Last updated: May 20, 2025
With Customer Data Platform (CDP), you can unify, manage, and analyze data from various sources. In addition, you can:
CDP empowers businesses to make data-driven decisions, streamline marketing efforts, and enhance customer satisfaction for increased revenue and long-term growth.
The main features of Customer Data Platform fall into the following categories:
The following section elaborates the features of CDP:
Campaigns is a customer segmentation and activation tool that orchestrates personalized marketing campaigns across engagement channels. It enables segmentation and personalization using omni-channel customer, transaction, and engagement data to deliver personalized content to multiple destinations.
Metrics is an analytics reporting tool that facilitates data analysis through the creation of insightful reports and visualizations. You can explore and analyze the output of Metrics reports in tabular format and a wide array of chart views to enhance comprehension. Metrics provides out-of-the-box, pre-calculated dimensions. It serves as a business intelligence tool that enables you to understand the data and make informed decisions.
Template Reports is a tool that you use to run and consume custom template reports.
Interactive Queries is a SQL Interactive Development Environment (IDE) to query data in CDP for data exploration and data analysis.
Cohort Analysis is a tool that enables data analysts and marketers to define static audiences of users to analyze their behavior in Metrics and leverage them in Campaigns.
Machine Learning Models is a set of standard, Acquia-maintained machine learning models available to use in Campaigns, Metrics, and 360 Profiles.
Machine Learning Studio (CDP Studio Apps) is a machine learning IDE that allows you to write Python and SQL code and also build and deploy client maintained custom machine learning models so that you can surface the custom machine learning models in Campaign+, Metrics, and 360 Profiles.
360 Profiles is a tool that you use to search for specific customers and access their information. You can query the unified and enriched customer profile built by CDP. You can use this tool for marketing and customer interactions, and power one to one customer interactions.
Universal Data Model (UDM) is a configurable data layer that provides a comprehensive and adaptable structure for your data. It comes with sets of standard entities, custom entities, standard fields, and custom fields. Standard calculations and custom calculations are calculated attributes.
Custom Attributes (CDP Studio Apps) is a tool that allows the self-service creation and deployment of custom fields of different data types (including string, decimal, integer, and date) to Campaign+, Metrics, and 360 Profiles.
Pipelines is a set of data processes to ingest, process, and surface the data in CDP. It is composed of batch pipelines and real-time pipelines.
Data Calculations is a set of data computations and data enrichment processes. The process includes calculated attributes, that is, standard calculations or custom calculations.
Custom Calculations (CDP Studio Apps) allows the self-service creation and deployment of custom calculations so that you can surface the custom calculations it in Campaign+, Metrics, and 360 Profiles.
Identity Resolution is a set of data processes to identify, connect, and consolidate data points from multiple sources to create a single, clean and comprehensive view of a customer.
APIs is a set of the following modules:
Data Export is a set of configurable modules that exports or shares data outside CDP. The following are the three modules of data export:
Access Management is a tool to manage users, roles, and permissions in CDP.
Data Retention is a set of data processes to ensure that CDP retains all the data that is relevant to the customer while maintaining the volume of data at manageable levels.
Data Erasure is a set of tools to manage data erasure requests for user records in CDP.
The following are the definitions of terminology used in CDP:
customersummary table.transaction table. More specifically, it is a combination of Transaction Lines that occur simultaneously.transactionitem table.event table.customer, transaction, transaction item, product, product category, and organization.pets is a new table in the data model and therefore is a custom entity.first name is a standard field on the standard entity customer.preferred pet color is not part of the base schema and therefore is a custom field.exact matching on email address is part of the default IRE rule and therefore is a Standard IRE rule.exact matching on loyalty id is not part of the base set of rules and therefore is a custom IRE rule.Standard Machine Learning Model - A Machine Learning model, which is trained and scored on the customer’s data. The following are the standard models:
For the standard model, the default parameters including input features must be unchanged.
