Thought Leadership

Getting value out of a CDP: The first use case

Recently NGDATA was the CDP Institute’s guest for a webinar on how to get the most out of your Customer Data Platform (CDP). How do you pick the right one? And what do you need to consider once you have chosen a CDP? This pre-phase merits some reflection to make sure your customer-centric program generates momentum from the start and maintains it. Here are some requirements to take into consideration in order to gain value from your CDP.

How to get started with a CDP

Any big data project can be complex, especially when you’re trying to boil the ocean before you have a cup of tea. Our advice is to first see what data should be connected in the initial phase. Analyze what experiences affect most of your customers and determine which changes will result in the most value. Start with a limited use case that can actually drive out value quickly so that you’re not stuck in a position where you can’t evaluate how a project is going until it’s been running for quite some time.

Another implementation challenge that may appear is that your processes aren’t ready for it. One of the big benefits of a CDP is that you can respond rapidly to your customers. The models you’re building need to take into account customer behavior, but this requires business lines to come together. The organizational mindset needs to follow, so it is very important to shift from product-centric to customer-centric in messaging and in how you’re going to deploy that messaging. Accessing the customer data might be new to certain departments in your organization, and those are usually not beating down doors to use the CDP data, even though there’s a huge amount of value to that data. However, internal process management can overcome that challenge when making sure your own people are aligned around the idea of becoming customer-centric from the ground up.

The lack of an integration framework or the organization’s unwillingness to commit to one will never give you the results you were hoping for.

Scalability, usability, integration

Keep the technical aspects also in mind when choosing a CDP and think of the platform’s capability to scale, use, and integrate.


Many organizations have huge data sets, so really being able to scale horizontally is incredibly important as more data is being added to the platform.


From a usability perspective, any platform can outline features and market them in a way that tells their clients they need a variety of use cases, while the platform itself isn’t actually usable by the people who will be operating it besides the data scientist. So then you won’t get the platform adoption that you really need to scale.


The integration part is incredibly important. Picking a CDP that has that fully baked-out integration framework, both on the frontend and backend, is really vital to success. You will need to connect with standard and bespoke source and execution systems and you will add more or change them over time. The lack of an integration framework or the organization’s unwillingness to commit to one will never give you the results you were hoping for. Make sure you can ingest your data quickly into the platform in real-time or batch, but also integrate it with a variety of enterprise sources. And on the execution front, having a CDP that connects to an array of channels and social media outlets is also very viable. It is not just about the integration itself but also about managing and monitoring the dataflows that necessitate a framework.

Start simple. Choose a use case that requires limited in- and outputs, as this is how you’ll get value a lot faster.

How to select your first CDP use case

Start simple. Choose a use case that requires limited in- and outputs, as this is how you’ll get value a lot faster. Think of a concrete challenge your customer is facing today, such as the onboarding process or when making a payment.

Another way to select in- and outbound channels is where most of your customers reside: Do most of your customers contact you through their mobile app or on desktop, versus do most of your customers contact a call center or have calls with an outbound agent? Figure out which in- or outbound channel to align with first to reach most of your customers.

Something else to consider is what metrics you need to influence rapidly. Do you need more revenue this year? More online customers? Or are you more moving towards something that’s long-term like increasing customer satisfaction or NPS? Determine which metrics you want to move pretty quickly, and come up with a use case that influences that metric with the least number of inputs and outputs. For instance, when a bank wants to look at credit card utilization, they could start by just looking at the credit card transactions and the mobile app. Later, they can add the customer’s web behavior to analyze, but they can start to move the needle with that limited set.

Organizations typically want to tackle the big problems first, such as reducing churn or addressing larger customer life-cycle challenges. The issue with these problems is that they require multiple historical data sources. These organizations must take a data-first approach and determine what the common denominators are. Start by ranking your use cases and finding sources that are easily obtained and common to many of your questions. Digital data, for instance, is a great example of channel data that is easy to source with tag management software but also included in many use cases. As you rank your use cases, keeping scalability and integration in mind will help with stakeholder alignment as you partner to build out their ever-evolving KPIs.


It’s not enough to just start with whichever projects require the least work. You must also select projects that lay a foundation for future growth. This means rejecting shortcuts that cannot easily be expanded or maintained over time, such as hard-coded connections between systems. Next, you need to assess which data and systems integrations will be reused. The goal is to develop a sequence where each new integration supports a new use case and shortens the path to future use cases. Similarly, you’ll want to add processes, analytical tools, and user skills that incrementally expand the range of what’s possible.

Want to get more advice on how to start and are you curious to hear which use cases we can suggest based on your industry?

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