You want the right data to drive personalized CX for a wide range of simple to complex use cases. You want to easily build and deploy data-rich segments to drive your data through to CX impact – delivering high ROI and low TCO without burdening IT.
You want the most complete, composable CDP for any cloud environment, MarTech stack, AI approach or use case – with data-in-place to give you control and flexibility.
But what is composability? You have questions. We have answers.
What is composability?
Composability refers to designing systems with interchangeable and interoperable components, allowing for greater flexibility and adaptability. Composability entails a modular approach where buyers have the freedom of choice to obtain best-of-breed components that complement existing investments. More than just assembly, composability is also an enterprise approach that prioritizes agility. According to Gartner, the core principles of a composable business are modularity, autonomy, orchestration and discovery.
In deciding whether a composable architecture makes sense for your business, one question to ask is how a composable environment will help you more quickly reach untapped business value. One purpose of a composable approach is to be more nimble, ready to easily pivot to sudden business and consumer changes. Another is to achieve specific business goals and unique tasks or processes via a customized toolset. For a composable framework to reach its full potential, each component of a composable system should create value as it applies to a business function.
What do people mean when they talk about a composable CDP?
Often when people talk about a composable CDP they’re referring to what’s called a zero-copy data or a data-in-place CDP, which means that your customer data sits in a data cloud. This is a distinction from the CDP having a built-in database in a traditional “packaged” CDP which is typically offered as software-as-a-service (SaaS) where the vendor hosts and maintains your data and builds a Golden Record on your behalf. A composable CDP that runs in a data cloud and performs core CDP functionality without having to replicate data allows you to control your customer data behind your own security perimeter, while still connecting to all your MarTech touchpoints and enterprise data sources.
A composable CDP that runs in a data cloud and performs core CDP functionality without having to replicate data allows you to control your customer data behind your own security perimeter, while still connecting to all your MarTech touchpoints and enterprise data sources.
A composable CDP that runs in a data cloud and performs core CDP functionality without having to replicate data allows you to control your customer data behind your own security perimeter, while still connecting to all your MarTech touchpoints and enterprise data sources. A composable CDP is about choice, allowing you to bring together best-of-breed capabilities from one or more vendors to create a purpose-built, cohesive platform through API integrations to give you more flexibility and speed-to-value to achieve your unique CX and business use cases. This approach balances control with the flexibility to add or change components as your business and use cases evolve.
Can a packaged CDP also be composable?
A packaged CDP can also be composable if it still permits you to choose the functionality you need, and allows you to use predefined features and functionality to perform day-to-day tasks without a separate sign-on for each process. With a packaged CDP, the software vendor will control the database, management, security and operational components, but it will retain characteristics of a composable CDP if you the marketer or business user maintain the flexibility to select only the functionality that you need.
What should marketers and IT expect to get out of a composable CDP?
For both marketers and IT, a data-in-place composable CDP provides many benefits. For IT, a composable CDP makes it easier to control costs and limit data exposure. From a practical standpoint, what this means is being able to adapt quickly to changing business requirements by assuming and reconfiguring data and the tech stack as needed.
For marketers, a composable CDP in a data-in-place environment provides a consistent, up-to-date and accurate view of a customer without data replication, enabling faster innovation and the ability to tailor solutions to specific customer needs more effectively. You have the flexibility to customize your MarTech stack and customer data, agility to respond to a changing market and evolving regulations, and you can manage your workflow with ease without having to routinely submit tickets.
For all stakeholders, a composable CDP provides vendor flexibility without having to sacrifice data security or accuracy, allowing you to:
- Minimize data movement and the systems you manage, saving valuable time and effort with streamlined integrations and vendor connection architectures
- Focus on your team’s projects and priorities when other teams utilize secure, no- and low-code tools that don’t require tickets
- Optimize costs by leveraging pay-as-you-go pricing models
- Minimize infrastructure costs
- Achieve the perfect balance between performance, functionality and cost
What does assembling a composable framework look like?
Just as a “one-size-fits-all” software approach isn’t ideal, there is also the possibility of having too many pieces (and too many vendors). When there are too many moving pieces to manage, the burden shifts from your software to your people. With the knowledge that custom setups should help you, not cost more money or more time and effort to manage, be wary of systems that have a separate tool for everything. That situation usually creates overlap, and when two or more of your components do the same thing, you inadvertently create an inefficient system that often results in duplicate work, more time managing vendors, additional IT oversight and increased costs.
