The differences between CRM, DMP and CDP

There are new technological solutions constantly appearing for companies to take control over customer experience. But which one should I choose? Is there really a difference between these platforms?

In this blog we analyze the differences between Customer Relationship Management (CRM) platforms, Data Management Platforms (DMP), and Customer Data Platforms (CDP), as well as the reasons behind the recent boom of CDPs.

What is a CRM?

A Customer Relationship Management platform is a platform where you can store basic data from your leads. It is a must for any sales team, as it helps to store and structure information about your customers.

What is a DMP?

A Data Management Platform is used to unify data in order to create and segment audiences in really specific ways, as the information integrated comes from different data sources.

What is a CDP?

A Customer Data Platform is software that enables companies to unify every single piece of data obtained from customers (including the data you have in your CRM) and unifies it with third-party data (or data obtained from the market in which you operate), to portray a 360 profile of your customers, in order to segment, personalize, and predict with the use of ML/AI.

Technological evolution: from a CRM to a CDP

CRM (1990s)

CRMs emerged at the end of the last century as a way of storing basic customer information online. They were a very important step: sales teams were able to use them to have databases with leads and to carry out campaigns through them. Today they are still a great help for lead management and lead storage, a great support for sales teams, but they do not cover all the needs of the contemporary company.

Nowadays, companies need to have a database that covers all possible customer data, not only basic information (age, sex, forms of contact, etc.), but they also need to enrich this information with behavioral and attitudinal data (product preferences, forms of purchase, contact times, favorite types of promotions, etc.).

DMP (2000s)

This is how the DMP (Data Management Platform) was born, with the intention of gathering all the information about your customers in a single platform, not only the sales data: you could unify this data (extracted from a CRM) with the behaviors and attitudes of your customers.

So with a DMP your company can create audiences and segment them in hundreds of ways so that your advertising or marketing teams can target their campaigns to much more specific audiences. The DMP was the next step from the CRM as it was much closer to the online personalization that companies were looking for.

CDP (2020s)

The unification of all possible customer data opened up a world of possibilities, but the key piece of the puzzle was missing: converting this data into actionable data. The CDP was born to integrate all the aforementioned data with ML, allowing companies to know their customers like never before. It allows you to have a detailed picture of each customer as an individual so that you can personalize your campaigns to the extreme.

The 360-degree customer profile that you obtain using a CDP allows companies to segment, personalize and predict behaviors with the use of Machine Learning. Customer Data Platforms thus emerge as the ultimate solution for omnichannel customer management, multiplying the knowledge you have of your customer to levels never before imagined.