CDPs in Marketing: Redefining What’s Possible in Personalisation

CDPs in Context: The Rise of Hyper-Personalised, In-the-Moment Marketing

Today’s customers expect brands to know their preferences. They expect offers and communications that anticipate their needs. They expect tailored interactions that connect seamlessly across channels.

Brands that don’t meet these expectations don’t grow. Especially enterprise brands – B2C and B2B alike. This is where a CDP (or customer data platform) comes in.

What Do CDPs Do In Marketing?

A CDP is a software solution designed to aggregate customer data. It collects, organises, and manages data from multiple sources. The result is a detailed and unified view of each individual, which can be used to deliver relevant and engaging experiences.

When deployed strategically and configured correctly, a CDP informs decision-making (by humans and machines) and supplies data that supports highly targeted campaigns.

This all might seem a tall order for a single platform. But that’s just it: a CDP isn’t a standalone solution. The first solutions that hit the market might have been standalone, but today’s CDPs take a different shape. They might be packaged software that ships with all or most of the features you need, or an open ecosystem compiled using best-in-class tools, or a hybrid with core functionality and custom integrations.

Don’t worry; we’ll come back to this when we talk about CDP types. For now, think of a CDP as the central nervous system for customer data. Not the brain. CDPs aggregate data, making it actionable in the ‘marketing brain’ (journey optimiser or customer decisioning hub) and other tools or delivery channels.

Key features of a CDP

A lot of marketing tools have claimed to offer a ‘360° view’ or ‘single customer view’. Where they fell short – and where CDPs go the distance – is centralising all data types at the same time, making the data usable and accessible, and maintaining progressive profiles.

A good CDP will:

• • Ingest and combine structured, unstructured, and semi-structured data from your CRM, eCommerce platform, POS, mobile app, website, email, ERP, social media, offline touchpoints and other sources.
  • Stitch disparate data points and interactions into unified, unique and persistent profiles using “identity resolution” processes.
  • Provide insights for segmentation, campaign activation and customer journey orchestration.
  • Enrich profiles with additional information from third-party sources and direct interactions.
  • Ensure data privacy and compliance with global regulations via a governance layer.
  • Integrate with martech stacks, media platforms and adtech via APIs and pre-built connectors.
  • Democratise data so that marketing, sales, and support teams can access and use the information they need.
  • Minimise reliance on IT or developers through out-of-the-box integrations and user-friendly interfaces.

Some CDPs do some of this in real time. We’ll talk more about this in a future article. Scroll down to subscribe to our newsletter so you don’t miss it.

Where CDPs Fit In the Modern Tech Stack

It’s important to know that CDPs didn’t always do all these things. They’ve evolved in line with the rise of connected, omnichannel experiences.

You could argue they’ve driven that rise, at least in part. As vendors released more sophisticated features, marketers experimented and did more cool things, which their competitors wanted to copy using their martech, prompting the vendors to release more sophisticated features – you see where this is going.

The market for CDPs is forecast to grow by 39.5% annually between 2024 and 2030, to a staggering $51.95B (£42.56B). That’s more than 2x the growth rate forecast for the marketing automation platform market. Why are CDPs suddenly so important? The answer is that it’s not sudden.

CDPs have been around since at least 2013. What we’re seeing now is the convergence of several key factors that are driving widespread CDP adoption in the US. Europe and other regions are lagging behind but will likely catch up within this decade.

Why is all this important? Because it points to the essential nature of CDPs in a matured marketing ecosystem.

Customer Data is More Complex

Most businesses are drowning in customer data. Transactions, emails, behavioural analytics, website and app engagement, social media platforms, third-party sources – it’s a lot.
Our understanding of customer behaviour is also becoming more nuanced as algorithms get better at correlating previously unrelated signals. And data is more fragmented, with lines between touchpoints getting blurrier by the day.

CDPs are tasked with unifying all this information. They’re built to integrate with other systems, processes and tech, forming a hub around which your data ecosystem develops.
In our experience, a big driver of CDP investment is the ability to access and action customer insights in a way that’s efficient and drives business growth.

Data Privacy is Moving Mainstream

With GDPR, CPRA, HIPAA and other privacy regulations coming into force, a CDP that’s strong in compliance is a big help. In particular, for compliance and customer-centric data management in global organisations. Some are better than others in this area, so it’s worth adding compliance to your CDP assessment checklist.

New Tools Are Challenging Old Data Management Systems

We’re starting to see businesses leveraging CDPs to power AI-driven personalisation and predictive analytics. These advanced tools require a greater volume and diversity of data than ‘traditional’ systems offer.

Loyalty is More Valuable Than Ever

CDPs enable you to craft and launch more targeted, personalised and effective marketing strategies. And they help you analyse the outcomes. As such, they become indispensable for building lasting customer relationships.

Marketers Are Asked To Do More With Less

Marketing budgets shrank another 15% in 2025 to a measly 7.7% of company revenue. Although CDPs can be a significant investment, they can yield big returns. Efficiency gains, better personalised marketing, improved collaboration, less tech needed to analyse customer data. The ROI is there if you choose the right platform.

