What is a Composable CDP?

What is a Composable CDP?

A Composable CDP has the same goal as a traditional CDP: activating customer data to downstream tools. But rather than operating as a separate entity and storing data outside of your current data infrastructure like a traditional CDP does, a Composable CDP is an activation layer that lets you curate audiences, orchestrate journeys, and send your existing data to your frontline marketing tools.

Traditional CDP vs. Composable CDP

The difference between a traditional CDP and a Composable CDP is that a Composable CDP lets you start with your current data (wherever it is) and activate it immediately rather than implementing and purchasing an entirely new tool.

The modularity of this architecture gives you far more extensive capabilities and flexibility to uniquely solve your most complex customer-facing use cases. This means you don’t have to conform your data to the requirements and constraints of another platform, and instead take advantage of your existing data assets.

A Quick History of CDPs

Traditional CDPs have been around for a long time, with Segment pioneering the space in 2011, but most CDPs didn’t actually set out to solve customer-facing use cases. In reality, many of the largest platforms today started out as a CRM or an event collection platform–only transitioning into a full customer data offering later on after realizing that companies have far more complex problems they need to solve.

Traditional CDP Architecture

CDPs emerged when data collection and data management were exceptionally difficult. These platforms pre-date affordable cloud solutions and, most notably, the cloud data warehouse. In some ways, CDPs were actually the very first data platform to democratize customer data. Prior to CDPs, marketers had no ability to access any of the insights from data teams.

There was a huge gap between data and marketing teams because non-technical users had no ability to access data assets, and data teams were forced to supply ad-hoc CSVs or build and maintain custom pipelines to various downstream destinations to make data available. When these CDPs came along, suddenly, any marketer could immediately access rich clickstream behavioral data to build audiences for marketing and personalization use cases.

How Traditional CDPs Work

Most CDPs are actually powered by cloud data warehouses under the hood. While cloud data warehouses are largely used as large computing engines to query datasets and drive analytics, traditional CDPs build upon that architecture to create a bundled offering for data collection, audience management, and activation.

Fundamentally, CDPs are perhaps one of the most revolutionary technological advancements in the martech world. For years companies of all industries and sizes have relied on these platforms to power their customer-facing experiences. As such, every traditional CDP is made up of four bundled components:

• Data Storage: All CDPs offer fully managed storage to house your customer data.
• Identity Resolution: Traditional CDPs have built-in identity resolution features to stitch together user actions and attributes across touchpoints.
• Audience Building: CDPs provide a rich suite of audience management tools to help you build user cohorts and orchestrate user journeys across your marketing channels.
• Data Syncing: CDPs provide out-of-the-box integrations with hundreds of third-party APIs, enabling you to send audiences directly to your operational tools.

Components of a Traditional CDP

Fundamentally, each of these components comes tightly bundled together in a single platform, which means you are inevitably forced to pay for every feature set within a CDP, even if you’re only going to use one aspect.

How Does a Composable CDP Work?

A Composable CDP is much simpler compared to a traditional CDP, especially in the context of your own customer data. The core difference between a traditional CDP and a Composable CDP is that a Composable CDP doesn’t act as a black box that stores and manages your data. A traditional CDP bundles collection, storage, modeling, and activation into a single platform, whereas a Composable CDP enables you to activate your data using your existing data collection, storage, and modeling practices.

The easiest way to understand a Composable CDP is to think of it as an activation and audience management layer that lets you build audience cohorts (using both first-party and third-party data) and sync them to your frontline marketing tools, whether that’s ad platforms, email tools, or even lifecycle or omnichannel marketing platforms. You can think of a Composable CDP as a middleman between your data assets and your marketing tools.

How a Composable CDP Works

A Composable CDP is the only solution that is technology agnostic. As long as you have a table with columns and rows, your data can be activated–it doesn’t matter whether it’s in a data warehouse, a data lake, a production database, or even a spreadsheet.

This activation layer sits on top of your existing architecture without ever storing any of your data, giving you an easy-to-use interface that lets you organize your data so you can build hyper-personalized experiences for your customers.

