Customer Data Platform
Pobuca as a Customer
Data Platform (CDP)
A CDP is a packaged software that imports customer data from multiple sources to create a unified customer database that is accessible to other systems.
Data is being mined from multiple touchpoints, cleaned, and combined with other data sources to create a single customer profile. These structured data are then made available from CDP to other marketing and operational systems.
Pobuca Experience Cloud integrates into its core a CDP that acts as the foundation for all other subsystems such as customer engagement, loyalty, and data analytics.
Sources of data
All data stored in CDP are customer-centric, as they are always related to a specific customer. They can be generated in any one of the following ways:
with back-office systems such as point of sales terminals or ERP.
by our platform itself
for example when a campaign or a survey is sent.
by other systems in
Pobuca Experience Cloud that provides a rich API to be used by external apps to get or send data.
Typical data types that are stored in our CDP
A 360o customer view is one of the most efficient benefits of a CDP that allows you to create and offer a personalized customer experience.
How to achieve it?
Customer profile & demographics
open newsletter, clicks
open newsletter, clicks
points, rewards & coupon information
Survey & feedback
responses & customer feedback
Customer Service interactions data
NPS scores, chats, emails, phone calls in call center
browsing activity, actions on a website or in an app
Most of this data is stored in Microsoft Dataverse, the data backbone of Pobuca Experience Cloud, a scalable and secure environment that also serves as the data backbone of Microsoft Power Platform and Dynamics 365. Additional data is stored in Azure Cosmos DB, to minimize data storage costs.
Following their collection and assessment, customer data can be enriched, either for filling in missing information or adding new, based on machine-learning models and other algorithms. For example, the gender of customers can be inferred through their first names, and the churn probability can be estimated using a churn prediction model.
Having all data stored in a common database gives us the advantage to have a 360° view of the customer, allowing us to perform unparalleled customer segmentation and personalization. Moreover, machine learning models are used to cluster customers and analyze them to create specific personas.
Customer events can be used as triggers for actions to provide the right response at the right time. These triggers can fire up complex workflows that are designed visually and provide common functionality such as messaging, customer attribute updates, or alerts.
Our data backbones, Dataverse and Cosmos DB, seamlessly integrate with Azure Data Analytics stacks and machine learning services such as Azure Synapse Analytics, Power BI, Databricks (Spark), and Azure ML.