CJA Compare percentages, concise labels and auto descriptions

The October 2026 Customer Journey Analytics notes are mostly about making existing analysis easier to read, easier to compare and easier to govern. Journey canvas gets a fairer way to compare periods, charts get shorter legends, components can describe themselves, and Adobe Brand Visibility now connects to your CJA data. None of it needs a re-implementation, but a few items deserve a deliberate decision before analysts start clicking.

Key takeaways

• Compare percentages on Journey canvas (generally available 19 October 2026) shows percentage-point change per node, arrow and fallout, so period comparisons stay fair when volumes differ.
• Concise labels (generally available 29 October 2026) is off by default, so existing dashboards look the same until someone turns it on.
• Automatic descriptions for components start rolling out on 29 October 2026 and reach general availability on 18 November 2026. Review what it writes before you trust it.
• The Adobe Brand Visibility integration became generally available on 8 October 2026 and links AI-driven discovery to website engagement in your CJA data.
• Coworker now appears in Analysis Workspace and in Content Analytics questions. The Content Analytics dates are not final, so plan pilots rather than commitments.

What Compare percentages changes on a Journey canvas

Journey canvas could already compare a journey with a prior period. The trouble was always volume. If last quarter had 80,000 people entering the journey and this quarter had 120,000, raw counts told you almost nothing about whether the journey got better.

The new Compare percentages option, generally available from 19 October 2026, shows the change in percentage points for each node, arrow and fallout. That matters most for rates: retention from one node to the next, or fallout at a step. A move from 40 percent to 44 percent reads as four points, whatever the audience size was in either period.

A worked example. A subscription team compares the weeks before and after a pricing page redesign. Traffic doubled because of a campaign. Raw comparison shows every node up, which is true and useless. With percentage-point comparison, the team can see that the fallout between the pricing page and the plan selection step improved by a few points while the step after it got slightly worse. That is a finding. The raw view hid it.

Who it affects: anyone who presents journey comparisons to non-analysts. Product managers and CX leads tend to read the canvas directly, so the change lands on them as much as on the analysts who built it.

What to do: open your two or three most-shared journey projects, enable the option on the comparison view, and check whether the story you have been telling changes. Do this before the next review meeting, not during it.

Concise legend labels: small setting, real readability gain

Anyone who has built a chart with three segments, two metrics and two date ranges knows the legend problem. Every label repeats the same long names, and the part that differs is hidden or visible only on hover.

The Concise labels setting, generally available from 29 October 2026, drops the names that every label shares and keeps what tells them apart. It is off by default. It applies to area, bar, combo, donut, histogram, horizontal bar, line and Venn visualizations, including stacked versions.

Two practical points follow from that.

1. Nothing changes on its own. Existing projects, scheduled deliveries and shared dashboards keep their current legends until someone switches the setting on.
2. The shortened label depends on what is shared. If you later add a fourth series that shares less with the others, the legend can read differently. Check any chart you have already pasted into a slide deck.

One trade-off worth naming. A concise legend is better for a reader who already knows the context and worse for someone who sees the chart without its title. If the chart will be screenshotted into an email, keep the full labels or put the shared context in the chart title. Treat this as a presentation choice, not a standard to impose on every project.

There is no reason to run a project around it. Turn it on for the dense charts that were hard to read, leave the rest alone.

Automatic descriptions for components and projects

Large CJA implementations accumulate components. Hundreds of dimensions, a long list of calculated metrics, segments built by people who have since left. Most of them have no description, or a description that says 'test'. New analysts guess.

Adobe now lets you generate descriptions for dimensions, metrics, calculated metrics, segments and date ranges. You can do it for one component or for many at once. You can also generate a description for a Workspace project when you save it, or from Project info and settings. Rollout starts on 29 October 2026, and general availability is listed as 18 November 2026. Until the second date, expect the feature to appear for some users before others.

This is a documentation shortcut, not a governance process. A generated description tells a reader what a component appears to be. It cannot know that a calculated metric excludes internal traffic by agreement with finance, or that a segment was built for one campaign and should not be reused. Those facts live in your team's heads.

A sensible way to use it:

• Run it in bulk on the components that currently have no description, and only those.
• Have the component owner, or a data steward, read each result. Fix anything that is wrong or vague.
• Leave existing human-written descriptions alone unless they are clearly stale.
• Record the business rule behind any calculated metric in the description yourself, even if the generated text is acceptable.

