How To Define Customer Data Platform Use Cases [2026 Update]

Use Cases: The First Step In Martech Investment

Customer Data Platforms (CDPs) have been the hot martech for years. So why is utilisation still in the doldrums?

One reason (among many) is that organisations buy new platforms without defining their customer data platform use cases up front. They get excited by features and forget to ask one all-important question: What is a CDP used for?

Another way to phrase the question is: What value will this platform bring to my customers and my business?

Just 22% of marketers reported high CDP utilisation. That’s up from 17% in 2024, but still below the across-the-board estimate of 33%.

Source: Gartner, 2025 Magic Quadrant for CDPs report.

Two Views On Customer Data Platform Use Cases

CDPs Have One Job

A CDP’s main job has historically been to build unified customer profiles and provide useful data. CDPs receive data from all your customer touchpoints and interactions, and compile one neat, reliable picture of each customer*.

So, it’s no surprise that data assembly is the most common CDP use case. It’s arguably the only use case if we’re talking about pure-play CDPs.

The thing they’re designed to do is collect and standardise customer data to create a single source of truth; a unified, persistent, and complete customer record.

But there are two things you need to know to understand customer data platform use cases today:

1. CDPs are evolving: Embedded and composable CDPs are increasingly common, meaining CDP capability sits alongside or on top of a data lakehouse or engagement platform. Even standalone SaaS CDPs have functionality beyond data assembly, like warehouse integration.
2. CDPs never exist in isolation: They provide usable data to other platforms (engagement, analytics, journey orchestration, ad markets) through APIs and custom integrations. Increasingly, CDP functionality is being split up across these platforms.

Most marketers implementing a CDP are looking to bridge a customer understanding gap. They’re investing in that data assembly functionality to create a unified view of customers.

However, as CDPs simultaneously evolve and fragment across the tech stack, their use case inevitably crosses into the territory of other martech:

• Enabling real-time customer experiences: Minimising delays between behaviour, data ingestion, and action.
• Journey orchestration: Sending actionable data to orchestration tools for smooth omnichannel experiences.
• Outbound campaigns: Providing the data for targeted marketing campaigns.
• Analytics: Furnishing analytics and measurement tools with clean, structured data.
• Activation (especially personalisation): Making customer data accessible and usable across various marketing and customer engagement platforms.

To be clear, the primary — and arguably sole — CDP use case is still data assembly. But we can’t ignore that the lines are blurring as standalone CDPs give way to embedded and composable functionality.

CDPs were originally like a universal adapter or dumb waiter for customer data. They collected information from incoming sources and the database, assembled it into a single customer view, and made that available to activation platforms.

Neil Hughes, Marketing Solutions Director

CDPs Must Deliver Against Business Goals

Let’s flip the question. Why is data assembly important?

In most cases, the answer is “to get a better understanding of our customers”. This shifts the focus from capability use cases to business goal use cases.

With a clearer understanding of customer behaviour and preferences, marketers – and marketing – become more effective. The most common goal-oriented customer data platform use cases revolve around existing customers:

• Customer value: Combining purchase history with behavioural insights to identify cross- and up-selling opportunities.
• Retention: Standardising data across purchase history, engagement, and other signals, making it easier to identify customers at risk of churning.

There are other use cases that tend to be secondary:

• Acquisition: Using lookalike modelling or pushing audiences into digital ad platforms.
• Awareness: Usually a side-effect or a step towards acquisition; CDPs can support awareness campaigns, but it’s never the main event.
• Expense reduction: By improving data quality and automating processes, CDPs can help reduce wasted spend and manual work.

Vendors do a great job promoting features, and it’s easy for marketing teams to get swept up in the excitement. But licenses are being purchased before there’s a clear understanding of how these tools align with business strategy, deliver ROI or drive long-term growth. This isn’t just a CDP issue. It’s widespread across martech. If a tool doesn’t support measurable outcomes or scalable value, then it’s technology for technology’s sake.

Thomas Fordham, Co-Founder and CSO

Blurred Lines: The State of CDPs in 2026

Globally, the CDP market is projected to grow by roughly 4x between 2024 and 2028, to over £21B ($28B).

While much of that growth will come from established players expanding into new markets, a good chunk will come from emerging platforms that break the traditional mould of data assembly platforms.

