Adobe Journey Optimizer

Hi Everyone,I am not able to find where I can get the contextual data from API triggered campaign payload within AEP/AJO datasets after email sent out.Normally you would see some metadata on AJO Interactive Messaging Profile Dataset, however I could not find contextual data in it. Thanks!

Hi ,we are working on ajo web channel personalizarion to show real time banners. while workign we found that we cant uise event contextual attributes inside web channel. we need to call aem content fragment based on the current page url which user has visited.is it possible to use window.location.href ? will it fetches the current browser url so that we can pass this as input to content fragment.Please help with inputs . ThanksUsha

Hi everyone,We are trying to better understand the actual behavior of the “Trigger after batch audience evaluation” option in AJO, because in our case it does not seem to behave the way the documentation and UI tooltip suggest.From what we have observed, if the first run of a daily journey happens before the export job for that day is available, the journey ends up using the previous day’s snapshot instead of waiting for the current day’s audience evaluation/export to complete. After that, each subsequent run appears to keep following the same pattern, since it only checks whether a newer snapshot is available compared to the one used in the previous execution.That makes us wonder whether this feature is really behaving as expected. In practice, it seems that if the first run happens too early, the journey can stay one day behind indefinitely, which makes the configuration much less useful for daily journeys than we would expect.The behavior we are expecting is that the journey should

Rules are the quiet workhorses of decisioning. They decide who’s eligible, who’s excluded, and which conditions have to line up before an offer, a message, or an experience is allowed through.They’re also, historically, one of the more technical things a marketer is asked to build — a careful stack of attributes, operators, values, and logic that has to be exactly right to work at all.The gap has always been the translation step. You know, in plain language, exactly who you want to target: “loyalty members in New York who haven’t opted out.” Turning that sentence into a valid rule expression — the right attribute paths, the right operators, the right nesting — is where the friction lives.AI-assisted rule authoring closes that gap. You describe the rule you want in everyday language, and the AI Assistant generates a ready-to-use rule suggestion, complete with the underlying expression, that you can apply to the builder with a single click. This post walks through where to start, how it

Building a Decisioning rule or a ranking formula is only half the job. The harder question is always the same one: will it actually behave the way I think it will?Until now, the honest answer was “let’s find out in production” — you’d wire the rule into a decisioning strategy or a campaign, push it out, and watch the results trickle in. That’s a slow, nervous way to work, and it’s an expensive one when a subtle logic error means the wrong offer reaches the wrong profile.Simulation changes that. You can now test any rule or ranking formula against sample or AI-generated data before you put it to work — right inside the authoring experience, in a few clicks, with no hand-built data and no guesswork. This post walks through both: simulating a rule to confirm it qualifies the right profiles, and simulating a ranking formula to confirm it orders your offers the way you intend. The UsecaseConsider a common scenario. You’ve authored a rule that should only apply to profiles whose favorite cat

I created:Profile-enabled Schema Profile-enabled Dataset Identity configured (Email namespace) Ingested customer data successfully Profiles are visible under Real-Time Customer Profiles Created a Batch Audience using Email Address Created a Journey using Read Audience as the entry activityHowever, the audience always shows:Qualified Audience Size = 0As a result, no profiles enter the journey. What I have already verifiedSchema & DatasetProfile-enabled schema Profile-enabled dataset Data ingestion completed successfully No failed batches in the current datasetProfilesThe profile exists and contains:Email Address First Name Last Name Identity MapAudienceAudience is Published Origin = Segmentation Service Evaluation Type = Batch Population remains 0 MonitoringIn Monitoring I noticed:Last Evaluation Job = No runs (for multiple audiences) Last Activation Job = No runsEven after waiting more than 24 hours, no evaluation job appears.AI Assistant FindingsI also checked using AJO AI Assista

Hi! I can't find anywhere the total amount of campaigns (Action campaigns) supported by ajo. Journeys limit is 200 but what about Campaigns? Thanks!

