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June 18, 2025

How Customer Data Platforms support a unified customer view

When discussing customer strategy with clients, I find the terms CDP and Customer 360° used very often. They have become quite common buzzwords in many industries. However, while everyone wants that perfect Customer 360° view, there’s sometimes a bit of confusion about what a Customer Data Platform (CDP) actually is and how it helps us get there. Let’s clear that up and explore these terms.

Gaining a unified customer view

Both Customer 360° and CDP help us get a single, comprehensive view of our customers.

Customer 360° is the outcome we’re aiming for: a complete profile of a customer that brings together all their relevant data into one place.

Customer Data Platform (CDP) is the underlying technology that makes this single view possible. It’s the system that collects, cleans, organizes, and unifies all that customer data.

In the simplest terms, the CDP is the tool that builds the Customer 360° outcome. It helps us personalize experiences and make smarter, data-driven decisions across all our teams – marketing, sales, service, and product.

What kinds of data does a CDP solution use?

To build a complete and useful customer profile, a CDP typically integrates a wide range of data and information. Here are the most common types of data we can use.

Transactional data

This type of data describes what the customer buys or how they spend. For example, this can include:

The sources of this data include Point-of-Sale (PoS) systems, order management systems, and e-commerce platforms.

Behavioral data

This type of information is about what users do and their activities in digital spaces. Example data include:

We can gather this information from websites, mobile apps, emails, cookies, or analytics tools.

Interaction and engagement data

This data type captures how customers interact with our brand across different channels. Here, we analyze:

reviews and ratings
survey responses
social media messages and mentions
customer service tickets
call center transcripts
chatbot conversations

This information is usually gathered from CRM systems, call center platforms, support tools, and social listening tools.

Demographic data

Demographic data help us understand who our customers are. Depending on the use case, this can include information such as:

name
age
gender
location
email address
phone number
company
job title
language preference

and other details.

Contextual, environmental, and identity data

There is a lot of additional information we can gather to add real-time context to customer interactions. We can also use it to match data to a particular user across multiple channels. This additional data can include:

real-time location
device
browser
device ID
username
cookies and session IDs
loyalty card numbers
social media handles

All these different types of information are essential for improving how we engage with both new and existing customers. But when this valuable data is stuck (siloed) in separate systems, it is difficult to get a clear picture of who our customers really are, what they’re doing, and what they expect.

A CDP solves this by breaking down these data walls. By unifying diverse sources into a single, enriched, and accessible profile, it allows us to deliver personalized and timely customer experiences that truly resonate.

The functionalities of a Customer Data Platform

A CDP does more than just collect data; it turns raw data into useful insights and actions. Here are some of its core functions that help us understand customers better, deliver more relevant experiences, and operate more efficiently.

Personalization at scale

A CDP allows us to deliver tailored experiences across multiple channels, in real time. At the core of this personalization is our unified customer view. It helps us understand not just who our customer is (demographics), but also what they’ve done (behavioral data), what they might want (predictive insights), and where they are in their journey.

Powering experiences with real-time data

Imagine this: a customer leaves an item in their online shopping cart. Seconds later, a personalized discount lands in their inbox. That’s how effective real-time data processing is with a CDP. This kind of timely, relevant engagement leads to better conversion rates and happier customers.

Real-time data also enables dynamic content delivery right where your users are, whether it’s your application or a website. We can deliver relevant, meaningful messages, for example recommended products based on browsing history, or ads based on real-time behavior or interests.

What’s important is that CDPs automate the collection, unification, and segmentation of customer data. As a result, they cut out the manual overhead traditionally needed to deliver personalized experiences. This means one-to-one personalization on an enterprise scale becomes a real possibility.

Dynamic customer segmentation

Traditional segmentation methods often rely on limited data, manual processes, and static groupings that quickly become outdated. They also typically include basic segments, e.g. based on demographics.

A modern Customer Data Platform enables a more dynamic, precise, and actionable segmentation. Customer groups are automatically updated based on real-time activity and data from multiple sources. For example, a customer might automatically move from a “prospect” to a “high-value repeat buyer” segment after their second purchase.

In addition, many modern CDPs include built-in AI and machine learning capabilities to support predictive segmentation. This lets us group customers by what they’re likely to do next, such as their probability of converting, churn risk, predicted customer lifetime value (CLV), or interest in a particular product category.

Not just for marketing

The benefits of customer segmentation go way beyond marketing. All our customer-facing teams – sales, support, and product – can access and use this rich data:

Next-gen analytics with AI

Many CDPs now come with integrated analytics and AI capabilities, offering predictive customer insights like churn risk, customer lifetime value, or even determining the next-best action.

A modern CDP turns the data it collects into a powerful training ground for AI/ML models. These models can uncover hidden patterns, score customer behavior and value, and generate actionable predictions.

This means that, instead of just looking at past activities, we can anticipate what customers are likely to do next and adjust our strategies accordingly. This can directly impact our business performance by:

Improving campaign ROI by targeting the right customers with the right message at the right time.
Reducing churn by identifying and engaging at-risk customers early.
Increasing conversion rates by aligning offers with customer intent.
Enhancing customer satisfaction by delivering more relevant, timely, and personalized experiences.
Optimizing resource allocation by focusing efforts where they’ll have the biggest impact.

Next-gen customer strategy with Dynamics 365 Customer Insights – Data

Dynamics 365 Customer Insights – Data is a CDP solution from Microsoft. It is built to create a single source of truth for your customer data and offers a comprehensive set of features, such as:

Connecting to a wide range of data sources (CRM, ERP, web, social, IoT, etc.),
Merging customer data using identity resolution and matching,
Building unified customer profiles (Customer 360),
Creating dynamic customer segments based on behavior, demographics, and more.

Dynamics 365 Customer Insights – Data easily connects with other Microsoft services like Power Platform and Dynamics 365, plus many other solutions, making it a flexible choice for most tech stacks. It also has powerful, built-in AI capabilities for insights, predictions, and data enrichment.

Integrated AI capabilities

Dynamics 365 Customer Insights – Data comes with powerful built-in AI capabilities powered by Azure Machine Learning and Dynamics 365.

Auto-generated insights

The platform offers automated insights based on connected data sources, giving you clear information on things like churn probability or customer lifetime value. Employees don’t need any data science expertise to get or use these insights. The solution provides understandable, ready-to-use information.

Custom models

With Azure Machine Learning and other cloud services, you can train custom data models based on the specific data you collect, no matter the source or format. These additional models can provide insights into hidden or less obvious customer behavior patterns.

AI-powered enrichment

You can get an even better view of your customers with AI-powered enrichment using third-party sources. This feature helps improve your segmentation or fill data gaps with information based on location clustering, sentiment analysis, or demographic inference.

Native integration

All these insights are built right into customer profiles and segments, meaning you don’t need extra tools or complex setups. This makes actionable information readily available for marketing, sales, and service channels, helping everyone make data-based decisions.

Take customer experiences to the next level

If you’re looking to provide better customer experiences, a Customer Data Platform could be just the right move. It lets you get the most out of the data you already have and use it to give your audience exactly what they need at exactly the right time.

If you’re not sure where to start or want to learn more about CDPs or Customer Insights – Data, feel free to reach out. I’d be happy to explore how it can support your business.

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