Architecturally, all Data Activation platforms are powered by Reverse ETL, which is the process of copying data from your existing data stores and syncing it to your operational systems. The reality is that a Composable CDP is the only solution that lets you bring your existing data and take advantage of the full benefits of a traditional CDP without the negative implications.

The Emergence of the Composable CDP

The core problem that CDPs solve, helping you manage and activate your customer data at scale, isn’t going away anytime soon. In fact, the multi-billion dollar CDP industry is doing nothing but continue to increase. However, shortcomings of traditional CDPs have led to new competition in the market as more companies look to activate and monetize their existing first-party data.

The Fundamental Problems with Traditional CDPs

CDPs gained popularity because they addressed a core challenge in the martech world: helping bridge the gap between data and marketing teams. However, they also introduced a level of added complexity because the tightly bundled architecture introduces several problems:

• Storage and Data Ownership: Traditional CDPs create a second source of truth because they force you to store and manage data outside of your existing data infrastructure. In reality, you shouldn’t have to purchase another layer of storage to access the existing data you already own in your data warehouse.
• Flexibility: Because traditional CDPs are solely designed to collect clickstream data (e.g., page view, abandon cart, session length, etc.), the platforms have no understanding of your separate first-party data. Most CDPs are built around a rigid user and account-based model. This rigidity means you can’t leverage any custom data models or first-party attributes without complex engineering work.
• Time-to-Value: The average CDP implementation takes over six months to complete, and that’s not even accounting for the onboarding time you have to spend training your team to use new tools. To make matters worse, any time you want to add a new data source to a CDP or ingest more data, you have to build new pipelines. Tackling new use cases means starting from scratch and completely rearchitecting and implementing your CDP to align with your data.
• Incomplete Data: Since CDPs only collect and store behavioral data, they create a fragmented view of your customer. You have no ability to access or leverage any of your existing first-party attributes (income, age, gender, address) or the custom data models your data team has built without undergoing huge engineering effort.
• Cost: Traditional CDPs are extremely expensive because every feature is bundled together. Inevitably, this means you have to pay for collection, storage, and modeling even if you already perform these functions in your data stack.

Most companies have existing customer data, and they don’t want to deal with all of the baggage that comes with a traditional CDP.

Why the Composable Approach is Better

Traditional CDPs have no understanding of anything outside of your clickstream data. In reality, your business is much more complex than the actions people take on your website or app. You have other offline actions happening via phone support or your point of sales system, data science models your team has built to make predictions and recommendations, and first-party attributes that are unique to each individual user.

With a traditional CDP, all of this context is lost and inaccessible. Here are a few tangible implications of what this looks like in the real world:

1. With a traditional CDP, you can send an email to cart abandoners, but you can’t send that same email with a local store incentive.
2. With a traditional CDP, you can show ads to people who visited a specific page, but you can’t ensure those ads aren’t shown when the product is out of stock.
3. With a traditional CDP, you can send an SMS about a new promotion, but you can’t send that same SMS to people who have a high propensity to redeem it.

Each of these marketing use cases points out a fundamental problem: traditional CDPs have no understanding of custom objects that are unique to your business (e.g., local stores, products, propensity models). With a traditional CDP, it’s impossible to create a Spotify rewind campaign or serve personalized recommendations to speciifc audiences. Traditional CDPs boil everything down to clicks and sessions.

Advantages of a Composable CDP

While a Composable CDP has many advantages compared to a traditional CDP, there are three core benefits.

• Modularity: You have full control to choose what technologies and processes you use for data collection, storage, modeling, and activation. This allows you to tailor your architecture to the specific organizational outcomes you’re looking to drive.
• Flexibility: A Composable CDP gives you immediate access to any and all of your data–not just your clickstream events. Ultimately this means you can leverage any data type to easily accommodate the complex breadth of your use cases.
• Compatibility: Since a Composable CDP is technology agnostic and integrates with any data infrastructure, it easily adapts to future infrastructure changes so you can avoid tech-debt and vendor lock in.

The modularity of this architecture enables you can think in terms of use cases rather than “technology stacks.” Too many organizations have marketing use cases they need to solve, but they end up thinking too broadly in terms of technologies, not realizing that they simply need a way to activate their existing data.

