5 Common CDP Challenges (And How To Overcome Them)

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Customer data platforms (CDPs) help you unify customer data silos and create a single source of truth for the entire organization. But the right CDP can do much more than create a 360-degree view of the customer, and it’s quickly becoming a key component of the marketing technology stack. 

Identifying the right CDP can be a challenge. According to the CDP Institute, there are over 161 CDP vendors, each with something different to offer. Knowing which CDP is right for your company requires understanding common CDP challenges, and what to look for to help you overcome them.

1. Inability to Scale

Can your CDP scale with your organizational goals? Some CDPs are designed to handle smaller datasets, so when you add more data as your company grows, or integrate more applications, you will see a degradation of processing speed. 

If the CDP can’t handle the amount of customer data you need to store and process, your organization’s IT team might need to integrate supplemental or redundant storage and processing. While this might not sound too bad, it means customizations that take time. You may miss opportunities because you can’t analyze the dataset as a whole, or you can’t analyze it in near real-time. 

Look for a CDP that can scale up and scale down as your requirements change without significant changes to the CDP’s data architecture. In addition, CDPs supporting larger datasets typically have more robust security and governance frameworks, a win for your compliance and data privacy requirements.

2. Demonstrating Time to Value To Slowly

There are many use cases for a CDP, but some provide a faster time to value than others. If you purchase a CDP with a plan to implement all your use cases at once, or focus on more complex ones right away, you will struggle to show the value of the implementation early.

You can do a few things to show the value of your CDP implementation early and have a roadmap outlining future plans.

  • First, document all your use cases and the resulting requirements for the CDP. This process requires that you have all your stakeholders from all departments involved from the beginning, regardless of which use cases you determine will go first. Without full stakeholder involvement, you may miss critical requirements and select a CDP that won’t meet all your needs.
  • Once you know your use cases, you need to decide which ones to prioritize. This decision depends on your business goals and how quickly you want to show value. Small projects with fewer data sources and target systems can be implemented quickly, and show value faster. As you start to demonstrate results, you can implement more use cases with additional data sources and systems. 

One suggestion from David Raab, founder of the CDP Institute, is to expand your use cases one department at a time. In other words, implement all the use cases for your marketing department, then move to your customer service department, and so on. This approach works because each department has its own set of data sources and types, and target systems. Multiple use cases from one department will use one or more of the same data sources and target systems. Of course, there is some overlap with other departments, but that means there will already be some things in place once you shift to working with the next department (thus potentially speeding up their use case implementations).

The key is to clearly outline your CDP implementation roadmap, so everyone knows what happens when. You’ll have quick wins to show value early, and a plan demonstrating your CDP’s long-term value.

 

3. Lack of Adoption From Non-Technical Users & Teams

If you’ve selected your CDP by involving all stakeholders in the purchase process, you’re on your way to ensuring everyone buys into the CDP. But adoption can still be challenging and ensuring that non-technical teams get training to use the CDP will be necessary.

Typically, IT does most of the work during a CDP implementation to ensure everything is done correctly. The right data sources are connected, the data is processed correctly, and the target systems are identified and connected.

But non-technical people need to be aware of how the CDP works and how to use it, and they need to be involved from the beginning to ensure success. That’s why identifying all use cases upfront is so important. The use cases will map out the campaigns and activities that rely on data and insights from the CDP. 

For example, many on your marketing team are not technical people, so while they may identify data sources and target systems, they might not be involved in connecting everything. To ensure their adoption of the CDP, show them features they can use early on, such as getting insights on the next-best action to take, looking for untapped markets, or potential upsell/cross-sell opportunities. 

Another way to increase adoption early is through low code/no-code tools. These tools enable non-technical users to create applications for their work quickly. Low code or no-code development platforms can be integrated with a CDP, giving non-technical users access to customer data. The right CDP will provide the security necessary to ensure only those people with the correct permissions can access the data.

The point is that the earlier you bring non-technical teams into the implementation process, the sooner they will see the value and start using the CDP.

Read More: So, You Have a Customer View. How Do You Get Marketers to Use It?

4. Difficulty Extracting Data Sources

A critical capability for a CDP is to extract data from source applications to store in the CDP’s data repository. That data can exist in structured, unstructured, and semi-structured formats. Therefore, the CDP needs to know how to connect to each source system, the type of data it’s ingesting, and how to deal with it once it’s ingested. 

In some instances, you might find yourself working with a CDP that requires a lot of manual effort and customization to connect to some source systems. Unfortunately, this means that IT will have a lot of work to do before you can start to use the CDP. 

Look for a CDP that provides connectors to your preferred source systems out-of-the-box, allowing seamless integration. The CDP should also be flexible enough to ingest all types of data and be schema-agnostic, meaning it stores raw, event-level data so that if changes to the source data structure occur, you won’t have to make changes in the CDP as well. 

5. A Lack of Analytics Capabilities

It’s not enough for a CDP to store your customer data. You also need to be able to analyze it and derive insights from it. But not all CDPs have analytics tools and capabilities, or they have some capabilities, but more advanced features like predictive analytics are missing. 

When you identify your use cases, you will have a good idea of the analytics capabilities you need to support them. But there may also be additional capabilities and tools you didn’t think of because you were sure what was available. It’s also hard to predict future needs as strategies, and business goals change over time.

Look for CDP that has embedded analytics and data visualization tools. Also, look at how the CDP leverages AI and machine learning for capabilities like predictive analytics. Finally, the CDP you choose should provide these capabilities for non-technical users. If you have to involve IT or a data scientist every time you want to create a new report or dashboard or define a new segment, it will slow down your team’s ability to take action.

So there you have it: five key challenges you may face when purchasing a customer data platform. These are critical challenges to watch for – preparing early and looking for specific capabilities in your CDP can help you overcome them.

Read More: How to Choose the Right CDP for You

CDP.com Staff
CDP.com Staff
The CDP.com staff has collaborated to deliver the latest information and insights on the customer data platform industry.
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