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Customer Data Platform

Skypoint’s AI-powered customer data platform (CDP) feature allows you to utilize AI agents to deliver exceptional customer experiences.

AI CDP: A Next-Gen Data Approach to Evolving Customers

A new era of data has arrived. Users are more in control of their experiences and brand and privacy expectations have never been higher. Unified data and AI agents are vital for delivering personalized experiences regardless of industry. 

Using AI, Skypoint’s modernized customer data platform (CDP) creates new dimensions for understanding and segmenting your customers into high-performing audiences. This approach pushes beyond the current standards of traditional CDPs, by incorporating AI agents to meet evolving customer needs.

Unified AI-Ready Customer Data

Personalization continues to be a top goal for organizations. Yet, the lack of customer insights and intelligence is slowing the shift to customer-centric business models. Our CDP is built on leading-edge data lakehouse technology that meets your ever-changing data needs. 

Make your data work for you by leveraging our zero-copy data lakehouse, or bring your own data warehouse. High-quality customer data unified through master data management enables valuable business intelligence and predictive analytics to simultaneously advance and simplify your efforts.

Skypoint Cloud Ecosystem Illustration - Customer Data Platform (CDP)

How Skypoint AI CDP Works:

Skypoint’s CDP brings your customer data together from multiple sources to create a unified view of the customer or business. It collects first-party, second party, and third-party details. The data is then cleansed and categorized for precision into enriched B2B or B2C profiles.

Customer Data Platform for Spas and Salons

1. Import

Import data from disparate data sources into the Skypoint Lakehouse using Dataflow, Skypoint’s built-in ELT tool. 

2. Unify

Data is then unified by removing unneeded attributes, consolidating duplicates, and  creating unique profiles.

3. Segment

Create targeted audience segments using AI-powered insights and unified customer or business profiles.

4. Activate

Use AI agents to activate unified customer data and take automated actions to drive engagement.

Skypoint AI CDP Capabilities:

Skypoint’s CDP focuses on core capabilities to provide a platform for B2B or B2C use cases that is both comprehensive, and flexible, while incorporating essential best practices centering around unification, governance, privacy and AI.

Data Ingestion

Skypoint’s built-in ELT, allows you to effortlessly centralize all your data, maintain privacy compliance, and deliver personalized experiences with real-time insights.

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Data Unification

Skypoint Cloud’s master data management enables organizations to integrate, cleanse, unify and enrich their data across various sources while providing data governance.

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Integrated Data Lakehouse

A Data Lakehouse is the core of the CDP, combining the benefits of a data lake and data warehouse to create a new open data management architecture.

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Entity Resolution

Harness the power of AI to deduplicate, manage, and improve core business entities or individuals, such as patients, providers, customers, guests, residents, products, and suppliers.

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Consolidated Profiles

Automate data unification across silos to create unique 360-degree  profiles for personalized and trusted interactions.

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Predictive Analytics

With a variety of options ranging from simple yes/no predictions, to bespoke machine learning models for complex scenarios – Skypoint CDP helps you make rapid decisions at scale to deliver the best possible outcomes.

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Privacy Compliance

A privacy-first approach to data management and accessibility ensures privacy compliance across business initiatives.

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Data Security

Built on Microsoft Azure, Skypoint Cloud fully aligns with Azure as a data security and trust platform that follows four core principles—security, privacy, compliance, and reliability.

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Why Skypoint AI CDP:

Industry Specific

Skypoint’s CDP provides 12+ different profiles to consolidate data to fit the needs of your industry, focusing on healthcare. 

Integrated Data Lakehouse

All the components of an CDP solution— ingestion, modeling, governance, lineage, tracking and visualization – work seamlessly together to support your ongoing success. Built on a centralized Data Lakehouse.

Unlocks AI Agents

Skypoint’s CDP, built-in unified profiles unlocks AI agents. This enables your organization to make proactive business decisions to engage customers and automate tasks.

Skypoint AI CDP FAQs

A customer data platform creates a unified customer profile with information gathered from multiple sources. CDPs collect data on anonymous visitors to your website and analyze lifetime customer behavior and customer journeys, tracking both online and offline customer data. They’re designed to handle multiple data points from a large number of sources.

Skypoint’s CDP is built with integrated privacy compliance and sensitive data management. We use a proprietary identity resolution model to stitch your first-party customer data together to create a comprehensive customer profile and journey. 