What Are The Different Types of CDP?

Depending on which source you consult, CDPs in marketing can be classified in dozens of different ways. For example, the CDP Institute divides the market into 4 categories based on core functionality. Gartner also defines 4 categories, combining organisational needs, CDP functionality, and tech stack flexibility. MarTech.org lists 10, dividing the field by focus area and use case.

Another way to categorise CDPs is by industry. Some have features that are better suited to fintech use cases than retail, for example. Zeotap is widely used by telcos, and Bloomreach excels in eCommerce.

You could also classify CDPs by architecture, like we mentioned earlier:

• Packaged or “closed” CDPs are standalone, pure-play solutions that ship with all core features. They tend to excel in one area, such as data unification or data activation.
• Composable, headless, or “open” CDPs integrate best-of-breed tools with a data warehouse, creating highly customisable data frameworks and workflows. Open CDP stacks are more flexible but also more technically finicky.
• Marketing cloud or “suite” CDPs are hybrid solutions typically offered by large vendors like Adobe and Salesforce. Core functionality is built on the vendor’s database and tightly integrated with its feature offering, with APIs and integrations for specific capabilities.

No classification system is better or worse than any other. It’s just a matter of perspective.

Ultimately, while it helps to be aware of how CDPs might be classified, we’d caution against getting too caught up in definitions. Every CDP in marketing has unique strengths, limitations, and applications, often resulting from its heritage. None will neatly fit just one category.

Platforms are evolving too fast, and there’s too much overlap. How we use CDPs is also changing, which in turn influences vendors’ development decisions.

Imagino and Zeta Global are good examples of pure-play CDPs expanding into orchestration. Braze, too (although Braze technically isn’t a CDP, which just shows how convoluted the conversation can become when you choose classifications as a starting point!).

A better place to start is with your organisation’s needs. 

This will help to define the vendor (suite/enterprise, open/headless, or closed/pure-play), core functionality, and additional features. It will at least narrow your shortlist from the 150+ vendors in the market to a handful with solutions that suit your needs

6 Ways a CDP Might Benefit Your Business

Collect and Manage Data From Multiple Sources

CDPs create a centralised hub for normalised, stitched-together customer data that’s continuously updated and accessible for marketing and analysis. A good CDP:

• • Collects first, second and third-party data
  • Combines data from known/unknown, online/offline, and behaviour/transactional sources
  • Consolidates identities across touchpoints
  • Continuously updates profiles with real-time data

An increasing crop of CDPs even use probabilistic ID matching to stitch anonymous website visits with known users.

Most businesses think they’re investing in CDPs to (re)gain oversight of their customers as individuals. That’s only partially the case in our experience. While the business challenge is customer intelligence, the value proposition lies in the ability to collect and collate data that can be used to make personalising omnichannel experiences easier.

Personalisation Beyond a Single Channel

CDPs are key enablers of personalised marketing at scale. They house a wealth of customer data to support personalised messaging, content, and recommendations in omnichannel journeys (compared to DMPs, which are largely single-channel). For example, a customer’s purchase history with one product line can be used to inform marketing for another. Or their website browsing behaviour can inform the offers they see in your app. Or a target account’s likelihood of conversion can be analysed from multiple angles. Or you can time an up-sell, after-sales, or cross-sell offer according to highly nuanced customer signals.

This doesn’t happen entirely within the CDP. Engagement and delivery platforms attached to the CDP do the implementation part. But they can’t do it without accurate, up-to-date data supplied by an integrated CDP.

Breaking Down Data Silos

CDPs are great for breaking down information siloes. They create a shared services-style foundation for customer data. For example, we’ve used CDPs to unify marketing and sales teams’ data in globally diverse organisations.

Naturally, this helps both teams individually access better customer insights. But maybe more importantly, it helps them collaborate to drive business goals. This is where you start to see the importance of tech, processes, team structure, and data all working in sync.

Efficient and Effective Operations

A good CDP eliminates (or at least reduces) the need to build bulky custom integrations between your customer data warehouse and delivery platforms. Provided the data handling processes are configured properly, this can significantly reduce errors, bottlenecks, and blockages in your data pipeline. Basically, there is less stuff that can break.

There’s a big flow-on benefit here in freeing up marketers’ time to focus on creative, value-added, big-picture work. Or take a day off – wouldn’t that be nice!

Compliance and Governance As Your Business Grows

Underpinning all this is a governance layer for compliance with privacy and data usage requirements. The right CDP, combined with a good data management strategy, helps maintain adherence to data privacy regulations as your customer base grows. It does this in a few ways:

• • Manage data usage permissions between martech platforms.
  • Track consent and communication preferences in real time.
  • Safeguarding customer information in robust security frameworks.

If you’re concerned about GDPR, HIPAA, CPRA, or any of the other myriad privacy regulations rolling out, this governance layer is essential for compliance as your business grows.

