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DocumentationCustomer Journey AnalyticsCustomer Journey Analytics Guide

Upgrade from ÃÛ¶¹ÊÓƵ Analytics to Customer Journey Analytics

Last update: Tue Apr 08 2025 00:00:00 GMT+0000 (Coordinated Universal Time)

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When upgrading from ÃÛ¶¹ÊÓƵ Analytics to Customer Journey Analytics, you can follow the recommended upgrade steps. Or you can dynamically generate upgrade steps for your organization’s unique circumstances.

The recommended process of upgrading from ÃÛ¶¹ÊÓƵ Analytics to Customer Journey Analytics is a new implementation of the Experience Platform Web SDK, which is the preferred data collection method for Customer Journey Analytics. In conjunction with the Web SDK, ÃÛ¶¹ÊÓƵ also recommends using the Analytics source connector to help with your transition to Customer Journey Analytics. Use the Analytics source connector to retain historical ÃÛ¶¹ÊÓƵ Analytics data and to perform side-by-side data comparison.

After you have enough historical data using the Experience Platform Web SDK and you have fully transitioned to Customer Journey Analytics, the Analytics source connector can be turned off and the Web SDK can be used exclusively.

NOTE
If the upgrade steps described in this section are not practical for your organization, use the Customer Journey Analytics Upgrade Guide to dynamically generate upgrade steps that are tailored to your organization’s unique circumstances. (To access the guide from Customer Journey Analytics, select the Workspace tab, then select Upgrade to Customer Journey Analytics in the left panel. Follow the on-screen instructions.)

  1. Implement the Experience Platform Web SDK (for ongoing data collection)

    A new implementation of the Experience Platform Web SDK is the best way to collect data for Customer Journey Analytics. It provides the best foundation to get the most out of Customer Journey Analytics because it is the most performant, straightforward, and future-proof method for implementing Customer Journey Analytics.

    • Highly performant reporting and data availability because ÃÛ¶¹ÊÓƵ Experience Platform is built to power real-time personalization use cases

    • Consolidate implementation for ÃÛ¶¹ÊÓƵ Experience Cloud data collection between other Experience Cloud products (AJO, RTCDP, and so forth)

    • Not reliant on ÃÛ¶¹ÊÓƵ Analytics nomenclature (prop, eVar, event, and so forth)

  2. Set up the ÃÛ¶¹ÊÓƵ Analytics source connector (for bringing over historical data)

    To help with a smooth transition to using the Experience Platform Web SDK with Customer Journey Analytics, ÃÛ¶¹ÊÓƵ also recommends using the ÃÛ¶¹ÊÓƵ Analytics source connector. This allows you to retain historical data and view data from your existing ÃÛ¶¹ÊÓƵ Analytics implementation in Customer Journey Analytics, side by side with the data from your new Experience Platform Web SDK implementation.

    The Analytics source connector allows you to:

    • Bring your historical ÃÛ¶¹ÊÓƵ Analytics report suite data into ÃÛ¶¹ÊÓƵ Experience Platform and Customer Journey Analytics.

      You can keep the Analytics source connector running for as long as you need to retain the historical ÃÛ¶¹ÊÓƵ Analytics data.

    • View the data collected with your original ÃÛ¶¹ÊÓƵ Analytics implementation (either AppMeasurement, the Analytics Extension, or the Web SDK Extension) within Customer Journey Analytics. You can compare this data side-by-side with that of your new Web SDK implementation.

      You can keep the Analytics source connector running until you are familiar and comfortable with the differences.

    The Analytics source connector as a stand-alone implementation is not a recommended long-term method for using Customer Journey Analytics. This is because of high latency, cluttered and complex schemas, reliance on ÃÛ¶¹ÊÓƵ Analytics nomenclature (prop, eVar, and so forth), and difficulty in eventually moving from the Analytics source connector to the recommended Web SDK implementation.

The following steps outline the recommended process for upgrading from ÃÛ¶¹ÊÓƵ Analytics to Customer Journey Analytics.

Each step provides a high-level explanation of a more detailed process. Follow the link for each step and complete its associated tasks, then return to this page and continue to the next step in the process.

