Service Offerings

Customer Data Platform Product Guide - New Packages

Last updated: March 30, 2024

Note

For additional information about Customer Data Platform, see its product documentation.

Overview

With Customer Data Platform (CDP), you can unify, manage, and analyze data from various sources. In addition, you can:

  • Create personalized and targeted marketing campaigns
  • Optimize customer experiences
  • Drive higher engagement
  • Conversion rates across multiple channels

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:

  • Integrations and Data Collection: Seamlessly collect and aggregate data from multiple sources, including CRM, website interactions, and third-party applications. This enables businesses to gather all relevant customer information in one place, laying the foundation for effective data unification.
  • Profiles and Data Unification: Utilize the Identity Resolution Engine to clean, de-duplicate, stitch, and enrich data from all sources, creating a unified customer record for analysis and campaigns. This comprehensive approach ensures a holistic understanding of your customer base, providing valuable insights for marketing and sales efforts. You can access this single view of the customer through a user-friendly interface or an API, which streamlines data management and integration.
  • Analytics and Machine Learning: Gain key insights with fully configurable visual dashboards, reports, and custom report creation capabilities. You can leverage the power of machine learning to generate insights at scale, using both custom and pre-configured models such as likelihood to buy, likelihood to engage, and next best offer.
  • Activation: Orchestrate messages and offers in real-time across all communication channels, such as email, SMS, push, and direct mail. For an integrated approach to customer engagement, you can extend this coordination to customer experience systems, including website personalization engines, customer service, and support systems.
  • Data Governance and Privacy: Facilitate compliance with data protection regulations by implementing strict data governance and privacy measures. Acquia’s Customer Data Platform prioritizes the security and privacy of customer data, providing peace of mind while maintaining transparency and control over data usage.

Features

The following section elaborates the features of CDP:

Activation

Campaigns

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.

Analytics and Machine Learning

Metrics

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

Template Reports is a tool that you use to run and consume custom template reports.

Interactive Queries

Interactive Queries is a SQL Interactive Development Environment (IDE) to query data in CDP for data exploration and data analysis.

Cohort 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

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 App)

Machine Learning Studio (CDP Studio App) 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.

Profiles and Data Unification

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

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 attributes, and custom attributes. Standard calculations and custom calculations are calculated attributes.

Pipelines

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

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 App)

Custom Calculations (CDP Studio App) 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

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.

Integrations and Data Collection

APIs

APIs is a set of the following modules:

  • 360 API - API to query an individual customer
  • Tracker API - API to ingest data in the CDP
  • WebTag - Captures data from your customer’s interactions with your web site or application

Data Export

Data Export is a set of configurable modules that exports or shares data outside CDP. The following are the three modules of data export:

  • Cloud data export
  • Snowflake data share
  • Interactive Queries export

Governance and Privacy

Access Management

Access Management is a tool to manage users, roles, and permissions in CDP.

Data Retention

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

Data Erasure is a set of tools to manage data erasure requests for user records in CDP.

Definitions

The following are the definitions of terminology used in CDP:

  • Profile - A row in the customersummary table.
  • Active Profile (formerly “Active Customer”) - A unique buyer who has conducted a Transaction within the prior 12 months and with an identified email address, postal address, phone number, or a combination. Anonymous buyers are tracked but not counted as an Active Profile until they have identified themselves with an email address, postal address, phone number, or a combination.
  • Transaction - A defined type of activity, such as a purchase, doctor’s appointment, lunch outing, form response, or other type of prescribed interaction, that is recorded in CDP’s transaction table. More specifically, it is a combination of Transaction Lines that occur simultaneously.
  • Transaction Line - A row in the transactionitem table.
  • Event - An entry in the event table.
  • Standard Entity - A table in the CDP data model. The list of standard entities are customer, transaction, transaction item, product, product category, and organization.
  • Custom Entity - A table in the CDP data model that is not in the standard entity list. For example, pets is a new table in the data model and therefore is a custom entity.
  • Standard Field - A column in the CDP data model that belongs to a standard entity in the base schema. For example, first name is a standard field on the standard entity customer.
  • Custom Field - A column in the CDP data model that is added to the base schema. For example, preferred pet color is not part of the base schema and therefore is a custom field.
  • Standard IRE Rule - An Identity Resolution rule that belongs to the base set of IRE rules. For example, exact matching on email address is part of the default IRE rule and therefore is a Standard IRE rule.
  • Custom IRE Rule -An Identity Resolution rule that is added to the set of IRE rules. For example, exact matching on loyalty id is not part of the base set of rules and therefore is a custom IRE rule.
  • Standard Calculation - A transformation that computes the value of a standard field. For example, lifetime revenue or purchase frequency are standard calculations.
  • Custom Calculation - A transformation that computes the value of a custom field. For example, lifetime revenue or purchase frequency are standard calculations.
  • Standard Data Feed - An input data file that follows all the rules in the Acquia file specifications documentation hosted on docs.acquia.com.
  • Custom Data Feed - An input data file that does not follow all rules in the Acquia file specifications documentation.
  • Standard Dashboard- A set of pre-built charts by Acquia in Metrics.
  • Custom Dashboard- A set of pre-built charts by the customer in Metrics.
  • Template Report - A template report represents an SQL based parameterizable report built by Acquia based on the customer’s specifications.
  • Batch Pipeline - A set of data that computes heavy processes to ingest, process and surface data in CDP on schedule.
  • Real-Time Pipeline -A set of data processes to ingest, process and surface data in the CDP as a stream.
  • Standard Machine Learning Model - A Machine Learning model, which is trained and scored on the customer’s data. The following are the standard models:

    • Likelihood to Buy
    • Likelihood to Convert
    • Likelihood to Pay Full Price
    • Likelihood to Engage on Email
    • Predictive Lifetime Value
    • Behavioral Clustering
    • Product Clustering
    • Fuzzy Clustering
    • Next Best Product
    • Next Nest Channel
    • Next Best Send Time

    For the standard model, the default parameters including input features must be unchanged.

