Adobe Journey Optimizer

The business I am working in is currently migrating to Adobe Experience Cloud utilising AEP and AJO as core products. We have discovered the OOTB AJO email seed list capability is not fit-for-purpose. This because the seed list can only be associated with one test profile at each email surface configuration.Our business context:We already have a total of 16 email surface configurations across four brands including consumer, business, marketing, and transactional email communications. There are multiple lines of business within the business, multiple projects on the go at once, and multiple product and marketing campaigns regularly launching.  At any given moment we have thousands of email communications in-market. It is difficult to keep track of what is in-market, and all of the personalised email variations. Marketing & Product want to be able to see all of the email variations in-market, especially when an email incorporates dynamic content. They want the capability to regularly

Hi! I’m working on a use case where an email was not sent because the profile had reached the daily frequency cap.The client would like to keep that communication on hold and retry it the following day. In other words, if the email is excluded today due to capping, it should automatically be sent tomorrow once the profile is eligible again.Is there a way to achieve this behavior in AJO?Thanks! 

Hi, we have a Channel Capping Rule of 1 Email per day shared across multiple journeys.# Example:Journey 1Trigger → EmailJourney 2Trigger → Email 1 → Wait 1d → Email 2 → Wait 1d → Email 3Scenario:Day 1: Journey 2 - Email 1 → SENTDay 2: Journey 1 - Email → SENT       Journey 2 - Email 2 → EXCLUDED by cappingWe need Journey 2 to behave like:Day 3: Retry Email 2Day 4: Email 3The problem is that a capping exclusion does not trigger the Email error path, so the journey continues normally.We also want to avoid creating one recovery journey or audience per communication because it would not scale.Is there a more native/scalable Adobe-recommended solution for this use case? Even with Data Distiller is something dificult to achieve.Thanks.

Is it possible to measure with AJO how much revenue particular email sendout generated?User opened email User went to web User bought something on a webI do not thinks so because I do not see such a metric in AJO but I would like to confirm 

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

I am trying to build a journey using the wave feature to send over 10 days. The send will be flighted each day over the 10 days. I have tried to dry run / use simulation to test the journey, and I keep drawing an error to say last wave must be within 6 days and 18 hours from journey start. Can waves not go beyond this time? Do we have to keep it within 6 days and 18 hours from journey start or is there a way around this? Thanks!  

I see the new 13 month in lake and 90 days in profile store have been implemented across the AJO experience tracking dataset. How is unsubscribe being managed now? I’m seeing cases of where customers have opted out of a communication by clicking the unsubscribe link, being opted back in. the unsub is in the lake, but not in profile any more. What is Adobe doing to manage this? I’m seeing massive GDPR issues here, unless I’m hopefully mistaken regardsMaec

Hi All I have a requirement for a landing page with five Opt-in/Opt-out services.If a user selects one or more specific services for Opt-out and then clicks the Call-to-Action (CTA) button, only the selected services should be opted out. If the user clicks the CTA button without selecting any specific service, the user should be opted out of all five services by default.How can we implement this logic in AJO? Thanks Gowtham Raj

Is there something to consider for push daily capping? I've applied capping to push but users are receving the push even with the daily capping.

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 all,I have a requirement for a landing page with five Opt-in/Opt-out services.If a user selects one or more specific services for Opt-out and then clicks the Call-to-Action (CTA) button, only the selected services should be opted out. If the user clicks the CTA button without selecting any specific service, the user should be opted out of all five services by default.How can we implement this logic in AJO? Thanks Gowtham Raj

How would you debug Ranking Formula in Decisioning?Create selection strategy in code base campaign with test profiles and check if for specific profiles best offer is returned?  

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

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

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!

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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?