In a quite amazing how customer data platforms (CDP) have moved to the top of enterprise Martech (marketing technology) discussions.
How do enterprises get the maximum insights from customer big data to make to make martech a successful and delightful exercise? Perhaps this question will be in the mind of enterprises that try to achieve the perfect mix of product and services for customer delight.
Customer data platform(s) are seen by many enterprise marketers as the solution. Thanks to big data technologies this ‘new’ category of solutions offers integrated insights to actionable customer data. These insights come from the offerings and customers’ expectations of more personalized content and better customer experiences. For marketers, it means rethinking about the promotions to offer them based on time and context, or the alerts and notifications to push when they step into a physical store.
Customers want customised attention, but they also want to understand how their data is being used and what is happening with their data.
Decoding Three Pillars of Customer Data Platforms
Data– Customer Data Platform (CDP)
The data CDP in is analogous to a customer database, it encapsulates data merging, data aggregation utilizing standard connectors within the CDP. The solution brings the basic functions for diagnostics, backup and data monitoring for quality so that the best data pipelines are ensured within the CDP already during data integration.
Analytics — Customer Data Platform (CDP)
An analytics CDP enriches the CDP’s internal customer database with customer segmentation information and customer profiles. Subsequently, an analytics CDP deploys this data to churn into information, partly with the help of artificial intelligence. This is done to perform selections and determine target groups for subsequent utilization.
Engagement– Customer Data Platform (CDP)
Engagement CDP is the umbrella term for customer database, analysis/selection and campaign initiatives. Through standard connectors and identity matching, it creates the customer perspective necessary for targeted campaigns, produces segments to address customer positioning. These target groups then receive personalised offers in multi-channel campaigns. A campaign CDP focuses on adding value to the customer lifecycles.
Fitting Customer Data Platforms to the MarTech Architecture
Organisations are different and so are their products and service offering. No customer is the same. So how do Chief marketing technologists fit CDP into their organisational architecture?
A look at the source systems to be connected helps answer this question. Marketing teams must answer the following questions-
- Do I have many source systems which I can connect to my data CDP with standard connectors?
- Can I merge customer data relatively easily with an identical customer number?
In a crux, when choosing the right kind of CDP, marketers and the tech teams must always consider the key areas covered by the individual types of the customer data platform. If business requirements require integration of customer data, a data CDP is the first choice; if the focuses on analytics or complex journeys, then martech professionals should choose analytics or engagement CDP. Besides, enterprises must not ignore the previously created use cases representing their business model for selecting a customer data platform from the right category to target and reach to their customers with product and service offerings that create a delightful experience.