Customer Data Platform vs. Data Warehouse
It is easy to confuse a Data Warehouse with a CDP. At the peak of the Data Warehouse hype, they were seen as the answer to enterprise businesses’ prayers – a place to store every scrap of Big Data, so that it could be analyzed as a whole to bring about efficiencies and spot patterns that might help to improve performance. But what made Data Warehouses exactly right for this job, and are CDPs better suited to the needs of modern marketing teams?
What is a Data Warehouse?
A Data Warehouse (often referred to as an Enterprise Data Warehouse, or EDW) is a central repository in which large amounts of business information, from multiple departments and data sources, are integrated. Data warehouses contain data from sales, marketing, purchasing, finance, (really any and all business functions.) The data, whether about employees, customers, support tickets, infrastructure, finance etc, is generally held in one big pool, a single, reliable source of information, that any department or stakeholder can potentially access for reporting and analysis purposes.
Data in a Data Warehouse tends to be difficult to access for non-technical staff, and is usually guarded by the IT department due to security concerns and permissions. For example, sensitive information about employees may be in the data warehouse and it’s important that only the right level of employee can access that specific information.
Because so much data needs to be ingested and processed, often using ETL tools or query builders, Data Warehouses also require a lot of looking after and maintenance. Planned periods of downtime will be scheduled in which caches of fresh data can be uploaded, and data compliance can be a tricky issue, since the pooled data is owned by many different departments, so it’s unclear whose responsibility it is to manage it.
How is a Data Warehouse different to a Customer Data Platform?
The main differences between an EDW and a Customer Data Platform (CDP) are their scale, purpose and treatment of the data.
As Data Warehouses store all corporate data, this typically makes them large, expensive, IT-driven and owned projects designed to serve as a repository for analysis across the whole enterprise. A CDP, as the name suggests, is interested only in customer data (generally at a much smaller scale), and is built for the needs of marketers and operated by Marketing, without the need for constant IT involvement.
An EDW is designed to support reporting and analysis, so while it cleans and deduplicates data in the same way as a CDP, to create one reliable record of truth, there is no requirement to match and merge the data; that would make it harder to analyze. Therefore, it does not include cross channel identity resolution for the creation of a Single Customer View in the same way as a CDP, nor does it support real-time updates, since those aren’t needed for wider business reporting and would slow the system. This means marketers cannot use EDWs to run reactive campaigns or extract and use the data they need as quickly as if they were using a CDP.
Additionally, EDWs do not transform, standardize or normalize the data specifically for marketing purposes. A retail business, for example, may store purchase and/or transactional data as codes (‘MX1294’ rather than ‘brown leather shoes’). The process of ‘normalization’ in a CDP will transform the MX1294 code into something that is (a) meaningful to marketing, (b) meaningful to the customer and (c) usable in the personalization of campaigns. Even more useful, and commonly seen in multi-channel organizations, it can merge and normalize different product codes, from different systems and consolidate into the category of ‘brown leather shoes’.
Being able to bring all this data together in a standardized and normalized format is extremely valuable, as it allows marketers to understand the buying behavior of their customers across systems and activate that data without the arduous task of data wrangling, writing scripts, waiting on IT or typing endless v-lookup formulae into spreadsheets.
With Data Warehouses, there is no such focus on marketing intelligence. The use cases for a Data Warehouse could range from giving Marketing access to data with the goal of reducing the strain of data requests on IT, to giving HR a consolidated view of performance, holidays, illness and company revenue to look for ways to optimize staff performance to improve profitability. Essentially, the Data Warehouse purchase is an unselfish purchase by IT to provide data insights to every area of the business.
The Customer Data Platform however, is a selfish purchase for marketing only, and the use cases are more focused on delivering additional revenue from customers through improved personalization and segmentation. The improved integration of marketing channels results in less data requests for IT to deal with, and the system is fully focused on deriving improvements that will optimize the results and revenue from marketing initiatives (and HR will never have any access).
This single control of data makes data protection a cinch. While multiple departments contribute to and have access to the Data Warehouse, the CDP mainly processes first-party customer data which is owned by the marketing department. It need never be shared with people who shouldn’t have access, and all customer data permissions can be managed in one location. Segmentation of information into the Single Customer View also means DARs can be created with ease.
A Data Warehouse is a fantastic purchase for an enterprise business, enabling them to use data to inform company-wide business decisions and find both efficiencies and opportunities that will make the business more profitable. It is an IT led project and can have profound effects on any business that is looking to become more insight-driven. For mass data collection, storage and reporting, it can’t be beaten.
The CDP, however, is built specifically for marketing team use and provides far-reaching benefits for marketers that the Data Warehouse does not. For personalization, integration of execution channels and the de-duplication and normalization of data, marketers need their own data store. A Customer Data Platform will meet these needs perfectly, and if the business already has a Data Warehouse in place it can be leveraged to make the implementation of a CDP easier, quicker, and therefore cheaper.
This blog article is an extract from BlueVenn’s “A Marketer’s Guide to Customer Data Platforms” eBook.
Remember, this is blog 3 of 5 in our Customer Data Platform series. For more from our CMO on the CDP landscape, capabilities and functionality, read blog 4 of 5 now or subscribe to the blog for alerts.