Customer Data Platform: setting the strategic foundations for Customer 360°

Successful marketing depends on understanding that the customer is king. In today's digital landscape, personalisation is key to meet the demands of consumers who expect tailored experiences. To achieve this, businesses need access to rich, real-time customer data, which is where a Customer Data Platform comes in. It gathers and processes data from various sources to provide a 360° view of the customer, enabling businesses to analyse behavior, predict needs, and deliver personalised experiences that meet customer expectations.

What is a Customer Data Platform?

A Customer Data Platform (CDP) is a solution designed to centralise customer data from various sources to enable omni-channel activation. It offers model flexibility, real-time actionable capabilities, and is typically managed through a user interface.

5 Reasons why Your Company Should Consider a CDP

Benefits of a Customer Data Platform

A Customer Data Platform offers a centralised platform for businesses to collect, process, and act on customer data. By leveraging advanced analytics and automation, businesses can derive insights, create personalised marketing campaigns, streamline marketing operations, and comply with data privacy regulations. A CDP is a powerful tool for businesses looking to enhance their customer data management capabilities and take their marketing to the next level.

Intelligence Interface

360° View of Your Customer

A Customer Data Platform collects real-time data from various sources and builds a single customer profile, providing a comprehensive view of the customer's journey, behavior, preferences and interests. This allows businesses to understand their customers better and make more informed decisions.


Customer Data Protection

A Customer Data Platform provides a secure and trustworthy foundation for building relationships with customers by leveraging customer consent and identifying customer preferences within a single platform. This helps protect customer data and ensures compliance with data protection regulations.


Advanced Analytics

A Customer Data Platform provides tools to measure and optimise campaigns based on real-time data. With the help of advanced analytics and machine learning techniques, businesses can gain insights into customer behavior, preferences and interests, and use them to improve their marketing strategies and ROI.


Accurate Segmentation and Targeting

By providing a deep understanding of customers’ behavior, preferences, and interests, a Customer Data Platform can assist businesses in creating targeted and personalised marketing campaigns that are more likely to be effective and drive revenue growth.


Enhanced Campaign Performance

A Customer Data Platform can optimise marketing campaigns by analysing customer data and making data-driven decisions to improve campaign performance, such as adjusting targeting, messaging, and offers.


Omni-Channel Campaign Optimisation

A Customer Data Platform offers a single, unified platform to create and deliver personalised marketing campaigns across multiple channels, such as email, social media, and web, which results in seamless customer experience across all channels.

Use Cases

A Customer Data Platform offers a multitude of possibilities and applications due to its capacity to bring together customer data from various sources. Nevertheless, when choosing a CDP solution, it's crucial to prioritise the business goals instead of solely considering the technological features offered by different vendors. Given that a CDP allows businesses to make data-driven decisions, the list of possible use cases is extensive. Here are a few examples.

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  • Enhancing value for businesses



    Segmentation is a key CDP use case to centralise customer segmentation. It can segment customers into different groups based on their characteristics and behavior, which can be used to target marketing efforts.

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    Churn prediction

    Churn prediction

    CDP can analyse customer data in order to predict which customers are at risk of churning, for example canceling their service or subscription. This information can be used to create retention campaigns and to identify areas for companies to improve its customer service.

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    Service center optimisation

    Service center optimisation

    CDPs can analyse customer service data, such as call logs and email transcripts, to understand customer issues and needs. This information can be used to optimise service center operations and improve the overall customer experience.

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    CDP can be used to personalise omni-channel with the use of profile attributes such as demographics and customer behavior. A variety of vendors even offer next best action and/or offer capabilities as part of their CDP solution.

A key benefit of using a Customer Data Platform is its capacity to bring together customer data from multiple sources and present it as a single, 360° view. This allows for real-time personalisation and omnichannel marketing efforts, which is more advanced compared to what a CRM or Data Warehouse can offer. With a Customer Data Platform, marketers can access a complete profile of each customer, enabling them to deliver more targeted and effective marketing campaigns and enhance the overall customer experience.

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The Key Advantage of a Customer Data Platform over CRM and a Data Warehouse

A key benefit of using a Customer Data Platform is its capacity to bring together customer data from multiple sources and present it as a single, 360° view. This allows for real-time personalisation and omnichannel marketing efforts, which is more advanced compared to what a CRM or Data Warehouse can offer. With a Customer Data Platform, marketers can access a complete profile of each customer, enabling them to deliver more targeted and effective marketing campaigns and enhance the overall customer experience.

Our Methodology

Our Customer Data Platform implementation methodology involves four stages executed in an agile, use case-driven approach.

1. The first stage is Intake, which includes a high-level business and ecosystem review to identify the current situation and future goals.
2. In the second stage, Analysis, we perform detailed analysis and create a roadmap of prioritised use cases, while examining key stakeholders such as data sources and their quality and content.
3. The third stage is Implementation, where we execute the prioritised use cases, data load, and channel set-up in an agile manner.
4. Finally, in the Evaluation and Iteration stage, we regularly assess performance, track success, evaluate data quality, and improve marketing campaigns to optimise effectiveness.

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