
Key features of Customer Data Platforms (CDPs)
8min • Last updated on Jul 11, 2025

Olivier Renard
Content & SEO Manager
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 the one hand, packaged or traditional CDPs, all-in-one but lacking flexibility. On the other hand, composable CDPs, which 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 of an effective and sustainable customer strategy.
Key takeaways:
A Customer Data Platform unifies data from traditional (stores, customer service) and digital (websites, mobile apps, social media, analytics tools) channels.
Its features are numerous and serve three main objectives: data collection and centralisation, management and modelling, then omnichannel activation.
A composable CDP integrates with your existing data stack (data warehouse, CRM, ad tools, etc.), offering greater flexibility, control and scalability.
Your CDP choice depends not only on functional and budget criteria, but also on how well it can adapt to your technical stack and business use cases.
👉 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.
The essential features of a CDP
A Customer Data Platform fulfils three main missions:
Collecting data,
Organising it into unified profiles,
Activating it across all channels.

Schematic diagram of a CDP
1️⃣ Data collection, centralisation and hosting
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 it.
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 will follow two different approaches:
A traditional CDP (or packaged CDP) duplicates your data by copying it into its own infrastructure.
A composable CDP relies on your existing data warehouse, avoiding duplication and ensuring secure, scalable hosting.

Traditional CDPs duplicate data, negating the concept of "Single Source of Truth"
By reconciling the data into an identity graph, the goal is to create a 360° customer profile, essential for understanding the entire customer journey. C’est tout l’enjeu des prochaines étapes.
2️⃣ Data management and customer profile unification
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.
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:
This is the core of the engine. Identity resolution is one of a CDP’s key features.
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.

Customer 360 components
Data modelling:
A data model maps relationships between information. 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 invisible 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 personalisation and prioritisation of marketing actions. Some platforms also allow enrichment with third-party data.
3️⃣ Audience segmentation and omnichannel activation
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:
Greater autonomy: there’s no longer any need to submit requests via support tickets,
Significant time savings for data teams,
More agility: segments are dynamic and based on reliable, up-to-date data.
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 (emailing, 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 quick measurement of campaign effectiveness using key performance indicators (KPIs): Customer Lifetime Value, conversion rate, or retention rate.

Features of a Customer Data Platform
Governance, compliance, interoperability
The platform must integrate easily with the rest of your stack: analytics tools, CRM systems, advertising platforms, or data warehouses. This interoperability ensures the smoothness and 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.
The composable CDP: a modular, secure and flexible approach
A composable CDP integrates directly into the 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.
Our composable CDP is natively compatible with major cloud data warehouses (Google BigQuery, Snowflake, Databricks, Amazon Redshift) and any PostgreSQL database.
This seamless connection to existing infrastructure allows you to quickly implement use cases without moving any data.
Other key strengths of DinMo include:
No-code logic: marketing teams can independently create segments and launch targeted campaigns.
Calculated fields functionality: generate custom fields from your existing data.
Observability: receive alerts in the event of errors and anticipate the impact before any data is deleted.
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.
Main use cases
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:
Personalised CRM retargeting
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. The result: higher open rates, an improved customer experience, and increased conversions.
Advertising campaign optimisation
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 group level and a 17% reduction in average CPC.
👉 To explore further, read our Interflora customer case study.

Interflora x DinMo Customer Case Study
How to choose your CDP?
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.
Start by identifying your key use cases: data centralisation, profile unification, segmentation, marketing activation… What are your primary communication channels? Which tools do you use on a daily basis?
Define your hosting preferences: do you want your data to be hosted within the CDP, or stored within your own environment?
Check ease of use: the platform’s user experience is also a crucial factor. A no-code interface will empower marketing teams to work autonomously. Ensure compatibility with your data warehouse, CRM, and analytics tools.
Assess deployment time: some CDPs require several months to implement. A composable solution can enable you to launch your first use cases within just a few minutes.
Consider your specific requirements: support, budget, compliance, scalability, partner ecosystem. Take time to evaluate every aspect before making a final decision.
👉 These criteria should guide the drafting of your RFP.
Conclusion
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 front of mind and prioritise adoption by your teams.
💡 Need help defining your priorities and comparing solutions? Get in touch!
FAQ
How long does it take to implement a CDP?
How long does it take to implement a CDP?
The implementation timeline depends on the solution you choose.
A packaged CDP generally requires several weeks or even months of setup, involving complex data import procedures.
In contrast, a composable CDP can be up and running in just a few hours. It integrates directly into your existing infrastructure and enables you to launch your first use cases quickly, without disrupting your current setup.
What types of data can a CDP collect?
What types of data can a CDP collect?
A CDP collects and centralises data from your online channels (website, mobile app, social media, email campaigns) as well as offline channels (stores, customer service, call centres).
It supports behavioural, transactional, CRM, and analytics data. The goal is to unify all relevant information needed to understand the customer journey.
Which KPIs should you track to measure a CDP’s effectiveness?
Which KPIs should you track to measure a CDP’s effectiveness?
Several indicators help assess a CDP’s performance:
- Campaign conversion rate
- Customer Lifetime Value (LTV)
- Cost per acquisition (CPA) and cost per click (CPC)
- Retention rate or churn rate
These KPIs should be tracked regularly to guide marketing actions and fine-tune your segments or activation channels.