How to Turn Your Data Warehouse Into a CX Engine
Concerned about the security and cost of creating copies on copies of your data, and having to constantly write SQL for your marketing team to activate that data? Luckily, there’s an alternative to that — and it’s all about composable customer data platforms (CDPs).
Enterprise businesses spend time, money and expertise deploying their data warehouses, but when a CDP is introduced, it usually means buying the whole new package of software and copying data into the CDP from the data warehouse to make accessible audiences and insights for marketers — more copies means more risk, more cost, more inconsistency, and more time.
So where does this leave data infrastructure teams? Marketing and business users still need access to customer data to drive the business forward, and asking marketers to run SQL in order to access it is still a tall order.
The ideal solution would offer the marketer-friendly capabilities of a fully functional CDP while mapping directly to the centralized data warehouse. This means leveraging your existing investments to power your customer experiences directly — think no risk, all reward. Enter composable CDPs.
Let’s take a look below at the fundamentals of bundled and composable CDPs to understand the key differences, along with the key elements and benefits of a composable approach.
The Bundled CDP vs. the Composable CDP
According to the 2022 Gartner CIO and Technology Executive Survey, 60% of organizations plan to invest in composable enterprise technology within the next three years. When you consider that 63% of chief information officers at organizations with high composability reported better business performance when compared to their industry peers, it’s easy to see why. Let’s take a look at the definitions.
What is a Bundled CDP?
Bundled CDPs — which the Customer Data Platform Institute defines as “packaged software” that is typically controlled by business users — are packaged infrastructure and applications of a CDP that require IT professionals to comply with individual vendors’ platform architectures, including all features and apps.
For some organizations – like those that have not heavily invested in a centralized data store – this is a great option. It simplifies the use of customer data for business teams and some bundled CDPs offer a path to composability if data infrastructure matures.
What is a Composable CDP?
Composable CDPs, while identical to the business user, are dramatically different on the back end. Composable CDPs enable a zero-copy architecture with capabilities to eliminate local storage of data copies. The warehouse agnostic approach offers flexibility so that teams can select their preferred cloud infrastructure while providing business teams with an advanced no-code interface.
3 Key Elements of a Composable CDP
Not all composable CDPs are created equal — in fact, for a CDP to qualify as composable, it needs to meet all three of the following criteria.
- Zero copy architecture: Zero-copy architecture avoids duplication of data and associated costs and security risks by allowing data computation to be performed in place within a company’s own data infrastructure. This design enables companies to leverage their existing data storage and processing resources — rather than copying data to external systems or vendors.
- Warehouse-agnostic: Things change and the composable CDP should not be tied to a single data warehouse or storage system and should instead work with any type of data storage system. This is important because it allows the system to be more flexible and adaptable based on different client use cases.
- No-code UI: In order for a composable CDP to benefit the IT and data organization, it needs to enable marketers to self-serve data and insights. As such, composable CDPs must offer a no-code interface into the data warehouse that does not require SQL. The CDP should be able to act as a translation layer between a no-code UI and SQL that will run on the data warehouse.
3 Key Benefits of a Composable CDP
- Control: Because the CDP will directly query the data warehouse, there’s no need for the IT team to continuously replicate data for upload into the system. With composable CDPs querying the data warehouse directly, IT teams can control data access and replication to improve data security and privacy.
- Agility and efficiency: With a bundled platform, you need to take all of the apps and infrastructure that come with it. With composable CDPs, you don’t have to undo or fail to act directly on the data infrastructure that your team has built. With composable CDPs, IT teams can swap out solutions as necessary to improve efficiency and keep costs associated with copies and redundant apps and infrastructure under control.
- Innovation: The key to future-proofing your martech stack is all about options and flexibility. Rather than committing to an entire set of apps, organizations can plug and play with different solutions designed to suit their needs. With composable CDPs, IT teams can plug and play different solutions to quickly expand capabilities.
Keep Composed and Carry On
IT and data teams have worked hard to centralize all of their company’s data to drive the business forward — so why sacrifice efficiency and performance by wasting architectural efforts (and money) on another bundled solution?
Intead, IT teams need to amplify the power of data lakes to maximize the value of their investments. And with a composable approach, you can save yourself a SQL headache with your marketing team.
See For Yourself in a No-Cost, Zero-Risk Proof of Concept
ActionIQ is offering a free trial that can be stood up in as little as 30 minutes. Just bring your data from an existing cloud data warehouse like Snowflake, Databricks, BigQuery or AWS Redshift and watch as a simple marketer-friendly interface gets quickly mapped directly to the data where it lives — no data copy required. This process takes only minutes to complete, and allows business users to test self-service audience building and journey mapping, and data teams to test and validate queries natively pushing down to their existing data warehouse investment.