Your Adobe Journey Optimizer experience could win you $50. 🎁We're gathering feedback from Journey Optimizer customers, and we want to hear from YOU, whether you're in the platform daily or driving the strategy behind it.Two short surveys are live now:✅ Practitioners: Tell us how you use Journey Optimizer's channels, capabilities, and workflows day to day (~5 min)✅ Decision Makers/Leaders: Share what drove your investment in Journey Optimizer and the business impact you've seen (~4 min)👉 Practitioner Survey: https://lnkd.in/gMqTBS85👉 Decision Maker/Leader Survey: https://lnkd.in/g9aJv--cYour input directly shapes what we build next. Every completed survey is entered into a random drawing for a $50 gift card.

Hi all,I'm trying to understand a specific aspect of AJO's decisioning capability. Does AJO's decisioning engine have the ability to generate/select offers purely on its own — using only internal AJO/AEP configuration (like offer eligibility rules, priorities, and constraints) — without needing to pull any profile or event data from an external/3rd party source into AEP?

Im using the following query to consult ClientIDs that entered a specific action (Email action): SELECTDISTINCT identityMap['clientId'] [0] ['id'] AS node_enter_profilesFROMjourney_step_eventsWHERE_experience.journeyOrchestration.stepEvents.journeyVersionID = 'd67b3772-71a9-4d4c-b78f-a7c5373f8034'AND _experience.journeyOrchestration.stepEvents.actionID = 'b5a8420a-899b-437b-97fd-4a425f7a4e71'AND COALESCE(_experience.journeyOrchestration.stepEvents.journeyNodeProcessed,false) = trueAND (_experience.journeyOrchestration.stepEvents.dryRunID IS NULLOR _experience.journeyOrchestration.stepEvents.dryRunID = '')AND COALESCE(_experience.journeyOrchestration.stepEvents.inTest,false) = false Is there a way to include in this query, the date of the start of the journey as well as tags related to the journey?

Adobe will stop supporting Batch Audiences in the Audience qualification start to a journey, and wants either streaming audiences (so 24 hour period max) or use of the read audience start. That means a read audience can’t determine which are new profiles in the audience and just sends to everyone in the audience, which just doesn’t work, or we need to define the audience in batch with very defined limits and have exclusions of people who have been messaged, which is not practical. Campaigns have an iterative type of read to process only new profiles entering the audience, journeys  dont. And campaigns arent an option for Whatsapp or logic around comms segmentation Are there any work arounds that anyone has put in place to negate the potential issues here? I really feel this is a very ill advised change to something that was working very well.

We are investigating unexpected email click-count behavior in Adobe Journey Optimizer and Customer Journey Analytics.For one email recipient, CJA displays:61 Total Clicks 1 Unique ClickThe profile’s email interaction data contains 20 message.tracking click events associated with the same profile, message execution, batch instance, campaign, and message.Here are some findings from within those records. Each click event has a different event _id. There are 19 distinct link labels and urlID values. The recorded links include buttons, ticket links, social links, app-store links, an Add to Calendar link, and other destinations throughout the email. All 20 events occurred between 22:38:45.166 and 22:38:46.383, a period of approximately 1.2 seconds. One link was recorded twice; the remaining events represent different links. Every event has "isBot": falseWe also reviewed the HTML used for the send. The links are represented as separate anchor elements, and the buttons reviewed do not contain

How are organization planning for changes to AJO platform which take you by surprise? Are there any pre-release notes that your Account Manager shares a month before new releases? Or is a there a release plan that you have aligned with your Account Manager so that new releases are first done in DEV environment and then pushed to PROD a week or so later. 

 What We're Hearing? Since rolling out the new canvas experience, one piece of feedback has come up more than any other: connecting and rearranging nodes feels harder than it used to. "I'm unable to select and move a branch." · "Once I disconnect the in-between node, I cannot connect it again." · "Joining nodes is harder in the new experience." The common thread across these comments is drag-and-drop. In the previous canvas, you could grab a node and physically drag it onto a connection point to rewire your journey. The new canvas — rebuilt for better performance and a cleaner layout — replaces that single drag gesture with two explicit actions: Detach and Join.They're not hidden, but they also don't look like what you're used to, so it's easy to miss them. Here's exactly where to find them and how to use them. Journey The Two Actions You Need Action What it does Where to find it Detach Disconnects a node (or an entire downstream branch) from the chain it's in, without deleting

