Key features of Customer Data Platforms (CDPs)

A Customer Data Platform (CDP) aggregates and organises data from multiple sources to provide a 360° customer view. It enables sales, marketing, support and product teams to fully leverage customer data and deliver a personalised experience.

Since their emergence in 2013, two main approaches have developed. On one hand, packaged or traditional CDPs are all-in-one but lack flexibility. On the other hand, composable CDPs plug directly into your existing data architecture.

The pressure is high for brands: purchase journeys are fragmented across online and offline channels, and data is scattered. Consumers expect consistent interactions at every touchpoint, while marketers can no longer rely on third-party cookies.

Whether packaged or composable, all CDPs share a set of essential features. Understanding CDP features means understanding how to build the foundation for an effective and sustainable customer strategy.

👉 What are the must-have features of a Customer Data Platform? Discover the different technical approaches to help you make the best choice based on your specific needs.

A Customer Data Platform fulfils three main missions: 

Event tracking: 

A Customer Data Platform centralises data from every touchpoint, both physical and digital.

On a website or mobile app, this is achieved through event tracking, allowing you to track specific actions: clicks, page views, sign-ups, basket additions, purchases, etc.

This data complements information from the CRM, support tools, or points of sale. The CDP interfaces with all these tools to retrieve this data.

Depending on the architecture, a customer data platform API can connect these sources and destinations while managing flow reliability, security and scale.

Data hosting: 

Where do you want to store and centralise your data? Options include public cloud, private cloud, or on-premise.

Depending on whether you choose a traditional or a composable CDP, data hosting follows two different approaches:

By reconciling the data into an identity graph, the goal is to build a 360° customer profile, essential for understanding the entire customer journey. This is the focus of the next steps.

Transformation and aggregation: 

Once identified and collected, the first step is to clean, standardise and enrich the data. In other words, transform it to make it usable for analysis and activation.

This is the role of ETL (Extract, Transform, Load) or ELT (Extract, Load, Transform) processes. They standardise formats, remove duplicates and ensure data quality. Data encryption and anonymisation further enhance regulatory compliance.

Identity resolution: 

Identity resolution is the core capability of a CDP.

It links all identifiers of a single customer (whether anonymous on desktop, logged in via mobile or recognised in-store) to create a single, usable profile for operational teams.

This Customer 360° view supports personalised experiences and coherent messaging throughout the journey.

Data modelling: 

A data model maps relationships between data. It acts as an abstraction layer that makes it easier to interpret and exploit business activity.

Unlike traditional CDP data models, which are more rigid, composable CDP models provide businesses with greater flexibility during implementation.

💡 At DinMo, the Knowledge Store is the underlying layer responsible for enhancing data representation. It powers the no-code functionalities of our composable CDP used by business teams.

Data enrichment: 

Models can be enhanced using scoring rules or AI-based algorithms to estimate purchase probability, churn risk, or Customer Lifetime Value (CLV).

Data enrichment features provide valuable insights for the personalisation and prioritisation of marketing actions. Some platforms also allow enrichment with third-party data.

Dynamic segmentation: 

Precise audience segmentation is the foundation of effective personalisation. A CDP lets you create simple or advanced segments by combining multiple criteria: purchase behaviour, churn risk, location, last interaction date, etc.

DinMo offers a no-code Segment Builder that allows marketing teams to create relevant audiences themselves. Its advantages:

This approach supports the implementation of more effective activations.

Omnichannel activation and personalisation: 

Once the segments have been defined, the activation phase involves taking action to harness the full power of your data. Using Reverse ETL, the CDP sends enriched data to tools used by business teams.

This mainly includes the CRM, advertising platforms, engagement solutions (email, push notifications, SMS), as well as support or personalisation tools.

This synchronisation enables targeted campaigns to be triggered across all channels: re-engaging an abandoned basket, personalised messages on a customer account, special offers via ad campaigns, or push notifications.

Conversion optimisation and scalability:

A high-performing CDP makes it possible to orchestrate complex marketing scenarios across multiple channels, addressing hundreds of thousands or even millions of customers. This large-scale marketing automation relies on a flexible and scalable architecture.

It should also allow rapid measurement of campaign effectiveness using key performance indicators (KPIs): Customer Lifetime Value, conversion rate, or retention rate.

The platform must integrate easily with the rest of your stack: analytics tools, CRM systems, advertising platforms, or data warehouses. This interoperability ensures the efficiency of marketing operations.

Data security is therefore a key consideration when implementing a Customer Data Platform project. This involves encrypting sensitive information and clearly managing access and usage rules.

CDPs must also ensure compliance with current regulations such as the GDPR or CCPA. A composable CDP offers greater control by relying on the existing data architecture.

A composable CDP integrates directly into a company’s data architecture. Unlike traditional platforms, it does not duplicate data to build its own database.

Instead, it reads data directly from the data warehouse: this is known as a zero-copy architecture.

This seamless connection to existing infrastructure allows you to quickly implement use cases without moving any data.

Other key strengths of DinMo include:

Faster to deploy and more cost-effective, a composable CDP builds on your data infrastructure following a Best of Breed approach. It is designed to scale with your business, adapting to the needs of operational teams.

A CDP supports numerous use cases across marketing, sales, support, and product teams. Here are two of the most common examples of marketing activation in action:

A CDP allows you to target audiences with precision, based on their needs or behaviours: recent purchases, browsing history, churn risk, etc. Segments are updated in real-time.

This enables you to tailor your campaigns based on context, channel, or customer value. This approach ensures higher open rates, an improved customer experience, and increased conversions.

The CDP feeds your advertising channels with precise, qualified audiences directly from the data warehouse. Using the Reverse ETL process, you can activate these segments on platforms such as Meta Ads, Google Ads, or TikTok Ads, and share your first-party data with conversion APIs.

This helps reduce advertising costs while increasing message relevance.

💡 Interflora has been using DinMo since 2023, synchronising 70 unique audiences daily to power omnichannel activations. The results: a 5% increase in net margin at the group level and a 17% reduction in average CPC.

👉 To explore further, read our Interflora customer case study.

A Customer Data Platform should align with your business objectives. Before getting started, ask the right questions based on your technical infrastructure and commercial priorities.

👉 Use these criteria as a guide for drafting your RFP.

Today, data is scattered, customer journeys are fragmented, and expectations are higher than ever. To address these challenges, a CDP helps you regain control: collect, unify, and activate your data to deliver a more consistent and personalised customer experience.

Choosing a Customer Data Platform goes far beyond ticking off a list of features: it’s about laying the foundations for your data-driven marketing strategy.

Composable CDPs pave the way for a more flexible, cost-effective approach that fits within a modern data stack. Whatever solution you choose, keep your use cases top of mind and prioritise adoption by your teams.

💡 Need help defining your priorities and comparing solutions? Get in touch!