Your decision to implement a new technology should be directly linked to the business value you’re trying to drive, and the work of your data team should be linked to the use cases they’re facilitating–not infrastructure.

Composable CDP Use Cases

While a traditional CDP is designed to solve generic marketing problems, a Composable CDP is much more flexible, allowing you to solve more complex use cases that simply wouldn’t be possible with a traditional CDP. Because a Composable CDP architecture is unencumbered by the limitations of traditional CDPs, you have extreme control and granularity when it comes to building and defining audience cohorts and powering your most complex marketing use cases.

Audience Curation

A Composable CDP is the only platform that enables you to leverage all of your data in your warehouse (regardless of how it is collected) so you can granularly build and define audiences for activation. This includes any data in your organization. Here are a few examples of what this might look like in the real world:

• Behavioral Data: App events and web events (e.g., page viewed, workspace created, item added to cart, last login, etc.)
• Offline Actions: Support tickets, phone calls, in-store purchases, and point-of-sale systems.
• Data Science Models: Propensity to purchase, personalized recommendations, experimental cohorts, etc.
• First-Party Attributes: Age, income, gender, email, location, deviceID, email, first/last name, income, etc.

How a Composable CDP Understands Customer Data

Ads

With a Composable CDP, you can power complex ad use cases that wouldn’t be possible under a traditional CDP because you can pass over more data to advertising platforms, thus increasing your match rates and lowering your customer acquisition costs (CAC). Here are a few examples of what this might look like in practice.

• Suppression Lists: Sending a list of recent purchasers to Facebook Ads to ensure you don’t accidentally advertise the same products to people who just purchased them.
• Retargeting: Syncing a list of recent cart abandoners to Google Ads so you can serve them ads across the web.
• Lookalike Audiences: Uploading a list of your top customers along with first-party attributes using the Facebook Conversion API so you can identify similar users to target.

Personalization

With a Composable CDP, you can power your most complex personalization use cases to ensure your delivering a consistent and relevant experience to all of your customers. This modular architecture allows you to easily orchestrate user journeys across marketing platforms and perform A/B testing in real time for various audiences that you define. Here are two practical examples:

• Lifecycle Marketing: Meeting your customers exactly where they are in the buyer’s journey and serving relevant and personalized experiences via push notifications, SMS, email, mobile, and web. Example: Uber notifying users when their ride has arrived.
• Omnichannel Marketing: Delivering consistent experiences across marketing channels so your customer needs are met wherever they are. Example: delivering tracking details across web, mobile, and email.

How to Build a Composable CDP?

Many companies have a misconception that they need to assemble a best-in-breed modern data stack before they can truly monetize their data. In reality, this is a lie. Traditional CDPs also rely on this assumption, forcing companies to undergo complicated implementations and re-implementations to ensure the platform is fully optimized for every feature set. The truth is most companies already have data storage, data collection, and data modeling capabilities.

All you need to get started with a Composable CDP is a Data Activation platform like Hightouch to put your existing stored data to work. Hightouch gives you power and usability without compromise. The platform is powerful, flexible, observable, and secure. Your data team can use SQL and all their favorite development tools, and your marketers can explore data and build audiences without writing a single line of code.

Turning your existing data infrastructure into a Composable CDP is really simple with Hightouch, and you can have data flowing in minutes:

• Step 1: Create a Hightouch workspace: After creating a workspace, you can connect to your data source(s) and destination(s). (Note: Hightouch only ever has read access to the data that you expose)
• Step 2: Define your data: You can visually choose what data you want to expose in Customer Studio so your marketing teams can easily self-serve using the parameters your data team has set in place.
• Step 3: Build your audience: Hightouch has a visual UI to granularly create audiences in seconds.
• Step 4: Sync your data: You can run your syncs to downstream tools manually or schedule them to run on a set basis that you define.

Final Thoughts

Without a Composable CDP, you’ll never be able to tackle complex personalization use cases. Hightouch lets you activate any and all of your customer data. This is the only architecture that works with any company regardless of data maturity, size, or industry. If you’d like to learn more about how Hightouch can help you drive value from your data, schedule a demo today!