We allow customers to configure role-based access to PII and other data that is labeled sensitive by our customers to ensure usability while protecting consumer privacy 

Skypoint’s CDP sits at the intersection of composable and unbundled, to provide the best of both worlds. It’s an architectural paradigm — the platform is unbundled, meaning it has a decoupled Data warehouse / Lakehouse and it’s “composable” with other tools like Dbt, fivetran etc. With a traditional CDP, the data warehouse is a separate entity from the CDP itself. Batch data moves through the ETL (Extract Transform Load) process to the data warehouse, while event data goes into the CDP. In this situation, the CDP is completely separate from the data warehouse. This means that analyzing data outside of the CDP environment is fractured and creates yet another data silo. With an unbundled CDP, the data warehouse or data lake serves as the center of the system and provides an easy-to-use interface to do data transformations under the covers for things like audience segmentation, metrics, and exporting lists to campaign tools like Mailchimp or Klaviyo. From there, your organization doesn’t need to do extra gymnastics to properly analyze your data and implement marketing changes based on the insights collected. By unbundling the CDP, you maintain the ability to analyze your data where and when you need it while also providing Marketing team-friendly capabilities you know and love from a traditional CDP. You also get more flexibility and control over your data, which is invaluable as your organization grows and develops. In simple terms, the real value here is that you’re gaining a strong data foundation so you’re set up to solve a vast array of business needs. Read our blog post

Skypoint Cloud normalizes and standardizes customer data leveraging the Common Data Model (CDM). CDM is an open standard that creates an extensible collection of data schemas (entities, attributes, relationships) that translate into business concepts and activities. 

The Skypoint platform maps your customer data to CDM to power our proprietary identity resolution model which stitches data together to create a comprehensive profile of customer activities, interactions, transactions, and behaviors. 

With a growing list of native connectors, you can easily and quickly connect your data from existing systems directly into Skypoint’s platform. Our integrations list is always expanding.

Customer data platform (CDP) and master data management (MDM) are both data management technologies, but they serve different purposes. MDM is focused on creating a single source of truth for critical business data, while CDP is focused on creating a unified view of customer data to support customer interactions and experiences. MDM is typically used for back-office functions, while CDP is used for customer-facing activities.

Here’s a brief summary of what makes CDP different from MDM:

Aspect

Master Data Management (MDM)

Customer Data Platform (CDP)

Goal

Creating a “single source of truth” for business data

Consolidating and unifying customer data from multiple sources

Data Sources

Structured data from internal systems

Structured and unstructured data from multiple sources

Data Management

Focuses on data quality, governance, and consistency

Focuses on data processing, segmentation, and personalization

Usage

Back-office functions (finance, supply chain, etc.)

Customer-facing activities (marketing, sales, customer service)

Skypoint Cloud uses a series of data quality checks to identify issues and ensure only the highest quality and most complete data is included in our identity resolution model—improving the overall accuracy of our matching model. 

We leverage pattern-based validations and standard regular expressions for normalizing data. Our platform also provides insights to help you continuously improve data quality and know which actions to take. Together, we are always increasing the completeness and accuracy of your data source systems.

customer 360 consolidates and organizes the information that a brand knows about its customers into comprehensive profiles. The information that these profiles contain varies from one business to another, but typically includes:

  • Customers’ contact information and preferences
  • Demographics shared by the customer (i.e. gender, age)
  • Digital and offline engagement history (i.e. email, customer care)
  • A customer’s transaction history—or treatment history in healthcare
  • Relevant healthcare data details on a patient’s medical care and status (i.e. prescriptions, allergies)

Many customer 360s include not just raw data but a view of each customer that is enriched with relevant attributes and predictions. For example, a customer 360 view for a consumer brand might include derived fields like “number of last transactions in the last 12 months” and “likelihood to purchase in the next 3 months.” 

A customer 360 is a foundational tool for businesses that aims to personalize and improve the customer experience. Brands typically use their customer 360 to fuel use cases like:

Understanding of the overall customer base to design better products and experiences (What percentage of my customers have seen a primary care physician at least once over the past month?)

Measurement of customer health (Has my active customer base been trending up or down over time?)

Segmentation to identify the optimal channel, message, or promotion for groups of customers (Who are my customers who make frequent, low dollar-value purchases?)

Personalization of one-to-one customer interactions (What’s the clinical history of a particular patient engaging with a care rep on a digital health app?)

Wrangle Your Data and Prioritize Consumer Trust

Skypoint’s AI CDP connects customer data to enable AI agents to take automated actions and engage your customers.

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