Gartner’s prediction for 2028 is that the data management markets (including storage, management, activation, analysis, and compliance) will converge into a single market enabled by AI and data fabric. This was reiterated in the 2026 Magic Quadrant for CDPs report, which was all about – you guessed it – preparing for agentic AI.

“CDP” as a product category could even cease to exist as data collection and identity resolution become standard in data solutions and engagement platforms.

All of this begs the question: What is a CDP used for in 2026?

What Is a CDP Really Used For?

The CDP’s core function hasn’t changed. It collates data and resolves customer profiles. In that sense, it remain a vital bit of tech as the typical customer journey becomes incomprehensibly fragmented and seemingly totally random.

What has changed, when you take a broader view of the market, is where that function lives:

• In a standalone CDP with a single function
• In a composable CDP that layers on top of an engagement platform or data lakehouse
• Embedded into a data lakehouse as CDP capability rather than a separate platform

Still, if you Google “customer data platform use cases,” you’ll find lists of 5-10 use cases. Most start with customer understanding before veering off into personalisation at scale, customer journey tracking, marketing process automation, and even omnichannel engagement.

These aren’t CDP use cases. What they are is a reflection of the confusion around CDPs as the market moves beyond standalone SaaS solutions into the “platformisation” era.

Some vendors are adding non-standard CDP features like customer engagement or decisioning. Engagement, analytics, reporting, tracking, outreach, and orchestration are all common in modern “CDPs”.

Others are shipping engagement platforms with identity resolution baked in, and not calling it a CDP at all.

You should ignore all this noise. Don’t let vendors oversell you on the art of the possible, and don’t be tempted to purchase an expensive licence just because a competitor has it.

Put your business requirements first – which is to say, your customers’ requirements. If you don’t know them well enough to gradually scale up personalisation efforts, you likely need some kind of identity resolution solution. That might be a standalone CDP, a composable stack, or functionality embedded into your existing data layer.

Or it might mean a rethink of your processes and workflows.

There is arguably a stronger business case for data assembly than ever. The trouble our clients are facing is that CDP vendors promise they’ll do the job and play well with other platforms, but that’s increasingly turning out not to be true. We’re seeing a shake-up of contract decisions, with more brands choosing monthly or PAYG over multi-year contracts.

Neil Hughes

Curveball: Do You Actually Need a CDP?

Interrogating your requirements could also lead you to realise that a CDP isn’t the right fit. Maybe you have a decent data warehouse with unused identity resolution features. Maybe your organisational processes are the real marketing efficiency roadblock. Maybe you’re mixing up analytics with customer understanding.

There’s no doubt that a CDP aligned with business goals will usually deliver strong ROI. Up to 800% in some cases, and 79% of new adopters see ROI within 12 months.

Still, your requirements should be the basis for martech investments. Not industry hype or flashy features.

It’s worth spending a little extra time to determine whether a CDP is the best solution. It could mean saving a lot of money on martech you won’t use.

What Happens When You Nail the Customer Data Platform Use Case Question

Our client Vertu Motors is a prime example of why customer data platform use cases matter. The company tried and failed twice to implement a CDP. The reason? They’d bought a licence without clarifying what the tech would be used for.

It was a costly lesson. Before the third attempt, Vertu did the work to clarify a series of use cases that would ease the customer journey and provide a better experience.

It all started with the need for a single customer view. In other words, data assembly.

Once Vertu’s team had a better understanding of the 4M+ individuals in their database, they could move on to the next use cases:

• Re-engaging customers who didn’t complete a car service booking.
• Optimising ad spending by suppressing people who purchased recently.
• Increasing campaign throughput without adding to headcount or staff hours.

Vertu rolled out the first CDP-enabled activities in December 2024. In January 2025, they made enough profit to cover the entire cost of the CDP project. If that doesn’t demonstrate the power of purpose in CDP projects, nothing does.

What This All Means For Your CDP Project

In essence, successful CDP projects hinge on clearly defining why you need one in the first place. That definition will always involve assembling data to better understand your customers as individuals.

When you start by clearly defining your customer data platform use case, you focus on the business benefits of establishing a robust data assembly process. Whatever comes next – real-time interactions, orchestrated customer journeys, targeted outbound campaigns, personalisation at scale – can only function with that foundation in place.

By prioritising clarity of purpose over flashy features, you’ll not only ensure a more successful CDP implementation but also unlock the true potential of your customer data to drive tangible business growth.