CDP: Platforms to Engage with Customers
Seeing at a glance the unique profile of a customer, with all the information available about him, is a luxury for a company that interacts a lot with consumers. Technology makes it possible to do this at an increasingly lower cost and in a very visual and usable way. This is what PDCs are for.
What is a Customer Data Platform (CDP)
A CDP or Customer Data Platform is a repository that functions as a single customer database. Once all the information has been collected, profiles of these consumers are created. To create this CDP, companies can use data from internal and external sources, which, although in different formats, are transformed into a homogenized one.
With a CDP, teams can perform predictive and marketing tasks on customer behavior. In addition to having a unique profile for each one, employees group each one into groups or segments.
Among the customer data that can be collected are:
- Their activity on the web or in the application
- Personal information such as age, gender…
- Purchases and returns
- Conclusions about advertising campaigns: impressions, clicks, reach…
This data can be combined in the CDP with other corporate data, such as the impact of an advertising campaign or the number of sales. Having them all in a single platform makes it easier to update and protect them. It is also easier to delete or modify them if a customer requests it.
Not only the marketing team will find this platform useful, but also, as we will see later, the sales and customer service teams.
In this way, by having a CDP, the company:
- Compile data in one place for retrieval whenever possible
- Manage all data from the same platform
- Design better customer experiences
- Create groups of audiences for personalized marketing campaigns, which have a great value: the data generated by their own consumers
Examples of a Customer Data Platform
As we said above and as Microsoft’s website reminds us, not only the marketing department could take advantage of CDPs. There are several examples of Customer Data Platforms, according to each corporate department.
Sales teams could also use it to create personalized profiles with the loyalty status of each customer, their spending or frequency of purchase. As for customer service departments, having a profile of each customer helps to give them a personalized and unique service, according to their needs and their relationship with the company (VIP customer, newcomer…).
A CDP is not only for digital activities. The platform also connects with analog activities. For example, if a customer enters a physical store, they can be identified and linked to their digital profile to offer them personalized attention.
Customer Data Platform and Sustainability
Whatever the department, CDPs bring with them greater efficiency and agility. And also more customers who appreciate sustainability.
Customers are increasingly interested in sustainable brands, and companies are interested in them and in meeting their Corporate Social Responsibility (CSR) or carbon emissions targets. Thanks to the use of big data, it is possible to know which people are most interested in sustainable products and to prepare specific advertising campaigns and offers for them, or to suggest sustainable products related to others already purchased.
The Architecture of a Customer Data Platform
To build the architecture of a CDP, you must take into account:
- That the data is going to be sorted in a single place for use at any time and across individual customer profiles.
- Also, it can be used in other third-party platforms (e.g., in an advertising campaign creation platform). CDPs need the tools to create those campaigns.
The CDP architecture should also include customer privacy and consent options. In this way, you contribute to improving your company’s brand image: customers know that your company respects the privacy of its users.
The structure should also serve to identify missing profile information or the opposite: to manage duplicate data.
If you want to go further, a CDP can also include predictive data, such as the likelihood of purchase or abandonment (newsletter, website, etc.). The architecture of a Customer Data Platform uses Artificial Intelligence and Machine Learning to improve prediction and analysis.
The implementation time of a CDP architecture depends on the complexity of the platform and the company’s objectives with it. Once it is operational, the possibilities that open up are broad and attractive.