  1. Plan your XDM schema architecture.

  2. Create your desired custom schema in ÃÛ¶¹ÊÓƵ Experience Platform.

    Consider the following options when creating your schema:

  3. Create a dataset in ÃÛ¶¹ÊÓƵ Experience Platform.

  4. (Optional) If you use classification data in ÃÛ¶¹ÊÓƵ Analytics, you can add classification data to your dataset in Customer Journey Analytics.

    To do this, create a lookup dataset for each dimension containing classification data.

  5. For ÃÛ¶¹ÊÓƵ Analytics implementations using AppMeasurement or the Analytics extension (tags), create a datastream in ÃÛ¶¹ÊÓƵ Experience Platform.

    For ÃÛ¶¹ÊÓƵ Analytics implementations using the Web SDK, a datastream already exists. For more information, see Configure your existing ÃÛ¶¹ÊÓƵ Analytics Web SDK implementation to send data to Platform.

  6. Add ÃÛ¶¹ÊÓƵ Experience Platform as a service to your datastream.

  7. (Optional) If you want to integrate Customer Journey Analytics with ÃÛ¶¹ÊÓƵ Journey Optimizer, use the personalization object in your implementation for use in ÃÛ¶¹ÊÓƵ Journey Optimizer.

  8. Expand the section that describes how you want to implement the Experience Platform Web SDK for your Customer Journey Analytics implementation, then complete the associated steps:

    accordion
    Manual implementation (JS file)

    1. Add alloy.js to your site.

    2. Populate an XDM object and send it to the datastream.
    accordion
    Tags

    1. Create a tag property and add the ÃÛ¶¹ÊÓƵ Experience Platform Web SDK extension.

    2. Add the ÃÛ¶¹ÊÓƵ Experience Platform Web SDK extension to your tag property

    3. Implement the loader tag on your site.

    4. Add XDM data collection logic to your tag.
    accordion
    API
    1. Use the Edge Network API to send data to the desired datastream.

  9. Validate that your Web SDK implementation is sending data to a dataset.

  10. Create a connection in Customer Journey Analytics.

  11. (Optional) Tie web data with data from other channels, such as call center data.

    You accomplish this by adding additional datasets to your Customer Journey Analytics connection, as described in Import call center and web data.

  12. Create a data view in Customer Journey Analytics.

  13. Validate that data is flowing into the data view in Customer Journey Analytics.

  14. In your ÃÛ¶¹ÊÓƵ Analytics environment, use the Analytics Inventory to see a comprehensive overview of your ÃÛ¶¹ÊÓƵ Analytics environment, including the number of projects and components, report suites, users, and more.

  15. Migrate projects and components.

  16. (Optional) If you use marketing channels in ÃÛ¶¹ÊÓƵ Analytics, you can create a marketing channel derived field in Customer Journey Analytics.

    Derived fields are an important aspect of the real-time reporting in Customer Journey Analytics. A derived field allows you to define (often complex) data manipulations on the fly, through a customizable rule builder.

    One use for derived fields is to define a derived Marketing Channel field that determines the proper marketing channel based on one or more conditions (for example, URL parameter, page URL, or page name).

    Use the marketing channels function template in derived fields to quickly create a derived field for marketing channels.

  17. Compare data in ÃÛ¶¹ÊÓƵ Analytics from your old implementation to data in Customer Journey Analytics from your new implementation and make sure you understand any differences and why they exist.

  18. Bring historical data from ÃÛ¶¹ÊÓƵ Analytics using the Analytics source connector:

    note note
    NOTE
    Use the following steps if you have not previously created an Analytics source connector.
    If you are already using the Analytics source connector with Customer Journey Analytics, follow the steps in Transition from the Analytics source connector to the Web SDK for Customer Journey Analytics.

    1. Create an XDM schema for the Analytics source connector

    2. If you don’t already have an Analytics source connector, create the Analytics source connector and map fields to your XDM schema.

      Or

      If you already have an Analytics source connector, map fields from the source connector to your XDM schema.

    3. Add the Analytics source connector dataset to the connection.

  19. Plan user onboarding.

    Like in ÃÛ¶¹ÊÓƵ Analytics, Analysis Workspace is the main user-facing tool in Customer Journey Analytics. However, there are some key differences when using Analysis Workspace in Customer Journey Analytics that users need to be aware of.