CDP vs CRM vs Data Warehouse: A Quick Comparison

Product	Customer Data Platform (CDP)	Customer Relationship Management (CRM)	Data Warehouse
Purpose	Unifies and activates customer data for insights and personalised marketing.	Manages customer interactions and relationships.	Houses data for reporting and analysis.
Data Sources	Collects data from all online and offline touchpoints.	Uses data generated from customer interactions.	Aggregates data from various internal and external sources (customer and non-customer).
Data Structure	Creates unified customer profiles with real-time updates.	Stores structured data related to customer accounts and interactions.	Stores structured and semi-structured data for analysis.
Real-Time Processing	Supports real-time data processing for immediate insights.	Generally not focused on real-time data; more transactional.	Typically processes data in batch mode, not in real-time.
User Base	Used by marketing and sales teams for campaign management and customer insights.	Used by sales, marketing, and support teams to manage relationships.	Used by analysts and business intelligence teams for reporting and decision-making.
Integration	Integrates with various marketing tools and platforms for data activation.	Integrates with sales and marketing tools but has limited third-party integration capabilities.	Integrates with BI tools for analytics but may require additional ETL processes for data access.

The Importance of Integration

Standalone CDPs and marketing automation tools all have their individual benefits. But their value is amplified in an integrated ecosystem. We’ve touched on this a couple of times. Still, it’s worth spelling out in detail because it influences your approach to CDP implementation.

It’s not enough to buy a CDP. They can’t execute campaigns on their own. They need to work with other tools.

Similarly, marketing automation tools can perform the tasks that take up your time. But you’ll struggle to get the benefits of personalisation at scale, progressive customer journeys, or updated customer intelligence without a CDP. The best-case scenario is standardised, pre-planned workflows.

Choosing the Right CDP for Your Business

A CDP is likely to be a significant investment. Careful planning and evaluation are essential to maximise the value you get back. This goes beyond technical considerations; process, organisation, and governance all feed into your decision.

Phase 1: Discovery

• Identify your overarching goals: What are you trying to achieve with a CDP? E.g. increased customer lifetime value, improved conversion rates, enhanced customer experience, more effective personalisation?
• Establish KPIs: How will you measure progress towards those goals? Don’t skip this step; you’ll need it later to assess whether your investment is paying off.
• Understand your customer landscape: Map all your existing data sources and analyse their quality, accessibility, and security controls. Identify gaps that a CDP can help bridge.
• Define use cases: What specific marketing activities will the CDP support? Which channels and third-party audience platforms will it need to connect to? Prioritise the most important use cases so you have a place to start.

Phase 1.5: Key Requirements

Based on your goals, data landscape, and use cases, define your must-have CDP features. This might include, among many other possible features:

• Open, closed, or hybrid architecture
• Real-time data processing
• Identity resolution
• Data cleansing
• Integration capabilities
• AI functionality
• Compliance tools
• Segmentation and targeting
• Analytics and reporting
• User-friendly interface

Phase 2: Evaluating CDP Vendors

When you start to research potential CDP vendors, you will probably notice that they all promise to exceed your defined requirements. To be fair, this could be true for many or most.

However, in our experience, your business will have unique considerations that require practical expertise and a strategic approach to match the right platform. We’ve seen more than one instance of a company investing heavily in new tech, only to learn that the features and functionality they needed actually aren’t compatible.

By all means, build a shortlist. Request platform demos. Talk to vendors. However, we strongly advise enlisting the help of a tech-agnostic CDP consultant who can translate your requirements to the vendor’s offering (and vice versa).

Phase 3: Organisational Readiness and Implementation

• Internal skills: Is your team comfortable using the CDP? What training will be required?
• External support: Do you need extra hands during planning, training, or implementation?
• Data ownership: Who will “own” the CDP? Who is responsible for managing the data within it?
• Change management: How will you manage the change within your organisation? How will you communicate the benefits of the CDP to different teams?
• Internal processes: Do any internal processes or team structures need to be updated, or interdepartmental interfaces created to accommodate the CDP?

Phase 3.5: Implementation Plan

Alongside the work you’re doing to prepare your team and colleagues, consider what you need to actually implement the thing:

• Realistic timeline
• Dependent and interfering projects
• Required resources
• Data migration
• Platform integrations
• Team training

This is getting to the pointy end. Now, we’re ready to test the CDP in real-world scenarios. We always recommend a phased implementation. That means moving or redeveloping processes and workflows one by one to the CDP.

Although this means hanging onto legacy platforms for longer than you might like, it ensures that customers don’t experience any disruption and data isn’t lost or compromised in the transition.

Phase 4: Ongoing Management and Optimisation

In most cases, a CDP is the enabler of long-term growth and continuous improvement. That means implementation is closer to the start of the process than the end. Go back to the KPIs you set in Phase 1. Use them to monitor the CDP’s performance and usage; this can be tricky because measurement usually involves multiple interconnected platforms and processes.

Watch for areas where you can improve or adjust. That might be training your team, reworking data processes, reconfiguring integrations, or adding functionality to enhance customer intelligence.

It’s never-ending. But not open-ended. Always use your strategic goals as guardrails to prevent scope creep, and as yardsticks to measure success.

As your customer base and business grow, continually check in with those goals to ensure you’re always moving in the right direction.