We are using a common footer fragment across multiple email templates. The footer receives a variable (welcomeText) from the email template and renders it using triple braces ({{{welcomeText}}}).When the variable contains HTML tags such as <br>, <sup>, <b>, or <p>, the email validates successfully.However, when the variable contains an HTML anchor (<a href="...">...</a>), the email validation fails with the error:welcomeText of email variant is malformed  Steps to ReproduceCreate a variable in an email template: {% let welcomeText = "<a href='https://google.com'>Google</a>" %} Render the variable in the email or fragment: {{{welcomeText}}} Validate or save the email. Actual ResultThe email validation fails with:welcomeText of email variant is malformed Expected ResultThe variable should accept valid HTML anchor tags in the same way it accepts other supported HTML tags such as <br>, <sup>, <b>, and <p>, allowing the

I assume that I cannot create: custom dimension  custom metric customer filter ? 

Hello, I’m trying to create a Journey using a Read Audience going into an Email. I am trying to only have the profile continue if they click on a specific CTA in the email.  I created an Rule Based Event where I look for a click and Label  However when I run the Journey and Click the email, I do not get the desired result of the second Email. I’ve even tried adding a Reaction Event and then see if the above event triggers and I get nothing,  But when I run a query in the ActionID - I can see clicks and Label. I need to have some assistance figuring this out since this is necessary for a few more reactions I will have in the Journey,  What am I doing wrong? How can I correct this Journey?

 Issue SummaryWe are using a common footer fragment across multiple email templates. The footer receives a variable (welcomeText) from the email template and renders it using triple braces ({{{welcomeText}}}).When the welcomeText variable contains HTML tags such as <br>, <sup>, <b>, or <p>, the email validates successfully.However, when the variable contains an HTML anchor tag (<a href="...">...</a>), the email validation fails with the following error:welcomeText of email variant is malformedSteps to Reproduce Define a variable in the email template: {% let welcomeText = "<a href='https://google.com'>Google</a>" %} Render the variable in the email template or a content fragment using: {{{welcomeText}}} Save or validate the email. Actual ResultThe email validation fails with the following error:welcomeText of email variant is malformedExpected ResultThe welcomeText variable should accept valid HTML anchor tags in the same way it accepts o

Issue SummaryWe are using a common footer fragment across multiple email templates. The footer receives a variable (welcomeText) from the email template and renders it using triple braces ({{{welcomeText}}}).When the welcomeText variable contains HTML tags such as <br>, <sup>, <b>, or <p>, the email validates successfully.However, when the variable contains an HTML anchor tag (<a href="...">...</a>), the email validation fails with the following error:welcomeText of email variant is malformed  Steps to ReproduceDefine a variable in the email template:{% let welcomeText = "<a href='https://google.com'>Google</a>" %}Render the variable in the email template or a content fragment using:{{{welcomeText}}}Save or validate the email.Actual ResultThe email validation fails with the following error:welcomeText of email variant is malformed

Hi, Trying to setup a Journey for a time sensitive cart abandonment scenario. Created a Streaming based Audience with the following definition, "Include audience who have at least 1 Product List Adds event then after 15 minutes do not have any Purchases event and occurs in last 1 hour(s)" But found that the profile will be qualified with this Audience right after a product is added to the cart without waiting for 15mins. Any advice please? Thanks,John

Introduction Personalized content is one of Journey Optimizer's strengths — but it is also one of the hardest things to test before you publish. A single email can personalize the subject line, branch on loyalty points and marital status in the body, and use fallback copy when attributes are missing — all in the same template. Simulate content variations gave you a dedicated screen to preview multiple variants and send proofs without the Adobe Experience Platform test profile workflow. That was a real step forward. But it still left the hardest part on your plate: figuring out which test variants you need, and building each one by hand. The Content Simulation Skill takes that job off your plate entirely. It reads your content, analyzes every conditional branch and personalization field, works out the minimal set of variants needed to cover each branch at least once, and uses AI to fill in realistic profile, context, and target attribute values that satisfy those branches. You preview t