    You should give your users ample time (3 - 6 months) to become familiar with the key differences of Analysis Workspace in Customer Journey Analytics.

    For information about some of the key differences between ÃÛ¶¹ÊÓƵ Analytics and Customer Journey Analytics, see User Guide for ÃÛ¶¹ÊÓƵ Analytics users.

  20. Learn about feature support in Customer Journey Analytics. Most ÃÛ¶¹ÊÓƵ Analytics features are supported in Customer Journey Analytics, and many additional features are available in Customer Journey Analytics.

  21. Disable ÃÛ¶¹ÊÓƵ Analytics when your Customer Journey Analytics Web SDK implementation is complete and you are comfortable with the data that you are collecting.

    ÃÛ¶¹ÊÓƵ recommends that you keep your ÃÛ¶¹ÊÓƵ Analytics environment running for a period of time after implementing Customer Journey Analytics.

    For more information about the uses of ÃÛ¶¹ÊÓƵ Analytics during and after an upgrade, as well as the suggested timing of disabling ÃÛ¶¹ÊÓƵ Analytics, see Evaluate how long you need ÃÛ¶¹ÊÓƵ Analytics after upgrading to Customer Journey Analytics.

Dynamically generate upgrade steps for your organization

Depending on several factors, such as timeline and resource constraints, the recommended upgrade steps described in Understand the recommended upgrade steps might not be practical for your organization. In this case, you can dynamically generate upgrade steps for your organization’s unique circumstances. The process of generating these steps differs depending on whether you already have access to Customer Journey Analytics.

For customers who have access to Customer Journey Analytics

To dynamically generate upgrade steps for your organization’s unique circumstances:

  1. Complete the Customer Journey Analytics Upgrade Guide.

    In Customer Journey Analytics, select the Workspace tab, then select Upgrade to Customer Journey Analytics in the left panel. Follow the on-screen instructions.

    After completing this upgrade guide, step-by-step instructions are provided to you, outlining the optimal upgrade steps that are unique to your organization requirements. These are the upgrade steps that best align with your existing ÃÛ¶¹ÊÓƵ Analytics environment and your goals for Customer Journey Analytics. The upgrade steps are available as a shareable link or as a downloadable .csv file.

  2. Follow the generated step-by-step instructions to upgrade to Customer Journey Analytics.

For customers who do not yet have access to Customer Journey Analytics

To dynamically generate upgrade steps for your organization’s unique circumstances:

  1. Contact your ÃÛ¶¹ÊÓƵ Account Team to complete the Customer Journey Analytics Upgrade Guide.

    Your ÃÛ¶¹ÊÓƵ Account Team can take you through the upgrade guide and provide you with a .csv file that contains the questions, your answers, and the dynamically generated upgrade steps that are unique to your organization.

    Prior to contacting your ÃÛ¶¹ÊÓƵ Account Team, familiarize yourself with the questions that are included in the Customer Journey Analytics Upgrade Guide and determine your answers. The Customer Journey Analytics Upgrade Guide contains the following questions and possible answers:

    table 0-row-3 1-row-3 2-row-3 3-row-3 4-row-3 5-row-3 6-row-3 7-row-3
    Question Available answers Additional information
    Select the option that describes your current ÃÛ¶¹ÊÓƵ Analytics implementation. This information can affect alternative upgrade options that might be available to you when upgrading to Customer Journey Analytics.

    Select one:

    • AppMeasurement:
      A JavaScript implementation that loads AppMeasurement.js on a page, and sends data to ÃÛ¶¹ÊÓƵ using the s object (for example, s.eVar1).
    • ÃÛ¶¹ÊÓƵ Analytics extension (tags):
      A tags implementation that loads ÃÛ¶¹ÊÓƵ Experience Platform Data Collection (formerly known as Launch). The tag has the ÃÛ¶¹ÊÓƵ Analytics extension installed.
    • Experience Platform Web SDK extension (tags):
      A tags implementation that loads ÃÛ¶¹ÊÓƵ Experience Platform Data Collection (formerly known as Launch). The tag has the Web SDK extension installed.
    • Experience Platform Web SDK (alloy.js): A JavaScript implementation that loads the Web SDK library (alloy.js) on a page, and sends data to ÃÛ¶¹ÊÓƵ using a JSON payload.
    • Bulk Data Insertion API:
      An implementation that uses the data insertion API or bulk data insertion API.
    • Experience Platform Mobile SDK:
      An implementation that uses the ÃÛ¶¹ÊÓƵ Experience Platform Mobile SDK.
    • AppMeasurement using a third-party tag management tool:
      An implementation that uses a third-party tag management tool.
    • A non-ÃÛ¶¹ÊÓƵ Analytics product:
      An implementation that collects data for a product other than ÃÛ¶¹ÊÓƵ Analytics, such as Google Analytics. Selecting this option disables several options in the upgrade guide that don’t apply when upgrading to Customer Journey Analytics from a non-ÃÛ¶¹ÊÓƵ Analytics product.
    • I don’t know:
      If you’re not the person that manages your implementation, you can temporarily select this option.

