August 29, 2022
In the field of marketing technologies (MarTech), we like to speak metaphorically of a jungle, because the subject proves to be a multifaceted landscape with different terrains and disciplines. Due to the sheer mass, one easily runs the risk of losing the overview.
In the context of this metaphor, Customer Experience Platforms (CXPs) can be described as green clearings from which the majority of these terrains can be accessed. One of these clearings may be CrossEngage.
To give a better perspective on the topic and on the tool, we asked our colleague and MarTech consultant David Deronja five questions about the CrossEngage CXP. David has been working for many years not only in the MarTech environment, but also with CrossEngage as a tool and is therefore an absolute expert in the field. He knows the features inside and out and knows exactly what marketing automation and data-driven marketing is all about.
First of all, let’s clarify some MarTech terminology: In the marketing automation context, we work with two basic systems: The CDP and the CXP. The Customer Data Platform (also called CDP) focuses as a tool on the preparation, transformation and aggregation of customer data. A Customer Experience Platform (CXP) focuses on the omnichannel customer experience. It enables omnichannel delivery of relevant marketing messages to the target audience.
CrossEngage, with all its features, falls more into the CXP category. It provides its users with a 360° view of the individual customer relationship, helps create customized (AI-powered) target groups, and activates them across all touchpoints and channels. This guarantees an outstanding brand experience and ensures sustainable customer relationships.
In addition to the CXP module, CrossEngage also offers GPredictive, a module that can be used to make predictions about specific customer behavior. It can be used to determine the (future) customer values, preferences and behaviors of customers. After all, knowing what you can expect from your customers is one of the most important levers for value-oriented customer management.
In order to successfully target customers with relevant marketing messages, data is needed first. Often, marketers do not have the necessary data to do this or existing data is heterogeneously distributed across the company’s system landscape. CrossEngage allows data from different sources to be brought together and aggregated into a unique 360-degree customer profile. By overcoming these data silos, a unified view of all customer data is guaranteed, optimizing every single customer experience.
Many marketing teams are also dependent on their IT department because they don’t have the skills to generate and aggregate data themselves.
CrossEngage provides no-code capabilities to break down this very dependency – also called: Democratization of Data. This makes data available so that marketing teams without technical skills or programming knowledge can serve content to their audiences based on data. This ensures consistent, uniform omnichannel playout at all times.
A special highlight of Crossengage is the Best of Breed approach. Best of Breed means that standard integrations are in place with all major marketing tools, such as Google, Facebook or Sendgrid as an email service provider.
In addition, the platform has an extremely intuitive user interface. This makes it particularly quick for a marketeer to work with data, perform segmentations and set up campaigns.
The combination of CrossEngage with GPredictive also makes it possible to make predictions based on collected data. In this way, for example, the purchase probability, the customer lifetime value (CLV) or the churn rate of a customer can be predicted. The data obtained in this way can then be used for campaigns and segmentation.
When it comes to cleaning, making available and aggregating data, I still see a challenge for CrossEngage. For example, if I want to find out the average shopping cart value of a user, this still has to take place in an upstream instance or in an external service.
However, since the general genre of Customer Data Platforms and Customer Experience Platforms is still young, it can be assumed that certain functions will be added in the future.
Before implementing CrossEngage, your own requirements for the tool should first be clearly defined in the form of marketing use cases. When formulating them, it is important to think of what specific marketing campaigns you would like to play with the tool. This helps to build the MarTech target architecture.
Interaction data should also be supplied in the form of events so that marketing managers can perform segmentations based on these events.
In addition, it is always recommended to define a unique identifier that identifies a single user across all source systems. This facilitates subsequent data aggregation.
Thanks for sharing your valuable experience with us, David!
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