  • Custom Machine Learning Model - A Machine Learning model that does not meet the requirements to be considered a standard model.
  • Tenant - A single instance of CDP ensuring isolation of the customer’s data, configurations, and customizations.
  • CDP Studio App: An application that includes the following self-service features:
    • Custom attributes
    • Custom calculations
    • Custom machine learning models

Limitations

The following are the limitations of CDP:

  • Pipeline - The batch pipeline runs once a day.
  • Data Retention- The data retention applies to the following categories:

    CategoryDefault RetentionNotes
    Email send events6 months 
    Email events (excludes sends)13 monthsIncludes email opens and clicks.
    Anonymous events6 monthsNot stored outside of the sessionization window.
    Direct mail events2 yearsDirect 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 analysis6 monthsCampaign history is only utilized for those customers using legacy. campaigns.
    Exports6 monthsUtilized to diagnose errors.
    Kafka (webtag)7 daysUtilized to diagnose errors.
    TransactionMessageXRef13 monthsUtilized to diagnose errors.
    Web events13 monthsCapture data from your customer’s interactions with your website or application.
    Non-event entities (DW and BI)3 yearsAny other entities not specified previously.
    FTP30 daysData placed in Acquia’s FTP server.
    Sparse30 daysInternal source for intermediate processing.
    Exports in S3 and RedshiftN/AClient responsibility.

Machine Learning Studio  (CDP Studio App)

Machine Learning Studio (CDP Studio App) Fair Usage (Package: Small)
Python instanceUp to 720 hours of the Python instance running per month
Query instanceUp to 100 hours of Snowflake query execution per month
Compute limitsUp to 8 vCPUs for Python and Snowflake instances
S3 StorageUp to 1 GB - S3 Storage only stores metadata. At no point, CDP data must not be stored in S3
Snowflake storageUp to 1 TB of Snowflake Storage
TenantsUp to one tenant
ML ColumnsUp to five columns for ML results
Machine Learning Studio (CDP Studio App) Fair Usage (Package: Medium)
Python instanceUp to 720 hours of the Python instance running per month
Query instanceUp to 100 hours of Snowflake query execution per month
Compute limitsUp to 32 vCPUs for Python and Snowflake instances
S3 StorageUp to 2 GB - S3 Storage only stores metadata. At no point, CDP data must not be stored in S3
Snowflake storageUp to 1 TB of Snowflake Storage
TenantsUp to one tenant
ML ColumnsUp to five columns for ML results
Machine Learning Studio (CDP Studio App) Fair Usage (Package: Large)
Python instanceUp to 720 hours of the Python instance running per month
Query instanceUp to 100 hours of Snowflake query execution per month
Compute limitsUp to 64 vCPUs for Python and Snowflake instances
S3 StorageUp to 3 GB - S3 Storage only stores metadata. At no point, CDP data must not be stored in S3
Snowflake storageUp to 2 TB of Snowflake Storage
TenantsUp to one tenant
ML ColumnsUp to five columns for ML results

Custom Calculations (CDP Studio App)

Custom Calculations (CDP Studio App) Resource Limit (Package: Small)
Python instanceUp to 240 hours of the Python instance running per month
Query instanceUp to 50 hours of Snowflake query execution per month
Compute limitsUp to 4 vCPUs for Python and Snowflake instances
S3 StorageUp to 1 GB - S3 Storage only stores metadata. At no point, CDP data must not be stored in S3
Snowflake storageUp to 0.1 TB of Snowflake Storage
TenantsUp to one tenant
Output ColumnsUp to five columns for outputs
Custom Calculations (CDP Studio App) Resource Limit (Package: Medium)
Python instanceUp to 240 hours of the Python instance running per month
Query instanceUp to 50 hours of Snowflake query execution per month
Compute limitsUp to 16 vCPUs for Python and Snowflake instances
S3 StorageUp to 2 GB - S3 Storage only stores metadata. At no point, CDP data must not be stored in S3
Snowflake storageUp to 0.5 TB of Snowflake Storage
TenantsUp to one tenant
Output ColumnsUp to five columns for outputs
Custom Calculations (CDP Studio App) Resource Limit (Package: Large)
Python instanceUp to 240 hours of the Python instance running per month
Query instanceUp to 50 hours of Snowflake query execution per month
Compute limitsUp to 32 vCPUs for Python and Snowflake instances
S3 StorageUp to 3 GB - S3 Storage only stores metadata. At no point, CDP data must not be stored in S3
Snowflake storageUp to one TB of Snowflake Storage
TenantsUp to one tenant
Output ColumnsUp 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.