Validate data with Coworker when upgrading from Adobe Analytics to Customer Journey Analytics

Log in to CX Enterprise Coworker.

Select New Chat.

In the text field, prompt the agent to validate your upgrade from Adobe Analytics to Customer Journey Analytics:

Prompt

Help me validate my company’s upgrade from Adobe Analytics to Customer Journey Analytics.

Your request is routed to the data validation skill, which starts an interactive setup process.

The setup process includes the questions in the table below. For each question, select an answer, then select Submit.

Review the setup summary to confirm you’re validating the right data before you continue. The summary includes the company, report suite, and data view you selected, along with a preview of the top metrics and dimensions in each system.

Continue with the following section, Choose the data to validate.

Select from the following options:

Continue with the following section, Review the analysis.

Select the Overall matching rate tab to view a percentage that indicates how closely the data from the Adobe Analytics report suite matches that of the Customer Journey Analytics data view. This score always appears first, before any other results. It weighs every compared metric and dimension equally to ensure that high-volume metrics, such as page views, don’t skew the score.

Use the following scale to interpret the score:

table 0-row-3 1-row-3 2-row-3 3-row-3 4-row-3
Score	Rating	What it means
97%–100%	Excellent	All properties are highly aligned. No action required.
90%–96%	Good	Minor gaps are present. Monitor trends and investigate if they decline.
75%–89%	Review	Meaningful gaps exist. Investigate root causes before relying on Customer Journey Analytics data.
Less than 75%	Poor	Significant misalignment. Take immediate action before using Customer Journey Analytics data.

Select the Key insights tab to view two to four short callout boxes, each summarizing one finding from the analysis in a single sentence. Callouts are color-coded by severity so you can spot the most important findings first.

Select the Summary tab to view Adobe Analytics totals, Customer Journey Analytics totals, total variance, days passing, and days critical, where days passing and days critical reflect how many days in the date range fall into the Pass and Critical variance statuses described below.

(Conditional) When doing a single-dimension comparison or a single-metric comparison, you can view a side-by-side comparison of the Adobe Analytics data and the Customer Journey Analytics data in the Daily trend tab.

For metrics, this is a line chart that compares the daily trend.

For dimensions, this is a bar chart that compares the top values.

(Conditional) When doing a single-dimension comparison or a single-metric comparison, you can view row-level detail in the Date detail tab. This table lists the date, the Adobe Analytics value, the Customer Journey Analytics value, the variance percentage, and a status badge for each compared metric or dimension value.

The variance and status columns use the following scale:

table 0-row-3 1-row-3 2-row-3 3-row-3
Variance	Status	What it means
Less than 3%	Pass	Data is well aligned. No action required.
3%–10%	Flag	Monitor the difference and investigate if it continues or worsens.
Greater than 10%	Critical	Investigate immediately. This usually points to a schema, ingestion, or mapping issue.

(Conditional) When running a full report suite and data view audit, the Daily trend and Daily detail tabs are replaced by a scorecard showing pass, flagged, and critical counts, along with separate tables listing the top five best-matching and top five lowest-matching metrics and dimensions.

Scroll down in the analysis to view additional patterns and issues that were discovered during the analysis, likely causes for those patterns, and suggested actions that you can take to resolve any data discrepancies.

Common issues include:

• Adobe Analytics counts device-based visitors, while Customer Journey Analytics counts people, using cross-device identity stitching.
• Adobe Analytics processes data at collection time, while Customer Journey Analytics processes data at report time.
• Session definitions differ: Adobe Analytics visits use a fixed timeout, while Customer Journey Analytics sessions are configurable.
• Adobe Analytics filters bots by default, while Customer Journey Analytics bot filtering is opt-in.
• Adobe Analytics reports missing values as “Unspecified” or “None,” while Customer Journey Analytics reports them as “No value.”
• Marketing channel differences can result from Adobe Analytics processing rules compared to Customer Journey Analytics derived fields applied retroactively.
• If Customer Journey Analytics values are consistently about twice the Adobe Analytics values across all metrics, this usually indicates duplicate data in the data view rather than an identity stitching effect.

Verify that the suggested actions are valid, then resolve them in Adobe Experience Platform or Adobe Analytics.

(Optional) Continue your analysis by analyzing another metric, analyzing another dimension, or by running another report of up to 40 metrics and 20 dimensions, as described in Choose the data to validate. You don’t need to repeat the setup process to do this; your company, report suite, and data view selections carry forward throughout the conversation.

Continue following the recommended upgrade steps or the dynamically generated upgrade steps in the Customer Journey Analytics Upgrade Guide. 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.