The risk is a library that looks documented and is not. A confident, slightly wrong description is worse than an empty one, because nobody questions it. Plan a review step, and give it an owner and a date.

Adobe Brand Visibility integration

The Adobe Brand Visibility integration, generally available from 8 October 2026, connects Brand Visibility with your Customer Journey Analytics data. The stated aim is to measure how AI-driven discovery turns into website engagement and business outcomes.

For teams already asking where their traffic from AI assistants and answer engines goes after the click, this is the first place to look. The question it helps answer is practical: do people who arrive through that kind of discovery behave differently from people who arrive through search or paid media? Do they convert, return, or leave at the first step?

What the notes do not say is how the connection is configured, what data flows in each direction, or what it needs on the licensing side. Read the Adobe Brand Visibility integration page on Experience League before scoping any work, and check entitlement with your Adobe account team.

If you do pilot it, keep the first test narrow. Pick one market or one product line, define the outcome you care about before you look at the data, and compare against a baseline you trust. A broad launch across every property makes it hard to tell whether the integration is useful or whether you are just looking at new charts.

Coworker in Workspace and Content Analytics

Two items in the notes concern Coworker. The in-product experience puts Coworker in a chat panel inside Analysis Workspace. It uses the project you have open as context, so you do not need to explain what the project contains. According to the notes, you can use it to summarize the open project, find insights and run root cause analysis, and to build and edit the project with natural-language prompts: adding panels and tables, breaking down data, changing visualization types and date ranges. The copy of the notes available to us is cut off partway through that list, so check the Experience League page for the full list and for its dates.

The second is Coworker Chat for Content Analytics, in the CX Enterprise Coworker entry. Rollout starts 14 October 2026, and general availability is listed as TBD. Users can ask a specific question, such as which images drove the most revenue last quarter, or a broader one about what content to prioritize.

The position worth taking: use these as a way to get marketers to the first draft faster, not as a replacement for an analyst's judgment. A natural-language build still produces a project that someone has to check. A summary still reflects the data views and components behind it. If your components are poorly named and undocumented, an assistant will work from the same mess your people do. That is a good reason to treat the description feature above as groundwork.

Because general availability for the Content Analytics piece is still to be determined, do not put it in a roadmap with a date.

A rollout plan with owners

None of these changes needs a project plan. A short checklist is enough.

Sequence matters a little. Do the descriptions first, because it improves everything else. Then the presentation settings, which take minutes. Hold the integration and Coworker pilots until someone owns the questions you want answered.

How to measure whether any of it helped

You cannot measure a legend setting with a KPI, and you should not try. Measure the things these features are supposed to move.

• Time to a trusted answer. Pick three recurring questions, such as the weekly funnel review. Note how long a new analyst takes to find the right component and chart before and after descriptions are in place.
• Misuse of components. Count the support questions asking which metric to use. If descriptions work, they should fall.
• Review quality. In journey reviews, track how often a reported change turns out to be a volume effect rather than a behaviour change. With percentage-point comparison, it should happen less.
• Pilot outcomes. For Brand Visibility, define the outcome and the comparison group in writing before you start.

Be honest about attribution. A better-documented library and a clearer canvas will not move a conversion rate on their own. They improve decisions, and that shows up slowly.

Where a partner helps and where you do not need one

You do not need outside help to turn on Compare percentages or Concise labels. They are settings. Do them yourself this week.

Bulk descriptions are also doable in-house if you have a named steward. A partner earns its fee when the component library itself is the problem: duplicate calculated metrics, inconsistent naming across data views, segments nobody owns. Cleaning that up before you generate descriptions is a design job, and an experienced consultant will do it faster than a team learning on the job. If you are choosing one, the Customer Journey Analytics partners page and the shortlist of top partners are useful starting points.

The Brand Visibility integration is the other place where help can pay off, mainly in the scoping: which data views, which identities, which outcomes. If you do go to market, the Customer Journey Analytics RFP template keeps the brief specific, and find-partners lets you filter by capability.

What not to do

Do not switch Concise labels on across every project as a house style. Do not publish generated descriptions without reading them. Do not tell leadership that an AI-discovery integration will explain your traffic before you have run a narrow pilot. And do not plan around dates the notes mark as TBD.

The notes update several times a month under Adobe's continuous delivery model, so check the Experience League page again before you finalise any rollout. Entries can move: one item in this release was originally planned for an earlier date and slipped.

Sources

• Adobe Experience League: Current Customer Journey Analytics release notes — October 2026 release period, last updated 2 November 2026. Source for every feature name and date in this post.