    Select if applicable:

    • Our implementation currently uses the Analytics source connecto:
      The Analytics source connector allows you to easily get value from Customer Journey Analytics, but requires that you pay for both ÃÛ¶¹ÊÓƵ Analytics and Customer Journey Analytics. This guide can help you move towards an independent Web SDK implementation.
    Most ÃÛ¶¹ÊÓƵ Analytics features are readily available in Customer Journey Analytics. However, the following features require consideration during the upgrade process. Select any that you plan to use.

    Select all that apply:

    • Historical data from ÃÛ¶¹ÊÓƵ Analytics:
      Bring your historical ÃÛ¶¹ÊÓƵ Analytics report suite data into ÃÛ¶¹ÊÓƵ Experience Platform and Customer Journey Analytics.
    • Components and projects from ÃÛ¶¹ÊÓƵ Analytics:
      Components from ÃÛ¶¹ÊÓƵ Analytics include: Projects (with their associated freeform tables and visualizations), segments, and calculated metrics.
    • Acivity map overlay and link tracking:
      A browser extension that allows you to see link tracking data as an overlay on your site.
    • Classification data:
      Group or categorize data as separate dimensions.
    • Marketing channels:
      Create rules that categorize how customers arrive on your site.
    • Data Warehouse:
      Export processed data from ÃÛ¶¹ÊÓƵ Analytics in spreadsheet format.
    • **Data Feeds:**An exact replacement for Data Feeds is not yet available in Customer Journey Analytics. However, similar functionality can be achieved with capabilities such as full table export, Platform dataset export, BI tool integration, and the reporting API.
    • Streaming media data:
      An add-on to ÃÛ¶¹ÊÓƵ Analytics and Customer Journey Analytics that specializes in data collection of media, such as audio, video, or streamed content.
    Most new features are readily available in Customer Journey Analytics. However, the following features require consideration during the upgrade process. Select any that you plan to use.

    Select all that apply:

    • Tie collected data with data from other sources (e.x. contact center data):
      (Recommended) Tie data from various web, mobile, and offline properties to create a single, consolidated view of customer behavior. This ability to combine analytics data from other channels is the primary use case for Customer Journey Analytics.
    • Stitch hits from other datasets using a custom dimension:
      If any of your datasets don’t share a primary identifier (such as an Experience Cloud ID), you can still stitch that data together using another dimension, such as login username or email address.
    • Integrate with ÃÛ¶¹ÊÓƵ Journey Optimizer:
      Deliver connected, contextual, and personalized experiences to customers.
    • Integrate with ÃÛ¶¹ÊÓƵ Real-Time CDP:
      Combine profile data from multiple sources to generate audiences and segments based on user traits.
    • Integrate with ÃÛ¶¹ÊÓƵ Target (A4T):
      ÃÛ¶¹ÊÓƵ recommends integrating with ÃÛ¶¹ÊÓƵ Journey Optimizer for personalization use cases. Integrating with ÃÛ¶¹ÊÓƵ Target is possible, but a short-term solution.
    • Integrate with ÃÛ¶¹ÊÓƵ Audience Manager:
      ÃÛ¶¹ÊÓƵ recommends integrating with ÃÛ¶¹ÊÓƵ Real-time CDP for audience-based use cases. Integrating with Audience Manager is possible, but a short-term solution.
    		 Understand features unique to Customer Journey Analytics
    Select how you plan to ultimately use ÃÛ¶¹ÊÓƵ Analytics and Customer Journey Analytics:

    Select one:

    • I intend to fully move to Customer Journey Analytics from ÃÛ¶¹ÊÓƵ Analytics:
      (Recommended) ÃÛ¶¹ÊÓƵ recommends that you transition fully from ÃÛ¶¹ÊÓƵ Analytics to Customer Journey Analytics. During the transition period, you should plan to run ÃÛ¶¹ÊÓƵ Analytics alongside Customer Journey Analytics in order to perform side-by-side data comparisons. When you are comfortable with the data, you can disable ÃÛ¶¹ÊÓƵ Analytics.
    • I intend to keep both Analytics products:
      (Not recommended) If you select this option, your contract with ÃÛ¶¹ÊÓƵ includes both ÃÛ¶¹ÊÓƵ Analytics and Customer Journey Analytics, which can be more expensive for your organization over time.
    		 Evaluate when to disable ÃÛ¶¹ÊÓƵ Analytics after upgrading to Customer Journey Analytics
    Select how you want to configure your Customer Journey Analytics schema:

    Select one:

    • I want to use a schema tailored to my organization:
      (Recommended) Customizing your schema allows your organization to track only what you need and avoid the overhead tied to messy and unneeded fields. This option includes field groups added by the Web SDK and field groups custom to your organization.
    • I want to use the default ÃÛ¶¹ÊÓƵ Analytics schema:
      (Not recommended) The ÃÛ¶¹ÊÓƵ Analytics schema contains more than a thousand fields, which can lead to cluttered and complex schema. Your organization would be forced to continue adhering to the concept of props and eVars, which is a legacy concept not used in Customer Journey Analytics. Integrating with other ÃÛ¶¹ÊÓƵ Experience Platform services is more difficult.
    		 Choose your schema for Customer Journey Analytics
    Select your preferred way of implementing Customer Journey Analytics:
    • Manual implementation (alloy.js):
      Include the Web SDK library (alloy.js) on each page your site.
    • Tags:
      (Recommended) If you are not yet using Tags, install the tag loader on your site. If you are already using Tags, you can add the Web SDK extension to your tag property. This option includes implementations using tags within ÃÛ¶¹ÊÓƵ Experience Platform Data Collection and third-party tag management systems.
    • API:
      Use the data collection API to send data directly to a datastream. Both non-authenticated (client-to-server) and authenticated (server-to-server) types are supported.
    		 Understand Web SDK implementation options when upgrading to Customer Journey Analytics
    (Optional) Select an alternative upgrade method

    • Soley use the Analytics source connector:
      (Not recommended) You can use the Analytics source connector as the sole implementation path for Customer Journey Analytics.

      This option saves implementation time by quickly sending data to Customer Journey Analytics. However, it includes various shortcomings, such as higher latency and difficulty moving off of ÃÛ¶¹ÊÓƵ Analytics in the future.

    • I want to use my AppMeasurement logic with the Web SDK:
      Instead of sending data through an XDM object, send all your variables in AppMeasurement format through the data object.

      This option saves implementation time by allowing you to map your AppMeasurement logic to XDM, rather than populating an XDM object from scratch. However, it introduces additional complexity over time because any field you add in the future must be mapped to XDM in the datastream.

    • I want to send my data layer to ÃÛ¶¹ÊÓƵ without additional configuration:
      Instead of sending data through an XDM object, you can send your entire data layer to ÃÛ¶¹ÊÓƵ through the data object.

      This option saves implementation time by allowing you to map your data layer to XDM, rather than populating an XDM object from scratch. However, this mapping is a large amount of work because there will be a significant amount of data that ÃÛ¶¹ÊÓƵ can’t readily interpret. This option also introduces additional complexity over time because any field you add to your data later in the future must be mapped to XDM in the datastream.

    After completing this upgrade guide with your ÃÛ¶¹ÊÓƵ Account Team, you will be provided with a .csv file that contains the questions, your answers, and the dynamically generated upgrade steps that best align with your existing ÃÛ¶¹ÊÓƵ Analytics environment and your goals for Customer Journey Analytics.

  2. Follow the generated step-by-step instructions in the .csv file to upgrade to Customer Journey Analytics.

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