The Gist
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CDP expectations adjusted. Organizations need more realistic CDP expectations to align with their capabilities in unifying and activating customer data.
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Composable CDP strategy. The trend toward composable CDPs lets companies build tailored solutions with flexible, modular components and avoid one-size-fits-all limitations.
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Successful CDP adoption. Clear use cases, technical assessments and external expertise are key to making sure CDPs drive tangible results for marketing teams.
Customer data platforms (CDPs) and their evolving role in marketing technology has left many professionals unsure of how to successfully implement them.
Let’s dive into the challenges, opportunities and misconceptions surrounding CDPs, along with the three key questions that experts say are plaguing marketing professionals:
- Have CDPs failed us?
- What trends are emerging in the CDP space? And how can organizations make sure CDPs work for them?
Table of Contents
Are Customer Data Platforms No Longer Effective in Modern Marketing?
The short answer is no, but the situation is much more nuanced. Customer data platforms have not failed as a technology. But in many cases, the expectations organizations have placed on them have been misaligned with reality.
At the heart of the issue is the fundamental question organizations have been grappling with for years: How can we activate data that exists in silos? Whether it’s static demographic data or dynamic behavioral data, organizations are constantly searching for ways to unify, enrich and activate this data to create a better customer experience. CDPs emerged in response to this challenge, as they offer a platform to unify disparate data sources. Analysts praised CDPs for their potential to streamline customer data management, while vendors were quick to jump on the bandwagon, eager to meet market demand.
However, over time, expectations around CDPs began to inflate. Organizations that were still struggling with the complexities of master data management (MDM) saw CDPs as a potential quick fix for all their data woes. This led to a scenario where CDPs were oversold as an all-in-one solution, which ultimately led to disappointment when they failed to deliver on unrealistic promises.
Ultimately, the disappointment we see in the market today stems from a cocktail of inflated expectations, organizational unpreparedness and a lack of clarity about what role CDPs should play in the broader marketing technology stack. CDPs have not failed, but organizations need to approach them with more realistic expectations and align their goals with the platform’s capabilities.
Related Article: Building a Strong Customer Data Strategy for This Year
Key Trends Shaping the Future of CDPs
The customer data platform landscape has evolved significantly since its inception, and several trends are shaping the future of this technology.
Composability: The Modular Approach to CDPs
One of the most significant trends we’re seeing is the rise of composability in CDP architecture. In the early days of CDPs, many organizations sought out a one-size-fits-all solution, an all-encompassing platform that could handle every aspect of customer data management. But as the market has matured, the focus has shifted toward more flexible, modular systems.
Think of composability as a set of LEGO bricks. Instead of buying a monolithic CDP that does everything (often imperfectly), organizations are now opting to build their CDP by selecting individual components that serve their specific needs. These components typically include core capabilities like data ingestion, identity stitching, audience building and activation. Additional layers, such as advanced analytics and downstream activation, can be added on top, depending on the organization’s requirements.
This modular approach allows companies to avoid unnecessary complexity and only implement what they need when they need it. Composability allows businesses to customize their CDP solution, making it more adaptable to their unique challenges and use cases.
Data Mesh and Zero Copy Architecture
Another trend gaining traction, especially in more mature organizations, is the growing recognition of the limitations of moving massive amounts of data between systems. As companies accumulate more data from a wider variety of sources (i.e., operational systems, data warehouses and public clouds), the costs associated with transferring this data back and forth between platforms can quickly become prohibitive.
This is where concepts like data mesh and zero copy architecture come into play. A data mesh approach decentralizes data ownership and makes it easier to manage and activate data without moving it between systems.
Similarly, zero copy architecture allows organizations to activate data where it already resides, without the need for costly and time-consuming data transfers. These trends offer a promising solution to the growing complexities and costs associated with managing customer data across distributed environments.
How to Maximize the Value of Your CDP
Customer data platforms are not a magic bullet, and organizations must be strategic in their approach to be successful. To quote Steve Jobs, “You’ve got to start with the customer experience and work backward to the technology. You can’t start with the technology and try to figure out how to use it.”
This principle holds true for CDPs as well. Organizations should begin by clearly defining their vision and strategy and breaking these down into tactical use cases. From there, they can assess the complexity of their needs in terms of data integration, touchpoints and analytics requirements.
Here’s how marketing professionals make sure a CDP project doesn’t fail:
Define Your Use Cases and Complexity
Organizations should start by identifying their specific use cases. For example, do you need a CDP to unify customer data across different channels? Are you looking to build more personalized marketing campaigns? Or do you want to create a seamless, omnichannel customer experience?
Once the use cases are defined, the next step is to assess their complexity. Consider factors like the number of data sources, integration points and touchpoints involved. Also, think about the level of analytics sophistication required and whether you need basic segmentation or advanced machine learning models.
Assess Your Technical Capabilities
Another critical step is to evaluate your organization’s technical capabilities. Do you have the technical muscle in-house to implement and manage a CDP? Or will you need external expertise?
This is where organizations need to be realistic about their resources. If your use cases are simple and you lack the necessary technical skills, a packaged CDP solution might be a better fit. In this scenario, you can rely on a vendor or partner to get your CDP up and running quickly.
On the other hand, if your use cases are more complex and you have a robust internal technical team, you might want to consider a more customized approach. By mixing and matching existing tools and technologies within your organization, you can build a CDP that meets your specific needs without unnecessary overhead.
Map Out a 2×2 Framework
A useful tool for organizations when deciding on a customer data strategy is the 2×2 framework. Along the X-axis, plot your organization’s ability to execute (high vs. low technical capability). Along the Y-axis, plot the complexity of your use cases (high vs. low). This simple visual can help you determine whether you need an off-the-shelf CDP solution or a more customized, composable approach.
Seek Professional Help if Needed
If your organization feels overwhelmed by the complexity of CDP implementation, it’s crucial to seek professional help. Whether it’s through a consulting firm or a specialized CDP vendor, getting the right expertise can make the difference between success and failure. CDP implementation is not a one-size-fits-all endeavor, and the right guidance can help align the technology with your business goals.
Related Article: CDP Evolution: Is the Hype Finally Over?
Building a Successful Strategy for CDPs
CDPs have a bright future ahead, but it’s important to shift your mindset away from thinking of CDPs as a pre-packaged, one-size-fits-all solution. Instead, organizations should view CDPs as a framework or concept that helps guide decisions about customer data architecture.
By focusing on your organization’s unique needs, use cases and capabilities — and not getting distracted by the myriad definitions of what a customer data platform “should” be — you can make informed decisions that drive real business value. Remember: Form follows function, and the best CDP is the one that fits your organization’s specific requirements.
Core Questions Around Customer Data Platforms
Editor’s note: Here are two important questions to ask about CDPs:
What are the main challenges organizations face when implementing a customer data platform?
Organizations often struggle with misaligned expectations, unrealistic goals and a lack of clarity on how CDPs should fit within their broader marketing technology stack. Many expect CDPs to be an all-in-one solution, which leads to disappointment when the platforms fail to meet complex, multifaceted needs. Additionally, the lack of internal preparedness and technical resources can hinder successful implementation.
How can organizations guarantee the successful implementation of a CDP?
Organizations should begin by clearly defining their use cases and complexity, assessing their technical capabilities and mapping out a strategy using frameworks like the 2×2 model. A tailored, modular approach — where components are selected based on specific business needs — will maximize a CDP’s potential.
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