The following are the limitations of CDP:
Data Retention- The data retention applies to the following categories:
| Category | Default Retention | Notes |
|---|---|---|
| Email send events | 6 months | |
| Email events (excludes sends) | 12 months | Includes email opens and clicks. |
| Events in Metrics | 3 months | Events in Metrics can only be filtered for up to 3 months within the retention period. |
| Anonymous events | 6 months | Not stored outside of the sessionization window. |
| Direct mail events | 2 years | Direct mail campaign file includes a list of final recipients of the direct mail campaign and those reserved as holdouts from the campaign. |
| Campaign, template reports, campaign history, cohort analysis | 6 months | Campaign history is only utilized for those customers using legacy. campaigns. |
| Exports | 6 months | Utilized to diagnose errors. |
| Kafka (WebTag) | 7 days | Utilized to diagnose errors. |
| TransactionMessageXRef | 13 months | Utilized to diagnose errors. |
| Web events | 13 months | Capture data from your customer’s interactions with your website or application. |
| Non-event entities (DW and BI) | 3 years | Any other entities not specified previously. |
| FTP | 30 days | Data placed in Acquia’s FTP server. |
| Sparse | 30 days | Internal source for intermediate processing. |
| Exports in S3 and Redshift | N/A | Client responsibility. |
| Machine Learning Studio (CDP Studio Apps) Fair Usage (Package: Small) | |
|---|---|
| Python instance | Up to 720 hours of the Python instance running per month |
| Query instance | Up to 100 hours of Snowflake query execution per month |
| Compute limits | Up to 8 vCPUs for Python and Snowflake instances |
| S3 Storage | Up to 1 GB - S3 Storage only stores metadata. At no point, CDP data must not be stored in S3 |
| Snowflake storage | Up to 1 TB of Snowflake Storage |
| Tenants | Up to one tenant |
| ML Columns | Up to five columns for ML results |
| Machine Learning Studio (CDP Studio Apps) Fair Usage (Package: Medium) | |
|---|---|
| Python instance | Up to 720 hours of the Python instance running per month |
| Query instance | Up to 100 hours of Snowflake query execution per month |
| Compute limits | Up to 32 vCPUs for Python and Snowflake instances |
| S3 Storage | Up to 2 GB - S3 Storage only stores metadata. At no point, CDP data must not be stored in S3 |
| Snowflake storage | Up to 1 TB of Snowflake Storage |
| Tenants | Up to one tenant |
| ML Columns | Up to five columns for ML results |
| Machine Learning Studio (CDP Studio App) Fair Usage (Package: Large) | |
|---|---|
| Python instance | Up to 720 hours of the Python instance running per month |
| Query instance | Up to 100 hours of Snowflake query execution per month |
| Compute limits | Up to 64 vCPUs for Python and Snowflake instances |
| S3 Storage | Up to 3 GB - S3 Storage only stores metadata. At no point, CDP data must not be stored in S3 |
| Snowflake storage | Up to 2 TB of Snowflake Storage |
| Tenants | Up to one tenant |
| ML Columns | Up to five columns for ML results |
| Custom Calculations (CDP Studio Apps) Resource Limit (Package: Small) | |
|---|---|
| Python instance | Up to 240 hours of the Python instance running per month |
| Query instance | Up to 50 hours of Snowflake query execution per month |
| Compute limits | Up to 4 vCPUs for Python and Snowflake instances |
| S3 Storage | Up to 1 GB - S3 Storage only stores metadata. At no point, CDP data must not be stored in S3 |
| Snowflake storage | Up to 0.1 TB of Snowflake Storage |
| Tenants | Up to one tenant |
| Output Columns | Up to five columns for outputs |
| Custom Calculations (CDP Studio Apps) Resource Limit (Package: Medium) | |
|---|---|
| Python instance | Up to 240 hours of the Python instance running per month |
| Query instance | Up to 50 hours of Snowflake query execution per month |
| Compute limits | Up to 16 vCPUs for Python and Snowflake instances |
| S3 Storage | Up to 2 GB - S3 Storage only stores metadata. At no point, CDP data must not be stored in S3 |
| Snowflake storage | Up to 0.5 TB of Snowflake Storage |
| Tenants | Up to one tenant |
| Output Columns | Up to five columns for outputs |
| Custom Calculations (CDP Studio Apps) Resource Limit (Package: Large) | |
|---|---|
| Python instance | Up to 240 hours of the Python instance running per month |
| Query instance | Up to 50 hours of Snowflake query execution per month |
| Compute limits | Up to 32 vCPUs for Python and Snowflake instances |
| S3 Storage | Up to 3 GB - S3 Storage only stores metadata. At no point, CDP data must not be stored in S3 |
| Snowflake storage | Up to one TB of Snowflake Storage |
| Tenants | Up to one tenant |
| Output Columns | Up to five columns for outputs |
Acquia Inc. reserves the right to change the Products and Services Guide based on prevailing market practices and the evolution of our products. Changes will not result in a degradation in the level of services provided during the period for which fees for such services have been paid.
| Date | Update |
| May 20, 2025 | Added quicklinks. |
| May 7, 2025 | Added document changelog. |
If this content did not answer your questions, try searching or contacting our support team for further assistance.
