

A data warehouse is a centralized repository that performs multiple data management functions: aggregation, storage, processing, and analysis. Data warehouses use data integration methods such as ETL (extract, transform, load) to collect information from various sources and preserve it in a single, unified, accessible location.

Just as a CDP offers a “single source of truth” for your customer data, the data warehouse provides a single source of truth for general-purpose data across the enterprise. As such, these repositories help break down "data silos," in which potentially useful information is only accessible to a single team or department — and not to others who might need it. Data warehouses have use cases that range from improving sales and marketing performance to capturing data on industry trends.

Once in the data warehouse, information can be analyzed using artificial intelligence and machine learning to uncover hidden trends and insights. These discoveries can then be converted into reports and visualizations for executives and managers to consult during the decision-making process.

The data warehouse is the most common variant of a centralized data repository, but it's not the only one. A popular variant is the "data lake," which can also store raw data that has typically not gone through the transformation stage of data integration. In addition, a data mart is essentially a mini-data warehouse that's purpose-built for the exclusive use of a single team or department.

Pros and Cons of Using a CDP as Your Data Warehouse

The concepts of a customer data platform and a data warehouse are related but not identical. The most significant difference between a CDP and a data warehouse is the types of data both solutions are intended to hold. Whereas a CDP restricts itself to customer data, the data warehouse has no such limitation: users can store everything from internal company records to their competitors' historical performance data.

However, the fact that data warehouses are by default more general-purpose doesn’t make them the best fit for every business. Data warehouses can be too bulky and expensive for organizations with lighter data handling needs. If most of your organization’s data is customer-focused, treating the CDP as your primary data warehouse or repository may be more sensible.

The choice to use a customer data platform as your data warehouse will depend on your unique situation, and there’s no correct answer for every company. Below, we’ll discuss the various pros and cons of using a CDP as your data warehouse.

Pro #1: Lower costs

One major selling point for using a CDP as your data warehouse is that it can significantly lower data management costs. CDPs are not designed to handle other types of information beyond customer data, so you don’t have to pay to store, process, and analyze it.

If your BI and analytics workloads are heavily focused on customer data, it may not make sense to use a general-purpose data warehouse with a scope that’s too broad for the job. Combined with the right data integration tool, using a CDP as your data warehouse can mean significant cost savings.

The Integrate.io data integration tool charges users based on the number of connectors they use in their workflow — not on the amount of data they consume. This means businesses moving from a data warehouse to a CDP can save big if they also cut down on the number of data connectors they use. Contact us today for a 7-day pilot of the Integrate.io platform.

Pro #2: Democratized insights

Data science experts speak of “democratizing” information and insights, which means making them available to everyone in the organization who needs them. This is the goal of techniques such as reverse ETL, which moves information out of a centralized data warehouse and into other software and systems for easier access.

Analyzing the contents of a data warehouse is often a highly technical project, requiring the assistance of data scientists and engineers. On the other hand, third-party systems like customer data platforms come with BI and analytics tools that let non-technical business users run their own queries and get keen insights.

Pro #3: Marketing-specific features

Customer data platforms have been built from the ground up for the specific needs of sales and marketing teams at customer-focused businesses. This means CDPs come with many features and functionality that exceed what you can accomplish with a standard data warehouse out of the box.

For example, as discussed above, one of the most important CDP operations is identity resolution: combining different data sources about the same customer. However, performing identity resolution can be much trickier than a simple JOIN SQL query that you might run in a data warehouse, since each individual record can be incomplete and fragmented. CDPs, conversely, offer sophisticated algorithms and features for identity resolution and other common operations with customer data, providing invaluable assistance from day one.

Con #1: Loss of features and flexibility

CDPs come with more marketing-specific benefits, but using a CDP as your data warehouse can mean the loss of some features. As a general-purpose repository, data warehouses typically come with a wider range of features and functionality. Users can slice and dice their information as they see fit, organizing it in the way that makes most sense to the business.

CDPs, on the other hand, may limit how you store information. For example, CDP vendors may require users to adhere to a strict data model, with each piece of information belonging to a specific user or account.

Before taking the leap, make sure that migrating from a data warehouse to a CDP won’t stifle your data workflows. If you’re on the fence, speak with several CDP providers to learn exactly how their products and services work, and how these offerings can replace your existing setup.

Con #2: Handling unstructured data

As discussed above, a variant of the data warehouse known as the data lake excels at handling unstructured and semi-structured data. There’s even a happy medium called the "data lakehouse," which adopts elements of both architectures to get the benefits of both.

However, customer data platforms often struggle to incorporate large amounts of unstructured data (such as audio, video, and text) due to the rigid nature of their data models. If you expect to consume a large amount of unstructured data in your analytics processes, relying solely on a CDP may be challenging.

Con #3: Data privacy and security

Most enterprise-grade data warehouses come with features and functionality to enable compliance with regulations such as the European Union’s GDPR (General Data Protection Regulation) and the CCPA (California Consumer Privacy Act). These laws strictly limit the storage, processing, analysis, and retention of an individual’s personal data.

For example, the Snowflake data warehouse includes a “time travel” feature that allows users to access historical data within a specific time period. This is extremely useful for meeting the GDPR, which requires personal data to be deleted after a certain amount of time (or if the user requests it).

When migrating from a data warehouse to a CDP, you need to ensure that your choice of CDP software offers the same data privacy and security guarantees as the previous repository. Because CDP platforms lack the general-purpose functionality of a data warehouse, you may need to compensate for the loss of some features with a custom-built solution.

How Integrate.io Can Help with Customer Data Platforms (CDPs)

As we’ve discussed above, there are both pros and cons of using a customer data platform as your data warehouse. However, whether you use a CDP or data warehouse as your “single source of truth,” you need the right data integration tool. Your solution should work seamlessly with your existing setup, helping extract information from across the enterprise and push it into your CDP or data warehouse.

Integrate.io is a powerful, feature-rich new solution for data integration and ETL that's been built from the ground up for the needs of Ecommerce businesses handling customer data. Thanks to Integrate.io’s user-friendly, no-code, drag-and-drop visual interface, users of any technical level can get started building robust, production-ready, real-time data pipelines.

With Integrate.io, users have access to more than 140 pre-built connectors and integrations for extracting from a wide variety of data sources. These connectors include the most popular web services, SQL and NoSQL databases, analytics tools, and other data sets, so the platform seamlessly fits into your existing data integration workflow.

The Integrate.io platform comes with deep Ecommerce capabilities, offering many tremendously useful features for users of customer data. For example, Integrate.io’s lightning-fast FlyData CDC (change data capture) functionality automatically detects only those records and databases that have changed since your last ETL job. This helps save massive amounts of time and manual effort, making your data integration pipelines much shorter and more streamlined.

Integrate.io also includes reverse ETL capability for sending data out of a centralized data warehouse and into third-party software (such as a customer data platform). This approach helps operationalize your data, making it more accessible to a wider, non-technical audience who uses this software.

Want to learn more about how Integrate.io can help with customer data platforms and data warehouses? Get in touch to discuss your business needs and objectives, or to start your 7-day pilot of the Integrate.io platform.