Value-driven composability refers to integrated processes with role-specific use interfaces to accomplish day-to-day tasks. Having standardized, well-documented integrations helps reduce complexity when new components are added. To avoid “over composing” or composing at too low a level, it’s important to start the design phase knowing precisely what you need a composable CDP to do. What special connector services will you need to ensure that different components “talk” to each other, for instance? Be aware that hidden costs may arise when you have to:
- Use multiple tools to create and run a new campaign or orchestration
- Find, troubleshoot and fix broken connections with a complex, multi-point setup
- Add SQL, Python or Java headcount (or submit an IT ticket) to build new segmentthere does data quality fit into a composable architecture?
Where does data quality fit into a composable architecture?
Do not underestimate the importance of data quality. In a composable system, the interoperability of components relies on consistent and reliable data inputs and outputs. Data validation, cleansing, and normalization processes should be implemented to ensure data quality across different components. The Redpoint CDP performs all data quality exercises (cleansing, validation, normalization, identity resolution) as data is ingested, resulting in clean data that is ready for business use for all downstream purposes and programs. Performing data quality processes once and up front ensure that all downstream use cases are working with clean data.
In a composable system, the interoperability of components relies on consistent and reliable data inputs and outputs. Data validation, cleansing, and normalization processes should be implemented to ensure data quality across different components.
It’s important to keep in mind that many vendors consider data quality as mere consented data, or as a stand-in for basic deterministic identity resolution or even basic de-duplication. A composable system that does not prioritize data quality will result in overmarketing (sending identical messages to the same person), under-marketing (thinking multiple profiles are the same customer due to poor identity resolution) and, ultimately, CX friction.
What does operating a composable system look like?
The following are important issues to consider for operating a composable system to minimize what Gartner deems “operational risks” to include loss of an easy-to-use UX, a canvas-style interface for segmentation and messaging sequence and out-of-the-box connectors to MarTech systems:
- Interface Design: A user should be able to work between systems without having to jump to different interfaces.
- Dependency Management: Manage dependencies between components to avoid cascading failures and minimize the impact of changes to individual components.
- Documentation: Thoroughly document each component’s functionality, interfaces and dependencies to facilitate understanding and usage by developers – and to avoid feature and function duplication across your setup.
- Testing: Implement comprehensive testing strategies to ensure that different components work correctly together and maintain expected behavior across various compositions.
- Security: Pay close attention to security implications, especially when integrating third-party components, to prevent vulnerabilities or data breaches.
- Training: Consider whether specialized training or coding will be needed. How soon will marketers be up-and-running?
How do I make sure performance meets my use case requirements in a composable CDP?
When designing a composable CDP, organizations should carefully evaluate their business objectives, data requirements and technical constraints to ensure it effectively addresses their specific needs and provides tangible business value.
A common misconception about a composable CDP is that it will not power real-time experiences. But that is only true for a CDP that does not store customer data, and in a data cloud environment must make call-outs to various systems to obtain information about a customer. In such a “warehouse-first” concept of what it means to be composable, workflow complexity may increase because marketers will have to work with IT to retrieve an updated dataset from a data warehouse.
In contrast, a composable CDP that provides a single customer view in a data cloud environment will meet performance requirements for any CX use case. When a composable CDP runs on a data cloud and there is no data replication, API integrations with real-time data streams and event processing systems provide marketers with a consistently updated unified customer profile. Use cases that run on batch processing, near real time and real time are all supported.
Can a composable CDP run in a private cloud/on-premise environment?
A composable CDP can run in a private cloud/on-premise, in a public cloud, or a hybrid of the two, and connect to all your MarTech touchpoints and enterprise data sources. Flexibility and adaptability extends to deployment options, allowing for a composable CDP to be configured to operate either in a private cloud or on-premise. Considerations for where to deploy a composable CDP include:
- Security and compliance: Running a CDP in a private environment can enhance control over data security and compliance with industry regulations, an important consideration for organizations handling sensitive data.
- Vendor support: A private deployment will require dedicated resources for maintenance, updates and management. Organizations should be clear about what type of support or resources a vendor will provide.
- Infrastructure requirements: A private cloud or on-premise infrastructure will need to meet the necessary hardware, software and networking requirements to support the composable CDP requirements, including whether the infrastructure can handle the anticipated data volume and processing demands.