Last updated: May 20, 2025
With Customer Data Platform (CDP), you can unify, manage, and analyze data from various sources. In addition, you can:
CDP empowers businesses to make data-driven decisions, streamline marketing efforts, and enhance customer satisfaction for increased revenue and long-term growth.
The main features of Customer Data Platform fall into the following categories:
The following section elaborates the features of CDP:
Campaigns is a customer segmentation and activation tool that orchestrates personalized marketing campaigns across engagement channels. It enables segmentation and personalization using omni-channel customer, transaction, and engagement data to deliver personalized content to multiple destinations.
Metrics is an analytics reporting tool that facilitates data analysis through the creation of insightful reports and visualizations. You can explore and analyze the output of Metrics reports in tabular format and a wide array of chart views to enhance comprehension. Metrics provides out-of-the-box, pre-calculated dimensions. It serves as a business intelligence tool that enables you to understand the data and make informed decisions.
Template Reports is a tool that you use to run and consume custom template reports.
Interactive Queries is a SQL Interactive Development Environment (IDE) to query data in CDP for data exploration and data analysis.
Cohort Analysis is a tool that enables data analysts and marketers to define static audiences of users to analyze their behavior in Metrics and leverage them in Campaigns.
Machine Learning Models is a set of standard, Acquia-maintained machine learning models available to use in Campaigns, Metrics, and 360 Profiles.
Machine Learning Studio (CDP Studio Apps) is a machine learning IDE that allows you to write Python and SQL code and also build and deploy client maintained custom machine learning models so that you can surface the custom machine learning models in Campaign+, Metrics, and 360 Profiles.
360 Profiles is a tool that you use to search for specific customers and access their information. You can query the unified and enriched customer profile built by CDP. You can use this tool for marketing and customer interactions, and power one to one customer interactions.
Universal Data Model (UDM) is a configurable data layer that provides a comprehensive and adaptable structure for your data. It comes with sets of standard entities, custom entities, standard fields, and custom fields. Standard calculations and custom calculations are calculated attributes.
Custom Attributes (CDP Studio Apps) is a tool that allows the self-service creation and deployment of custom fields of different data types (including string, decimal, integer, and date) to Campaign+, Metrics, and 360 Profiles.
Pipelines is a set of data processes to ingest, process, and surface the data in CDP. It is composed of batch pipelines and real-time pipelines.
Data Calculations is a set of data computations and data enrichment processes. The process includes calculated attributes, that is, standard calculations or custom calculations.
Custom Calculations (CDP Studio Apps) allows the self-service creation and deployment of custom calculations so that you can surface the custom calculations it in Campaign+, Metrics, and 360 Profiles.
Identity Resolution is a set of data processes to identify, connect, and consolidate data points from multiple sources to create a single, clean and comprehensive view of a customer.
APIs is a set of the following modules:
Data Export is a set of configurable modules that exports or shares data outside CDP. The following are the three modules of data export:
Access Management is a tool to manage users, roles, and permissions in CDP.
Data Retention is a set of data processes to ensure that CDP retains all the data that is relevant to the customer while maintaining the volume of data at manageable levels.
Data Erasure is a set of tools to manage data erasure requests for user records in CDP.
The following are the definitions of terminology used in CDP:
customersummary table.transaction table. More specifically, it is a combination of Transaction Lines that occur simultaneously.transactionitem table.event table.customer, transaction, transaction item, product, product category, and organization.pets is a new table in the data model and therefore is a custom entity.first name is a standard field on the standard entity customer.preferred pet color is not part of the base schema and therefore is a custom field.exact matching on email address is part of the default IRE rule and therefore is a Standard IRE rule.exact matching on loyalty id is not part of the base set of rules and therefore is a custom IRE rule.Standard Machine Learning Model - A Machine Learning model, which is trained and scored on the customer’s data. The following are the standard models:
For the standard model, the default parameters including input features must be unchanged.
