Customer Data Platform

What is a customer data platform?

A Customer Data Platform (CDP) is a highly technical platform for data consolidation. It captures all newly generated customer data in any solution to which it is connected - from e-commerce tools, content management systems, ERP solutions, and many more. A customer data platform tracks invoice receipts, clicks on websites or online stores, and any other interactions that users make in the integrated source systems. This information can be used to answer the following questions with the help of a customer data platform:

• Who is the customer?
• What does he do?
• When does he do it?

Due to the complexity associated with CDP-supported data management, using a customer data platform is only recommended in IT system landscapes of a specific size. The following applies: the more tools a company uses, the more strategically sensible and economically profitable a CDP is.

In addition to its primary function of centralized data consolidation, a customer data platform offers features that go far beyond those of a CRM system. These are the most important:

1. Track (anonymous) data of any kind

   A customer data platform records every interaction and transaction, no matter how small. For example, if previously unknown users visit an online store, cookies are set in the browser - depending on the personal data protection settings. If visitors object to the data being recorded, tracking can be done without cookies. In this case, the Customer Data Platform registers, for example, which end device the user uses to visit the store and which browser version they use.

   Tracking anonymous data in a customer data platform makes sense for another reason: as soon as users register, the recorded data can be used to reconstruct their previous user history - which is very helpful for sales and customer service.

    

2. Segment target groups at an acceptable granular level

   Different customer and prospective customer target groups can be very accurately differentiated based on the variety and diversity of customer data provided by a customer data platform. This fine-grained segmentation allows individual conclusions to be drawn, such as: "Anyone looking for blue sneakers is also very likely to be interested in black sneakers." This means that when users make a corresponding search query in an online store, an AI-supported process of hyper-personalization is automatically set in motion. In the next step, users are shown individual content on a dynamically generated landing page that matches their interests and previous history (for known website visitors) - from products and discount promotions to further content.
    

3. Predefining customer journeys

   With the help of a customer data platform, it is possible to use personal data and, with the help of artificial intelligence metrics, determine if-then causalities. This is done by using a CDP to cluster and summarize data of all kinds. The analytical information obtained in this way reveals recurring patterns that can be translated into sets of rules that are then automatically applied. For example, it is possible to specify that known website visitors who repeatedly visit a specific page receive a predefined email on the umpteenth visit, which should trigger a particular action. Depending on how visitors interact with this email, i.e., whether the desired conversion occurs - or not - the next step of the predefined customer journey occurs automatically (customer journey mapping).

   For this process to function smoothly, it must be clearly defined: How does the data enter the Customer Data Platform? And how does it leave it again? For this, it is essential to rely on an experienced IT service provider that provides companies with expert advice and performs needs analysis, integrates the customer data platform into the IT infrastructure, models clean data flows, defines segmentation rules, and implements and configures the resulting rules.

The answer to this question lies in the previous one: A CDP contains all customer data from all connected systems and platforms. In contrast, only relevant information for marketing, sales, and customer service flows into a CRM system. This means that the sole use of a customer data platform does not make sense. After all, source systems are needed from which the data flows into the CDP. Target systems are required so that the processed information can then be made available in a usable form.

How does data get into a Customer Data Platform?

The CDPs from renowned providers such as Microsoft, SAP, and Informatica have modern web interfaces. These preconfigured and high-performance APIs (Application Programming Interfaces) make it easy to seamlessly integrate a customer data platform with the relevant source and target systems, thus ensuring smooth data flows. An ETL process (Extract - Transform - Load) forms the basis for data consolidation and provision: structured and unstructured raw data from any source is transferred to the CDP via the APIs. Once the relevant data has been filtered out of the mass of data, it is converted into the desired format, written to databases, and finally made available in the intended target system. All of this happens in real-time.

Many aspects favor using a customer data platform in online retail companies. The following examples outline predestined application scenarios:

• Online retailers can enrich customer data with additional information from the CDP. This puts them in a better position than before to segment prospective customers with similar interests and not only offer these customer groups tailored prices but also alert them to attractive discount promotions. This increases retailers' chances of generating more sales.
• If interested parties look around a web store, the CDP registers all clicks and the resulting page visits. However, this action is only recorded in the CRM system when users place a product in the shopping cart. The customer activity is the predefined trigger that triggers the CRM entry because it is relevant for sales - the individual clicks beforehand are not.
• The more personal data online retail companies have at their disposal, the more individually they can view and support individual customers. This makes it possible, for example, to accurately display personalized advertising on a website or in an online store. This is not just about differentiating between men and women or younger and older people but also anticipating the needs of each customer and targeting them with advertising exactly where the shoe pinches. The data for such individualized ads comes from a customer data platform.
• The data collected in a customer data platform is beneficial for sentiment analysis. As it records every comment about a product, its quality, customer service, or the retail company - whether positive or negative - specific terms can be defined, the use of which automatically triggers an action in the CRM system. This allows customer service to contact the relevant customer and thank them for a positive review, for example. Or resolve a situation even before dissatisfied customers make an official complaint.