Customer Data Platforms Conquer Marketing

Customer-driven marketing is gaining ground. But this development can only be successfully realized with the right technical equipment. To date, most companies use several technologies with overlapping functionalities. This fragmented tool landscape generates additional costs. In addition, such tool architectures cannot meet the challenge of co-orchestrating all channels. However, only when this coordination takes place is it possible to create a successful user experience.

What is needed, then, is a reassessment of the technical infrastructure. The prerequisite for this is that the objective is clear. Once the goal has been defined, the need can be determined and the technological partners can be identified and selected. This shows that CDP solutions can be used to successfully implement a customer-driven user approach.

CDP solutions are characterized by three key functionalities.

1. data aggregation

CDP platforms are aggregators. Data from different sources - from e-commerce, CRM, POS, online, offline - is brought together. Then they are cleansed, normalized and unified - this is called Identity Resolution Management. This creates identities that are compliant with data protection laws and enable those responsible to have a 360-degree understanding of the customer. Miki Müller, Managing Director DACH/EE at Tealium, confirms this: "In our view, the value of a CDP lies in creating a seamless customer experience by unifying customer data from all available sources, including across devices and channels, and making it available to other technologies and the entire enterprise. CDPs thereby enable effective marketing and personalized as well as relevant customer experiences."

2. data processing

After data aggregation and unification, logics and intelligences are created around the customer profiles. The basis for this is the development of intelligent customer segments, taking into account the following data sets:

• Website data: Movements of the user on the website (popular method Recency - Frequency - Monetization).
• Database data (information from the company's databases (transaction history, CLV).
• Modern CDP solutions go one step further and also derive future customer behavior from the tracked data:
• Predictions: Churn probability, Return probability, Purchase probability
• Recommendations: next best product, next best action

3. data activation

But collecting and consolidating customer data centrally is not enough, confirms Maxi Nelkenbrecher, Senior Sales Consultant at CrossEngage. In her view, it becomes exciting when this data can be meaningfully activated for cross-channel and personalized customer communication. However, this is not trivial. That's why some CDP providers provide features to orchestrate marketing channels based on the consolidated data. This includes, for example, the automated playout of campaigns through event-based real-time triggers triggered by previously defined customer behavior. Native integration of the best-of-breed solutions used via APIs ensures a seamless user experience and enables effective personalization.

Data activation is thus the final step in building an efficient data infrastructure. It is about the ability to make the built-up customer identities and the corresponding logics available synchronously or asynchronously to the corresponding channels and thus enable an individualized customer approach. It is important here that the CDP solution has good connectivity to marketing channels. This is the only way to achieve a holistic user approach.

But how do customer data platforms differ from the DMP solutions (data management platforms) that have become very popular in recent years? To begin with, both systems are necessary and not mutually exclusive. Fritz Oleinek, Senior Director Marketing Technology Consulting at Netcentric, sums up the essential differences:

• The DMP serves as the data source for the CDP.
• A CDP must also be much more scalable and able to handle personally identifiable information (PII). As a rule, DMPs are limited to non-PII data (data that cannot be used to identify or track an individual).
• The DMP must provide the interfaces to third-party affiliates so that activated data from the CDP can be used to play ads on the affiliate networks in a personalized manner. The "response" data from the DMP is in turn fed back to the CDP so that further profile enrichment can be carried out there and the data cycle is closed.

In addition to the direct performance comparison, the differences between DMPs and CDPs also become clear along the customer journey.

CDP solutions are taking over businesses and evolving at the same time. Originally intended as data aggregators, they are now becoming customer intelligence platforms. The growth and development area in the next few years will be the use of AI processes for identity resolution management and for developing forecasts and recommendations. In addition, real-time decisions regarding "next best offer" and "next best action" will make customer targeting increasingly relevant and thus more successful.