The following are the limitations of CDP:
Data Retention- The data retention applies to the following categories:
| Category | Default Retention | Notes |
|---|---|---|
| Email send events | 6 months | |
| Email events (excludes sends) | 12 months | Includes email opens and clicks. |
| Events in Metrics | 3 months | Events in Metrics can only be filtered for up to 3 months within the retention period. |
| Anonymous events | 6 months | Not stored outside of the sessionization window. |
| Direct mail events | 2 years | Direct mail campaign file includes a list of final recipients of the direct mail campaign and those reserved as holdouts from the campaign. |
| Campaign, template reports, campaign history, cohort analysis | 6 months | Campaign history is only utilized for those customers using legacy. campaigns. |
| Exports | 6 months | Utilized to diagnose errors. |
| Kafka (WebTag) | 7 days | Utilized to diagnose errors. |
| TransactionMessageXRef | 13 months | Utilized to diagnose errors. |
| Web events | 13 months | Capture data from your customer’s interactions with your website or application. |
| Non-event entities (DW and BI) | 3 years | Any other entities not specified previously. |
| FTP | 30 days | Data placed in Acquia’s FTP server. |
| Sparse | 30 days | Internal source for intermediate processing. |
| Exports in S3 and Redshift | N/A | Client responsibility. |
| Machine Learning Studio (CDP Studio Apps) Fair Usage (Package: Small) | |
|---|---|
| Python instance | Up to 720 hours of the Python instance running per month |
| Query instance | Up to 100 hours of Snowflake query execution per month |
| Compute limits | Up to 8 vCPUs for Python and Snowflake instances |
| S3 Storage | Up to 1 GB - S3 Storage only stores metadata. At no point, CDP data must not be stored in S3 |
| Snowflake storage | Up to 1 TB of Snowflake Storage |
| Tenants | Up to one tenant |
| ML Columns | Up to five columns for ML results |
| Machine Learning Studio (CDP Studio Apps) Fair Usage (Package: Medium) | |
|---|---|
| Python instance | Up to 720 hours of the Python instance running per month |
| Query instance | Up to 100 hours of Snowflake query execution per month |
| Compute limits | Up to 32 vCPUs for Python and Snowflake instances |
| S3 Storage | Up to 2 GB - S3 Storage only stores metadata. At no point, CDP data must not be stored in S3 |
| Snowflake storage | Up to 1 TB of Snowflake Storage |
| Tenants | Up to one tenant |
| ML Columns | Up to five columns for ML results |
| Machine Learning Studio (CDP Studio App) Fair Usage (Package: Large) | |
|---|---|
| Python instance | Up to 720 hours of the Python instance running per month |
| Query instance | Up to 100 hours of Snowflake query execution per month |
| Compute limits | Up to 64 vCPUs for Python and Snowflake instances |
| S3 Storage | Up to 3 GB - S3 Storage only stores metadata. At no point, CDP data must not be stored in S3 |
| Snowflake storage | Up to 2 TB of Snowflake Storage |
| Tenants | Up to one tenant |
| ML Columns | Up to five columns for ML results |
| Custom Calculations (CDP Studio Apps) Resource Limit (Package: Small) | |
|---|---|
| Python instance | Up to 240 hours of the Python instance running per month |
| Query instance | Up to 50 hours of Snowflake query execution per month |
| Compute limits | Up to 4 vCPUs for Python and Snowflake instances |
| S3 Storage | Up to 1 GB - S3 Storage only stores metadata. At no point, CDP data must not be stored in S3 |
| Snowflake storage | Up to 0.1 TB of Snowflake Storage |
| Tenants | Up to one tenant |
| Output Columns | Up to five columns for outputs |
| Custom Calculations (CDP Studio Apps) Resource Limit (Package: Medium) | |
|---|---|
| Python instance | Up to 240 hours of the Python instance running per month |
| Query instance | Up to 50 hours of Snowflake query execution per month |
| Compute limits | Up to 16 vCPUs for Python and Snowflake instances |
| S3 Storage | Up to 2 GB - S3 Storage only stores metadata. At no point, CDP data must not be stored in S3 |
| Snowflake storage | Up to 0.5 TB of Snowflake Storage |
| Tenants | Up to one tenant |
| Output Columns | Up to five columns for outputs |
| Custom Calculations (CDP Studio Apps) Resource Limit (Package: Large) | |
|---|---|
| Python instance | Up to 240 hours of the Python instance running per month |
| Query instance | Up to 50 hours of Snowflake query execution per month |
| Compute limits | Up to 32 vCPUs for Python and Snowflake instances |
| S3 Storage | Up to 3 GB - S3 Storage only stores metadata. At no point, CDP data must not be stored in S3 |
| Snowflake storage | Up to one TB of Snowflake Storage |
| Tenants | Up to one tenant |
| Output Columns | Up to five columns for outputs |
Acquia Inc. reserves the right to change the Products and Services Guide based on prevailing market practices and the evolution of our products. Changes will not result in a degradation in the level of services provided during the period for which fees for such services have been paid.
| Date | Update |
| May 20, 2025 | Added quicklinks. |
| May 7, 2025 | Added document changelog. |
If this content did not answer your questions, try searching or contacting our support team for further assistance.